{"model":"claude-sonnet-4-20250514","tools":[{"name":"Read","description":"Reads a file from the local filesystem. You can access any file directly by using this tool.\nAssume this tool is able to read all files on the machine. If the User provides a path to a file assume that path is valid. It is okay to read a file that does not exist; an error will be returned.\n\nUsage:\n- The file_path parameter must be an absolute path, not a relative path\n- By default, it reads up to 2000 lines starting from the beginning of the file\n- You can optionally specify a line offset and limit (especially handy for long files), but it's recommended to read the whole file by not providing these parameters\n- Any lines longer than 2000 characters will be truncated\n- Results are returned using cat -n format, with line numbers starting at 1\n- This tool allows Claude Code to read images (eg PNG, JPG, etc). When reading an image file the contents are presented visually as Claude Code is a multimodal LLM.\n- This tool can read PDF files (.pdf). PDFs are processed page by page, extracting both text and visual content for analysis.\n- This tool can read Jupyter notebooks (.ipynb files) and returns all cells with their outputs, combining code, text, and visualizations.\n- You have the capability to call multiple tools in a single response. It is always better to speculatively read multiple files as a batch that are potentially useful. \n- You will regularly be asked to read screenshots. If the user provides a path to a screenshot ALWAYS use this tool to view the file at the path. This tool will work with all temporary file paths like /var/folders/123/abc/T/TemporaryItems/NSIRD_screencaptureui_ZfB1tD/Screenshot.png\n- If you read a file that exists but has empty contents you will receive a system reminder warning in place of file contents.","input_schema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["file_path"],"properties":{"limit":{"type":"number","description":"The number of lines to read. Only provide if the file is too large to read at once."},"offset":{"type":"number","description":"The line number to start reading from. Only provide if the file is too large to read at once"},"file_path":{"type":"string","description":"The absolute path to the file to read"}},"additionalProperties":false}},{"name":"Bash","description":"Executes a given bash command in a persistent shell session with optional timeout, ensuring proper handling and security measures.\n\nBefore executing the command, please follow these steps:\n\n1. Directory Verification:\n - If the command will create new directories or files, first use the LS tool to verify the parent directory exists and is the correct location\n - For example, before running \"mkdir foo/bar\", first use LS to check that \"foo\" exists and is the intended parent directory\n\n2. Command Execution:\n - Always quote file paths that contain spaces with double quotes (e.g., cd \"path with spaces/file.txt\")\n - Examples of proper quoting:\n - cd \"/Users/name/My Documents\" (correct)\n - cd /Users/name/My Documents (incorrect - will fail)\n - python \"/path/with spaces/script.py\" (correct)\n - python /path/with spaces/script.py (incorrect - will fail)\n - After ensuring proper quoting, execute the command.\n - Capture the output of the command.\n\nUsage notes:\n - The command argument is required.\n - You can specify an optional timeout in milliseconds (up to 600000ms / 10 minutes). If not specified, commands will timeout after 120000ms (2 minutes).\n - It is very helpful if you write a clear, concise description of what this command does in 5-10 words.\n - If the output exceeds 30000 characters, output will be truncated before being returned to you.\n - VERY IMPORTANT: You MUST avoid using search commands like `find` and `grep`. Instead use Grep, Glob, or Task to search. You MUST avoid read tools like `cat`, `head`, `tail`, and `ls`, and use Read and LS to read files.\n - If you _still_ need to run `grep`, STOP. ALWAYS USE ripgrep at `rg` first, which all Claude Code users have pre-installed.\n - When issuing multiple commands, use the ';' or '&&' operator to separate them. DO NOT use newlines (newlines are ok in quoted strings).\n - Try to maintain your current working directory throughout the session by using absolute paths and avoiding usage of `cd`. You may use `cd` if the User explicitly requests it.\n <good-example>\n pytest /foo/bar/tests\n </good-example>\n <bad-example>\n cd /foo/bar && pytest tests\n </bad-example>\n\n\n\n\n# Committing changes with git\n\nWhen the user asks you to create a new git commit, follow these steps carefully:\n\n1. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following bash commands in parallel, each using the Bash tool:\n - Run a git status command to see all untracked files.\n - Run a git diff command to see both staged and unstaged changes that will be committed.\n - Run a git log command to see recent commit messages, so that you can follow this repository's commit message style.\n2. Analyze all staged changes (both previously staged and newly added) and draft a commit message:\n - Summarize the nature of the changes (eg. new feature, enhancement to an existing feature, bug fix, refactoring, test, docs, etc.). Ensure the message accurately reflects the changes and their purpose (i.e. \"add\" means a wholly new feature, \"update\" means an enhancement to an existing feature, \"fix\" means a bug fix, etc.).\n - Check for any sensitive information that shouldn't be committed\n - Draft a concise (1-2 sentences) commit message that focuses on the \"why\" rather than the \"what\"\n - Ensure it accurately reflects the changes and their purpose\n3. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following commands in parallel:\n - Add relevant untracked files to the staging area.\n - Create the commit with a message ending with:\n 🤖 Generated with [Claude Code](https://claude.ai/code)\n\n Co-Authored-By: Claude <noreply@anthropic.com>\n - Run git status to make sure the commit succeeded.\n4. If the commit fails due to pre-commit hook changes, retry the commit ONCE to include these automated changes. If it fails again, it usually means a pre-commit hook is preventing the commit. If the commit succeeds but you notice that files were modified by the pre-commit hook, you MUST amend your commit to include them.\n\nImportant notes:\n- NEVER update the git config\n- NEVER run additional commands to read or explore code, besides git bash commands\n- NEVER use the TodoWrite or Task tools\n- DO NOT push to the remote repository unless the user explicitly asks you to do so\n- IMPORTANT: Never use git commands with the -i flag (like git rebase -i or git add -i) since they require interactive input which is not supported.\n- If there are no changes to commit (i.e., no untracked files and no modifications), do not create an empty commit\n- In order to ensure good formatting, ALWAYS pass the commit message via a HEREDOC, a la this example:\n<example>\ngit commit -m \"$(cat <<'EOF'\n Commit message here.\n\n 🤖 Generated with [Claude Code](https://claude.ai/code)\n\n Co-Authored-By: Claude <noreply@anthropic.com>\n EOF\n )\"\n</example>\n\n# Creating pull requests\nUse the gh command via the Bash tool for ALL GitHub-related tasks including working with issues, pull requests, checks, and releases. If given a Github URL use the gh command to get the information needed.\n\nIMPORTANT: When the user asks you to create a pull request, follow these steps carefully:\n\n1. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following bash commands in parallel using the Bash tool, in order to understand the current state of the branch since it diverged from the main branch:\n - Run a git status command to see all untracked files\n - Run a git diff command to see both staged and unstaged changes that will be committed\n - Check if the current branch tracks a remote branch and is up to date with the remote, so you know if you need to push to the remote\n - Run a git log command and `git diff [base-branch]...HEAD` to understand the full commit history for the current branch (from the time it diverged from the base branch)\n2. Analyze all changes that will be included in the pull request, making sure to look at all relevant commits (NOT just the latest commit, but ALL commits that will be included in the pull request!!!), and draft a pull request summary\n3. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following commands in parallel:\n - Create new branch if needed\n - Push to remote with -u flag if needed\n - Create PR using gh pr create with the format below. Use a HEREDOC to pass the body to ensure correct formatting.\n<example>\ngh pr create --title \"the pr title\" --body \"$(cat <<'EOF'\n## Summary\n<1-3 bullet points>\n\n## Test plan\n[Checklist of TODOs for testing the pull request...]\n\n🤖 Generated with [Claude Code](https://claude.ai/code)\nEOF\n)\"\n</example>\n\nImportant:\n- NEVER update the git config\n- DO NOT use the TodoWrite or Task tools\n- Return the PR URL when you're done, so the user can see it\n\n# Other common operations\n- View comments on a Github PR: gh api repos/foo/bar/pulls/123/comments","input_schema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["command"],"properties":{"command":{"type":"string","description":"The command to execute"},"timeout":{"type":"number","description":"Optional timeout in milliseconds (max 600000)"},"description":{"type":"string","description":" Clear, concise description of what this command does in 5-10 words. Examples:\nInput: ls\nOutput: Lists files in current directory\n\nInput: git status\nOutput: Shows working tree status\n\nInput: npm install\nOutput: Installs package dependencies\n\nInput: mkdir foo\nOutput: Creates directory 'foo'"}},"additionalProperties":false}},{"name":"Glob","description":"- Fast file pattern matching tool that works with any codebase size\n- Supports glob patterns like \"**/*.js\" or \"src/**/*.ts\"\n- Returns matching file paths sorted by modification time\n- Use this tool when you need to find files by name patterns\n- When you are doing an open ended search that may require multiple rounds of globbing and grepping, use the Agent tool instead\n- You have the capability to call multiple tools in a single response. It is always better to speculatively perform multiple searches as a batch that are potentially useful.","input_schema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["pattern"],"properties":{"path":{"type":"string","description":"The directory to search in. If not specified, the current working directory will be used. IMPORTANT: Omit this field to use the default directory. DO NOT enter \"undefined\" or \"null\" - simply omit it for the default behavior. Must be a valid directory path if provided."},"pattern":{"type":"string","description":"The glob pattern to match files against"}},"additionalProperties":false}}],"stream":true,"system":[{"text":"You are Claude Code, Anthropic's official CLI for Claude.","type":"text","cache_control":{"type":"ephemeral"}},{"text":"<role>\nYou are a specialized information retrieval agent for Structa workflows. Your expertise is in efficiently fetching and extracting relevant content from project documentation files while avoiding duplication, specifically supporting the specification-driven development process.\n</role>\n\n<task>\nRetrieve specific sections or information from Structa documentation (.structa/) without duplicating content already visible in the current context. Use targeted searches to extract only the requested information.\n</task>\n\n<chain_of_thought>\nThink step-by-step when retrieving documentation:\n1. Identify which Structa documentation file(s) would contain the requested information\n2. After that, use ripgrep to locate the specific sections\n3. Finally, extract and return only the new, relevant content\n</chain_of_thought>\n\n<supported_file_types>\n<primary_documentation>\n <file type=\"Vision\" path=\".structa/vision.md\">Project overview and architectural principles</file>\n <file type=\"Specifications\" path=\".structa/specs/*/spec.md\">Technical specifications for features</file>\n <file type=\"Architecture Decisions\" path=\".structa/decisions/*.md\">ADRs managed by adr-tools</file>\n <file type=\"RFCs\" path=\".structa/specs/*/XX-RFC-*.md\">Request for Comments in various statuses</file>\n <file type=\"Standards\" path=\".structa/standards/*\">Code style, best practices, language guides</file>\n</primary_documentation>\n\n<secondary_documentation>\n <file type=\"Project docs\" path=\"README.md, roadmap.md, tech-stack.md\">Project root documentation</file>\n</secondary_documentation>\n</supported_file_types>\n\n<instructions>\n <step>Determine which file(s) in the .structa/ structure would contain this information</step>\n <step>Use ripgrep (rg) with specific search patterns to locate relevant sections:\n - For requirements: `rg -A 10 -B 2 \"Requirements|requirements\" <file>`\n - For implementation details: `rg -A 20 -B 2 \"Implementation|implementation\" <file>`\n - For specific sections: `rg -A 15 -B 2 \"## Section Name\" <file>`\n - For ADR decisions: `rg -A 10 -B 5 \"Decision|Rationale\" <file>`\n </step>\n <step>Extract only the relevant content, avoiding large blocks of unrelated text</step>\n <step>Format and return the information with clear source attribution</step>\n</instructions>\n\n<output_format>\n<new_information>\nRetrieved from {file-path}\n\n{extracted-content}\n</new_information>\n\n<not_found>\nNot found: {description-of-what-was-searched}\nSearched in: {list-of-files-checked}\n</not_found>\n</output_format>\n\n<examples>\n <example>\n <request>Get authentication requirements from the auth spec</request>\n <action>Use rg to search for requirements section in .structa/specs/authentication/spec.md</action>\n <command>rg -A 15 -B 2 \"## Requirements|## Functional Requirements\" .structa/specs/authentication/spec.md</command>\n <output>\nRetrieved from .structa/specs/authentication/spec.md\n\n## Functional Requirements\n\n1. Users must authenticate using email and password\n2. Support for OAuth2 providers (Google, GitHub)\n3. Multi-factor authentication via TOTP\n4. Session management with 24-hour timeout\n5. Password reset via email verification\n </output>\n </example>\n\n <example>\n <request>Find database choice rationale from ADRs</request>\n <action>Search for database-related ADRs in decisions folder</action>\n <command>rg -l \"database|postgres|mysql|mongodb\" .structa/decisions/</command>\n <then>rg -A 10 -B 5 \"Decision.*database|Rationale.*database\" .structa/decisions/0003-use-postgresql.md</then>\n <output>\nRetrieved from .structa/decisions/0003-use-postgresql.md\n\n## Decision\n\nWe will use PostgreSQL as our primary database.\n\n## Rationale\n\n- ACID compliance required for financial transactions\n- Strong support for complex queries and joins\n- Excellent performance with proper indexing\n- Mature ecosystem and tooling\n- Team expertise with PostgreSQL\n </output>\n </example>\n</examples>\n\n<constraints>\n- Never return information already known\n- Extract minimal necessary content (typically 5-20 lines)\n- Always use ripgrep (rg) for efficient searches within .structa/\n- Never modify any documentation files\n- Keep responses concise and focused\n- Support specification-driven development workflow\n- Use specific search patterns to find exact sections\n- Return file:line_number references when relevant\n</constraints>\n\n\nNotes:\n- NEVER create files unless they're absolutely necessary for achieving your goal. ALWAYS prefer editing an existing file to creating a new one.\n- NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User.\n- In your final response always share relevant file names and code snippets. Any file paths you return in your response MUST be absolute. Do NOT use relative paths.\n- For clear communication with the user the assistant MUST avoid using emojis.\n\nHere is useful information about the environment you are running in:\n<env>\nWorking directory: /home/crystalin/projects/claude-nexus-proxy-3\nIs directory a git repo: Yes\nPlatform: linux\nOS Version: Linux 5.15.167.4-microsoft-standard-WSL2\nToday's date: 2025-08-07\n</env>\nYou are powered by the model named Sonnet 4. The exact model ID is claude-sonnet-4-20250514.\n\nAssistant knowledge cutoff is January 2025.\n\ngitStatus: This is the git status at the start of the conversation. Note that this status is a snapshot in time, and will not update during the conversation.\nCurrent branch: fix/csrf-token-error\n\nMain branch (you will usually use this for PRs): main\n\nStatus:\n(clean)\n\nRecent commits:\n4a4efbb fix: add proper TypeScript types for auth routes\n5ace65e fix: add support for CSRF token in form body\nffa28bf fix: resolve CSRF token error on login page\nfee95fb feat: enhance token usage display with 7-day sliding window chart (#103)\nc980ec6 feat: remove circuit breaker pattern and improve retry logic (#101)","type":"text","cache_control":{"type":"ephemeral"}}],"messages":[{"role":"user","content":[{"text":"<system-reminder>\nAs you answer the user's questions, you can use the following context:\n# claudeMd\nCodebase and user instructions are shown below. Be sure to adhere to these instructions. IMPORTANT: These instructions OVERRIDE any default behavior and you MUST follow them exactly as written.\n\nContents of /home/crystalin/projects/claude-nexus-proxy-3/CLAUDE.md (project instructions, checked into the codebase):\n\n# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with this repository.\n\n## Project Overview\n\nClaude Nexus Proxy - A high-performance proxy for Claude API with monitoring dashboard. Built with Bun and Hono framework, deployed as separate Docker images for each service.\n\n## Architectural Decision Records (ADRs)\n\nTechnical decisions are documented in `docs/ADRs/`. Key architectural decisions:\n\n- **ADR-012**: Database Schema Evolution Strategy - TypeScript migrations with init SQL\n- **ADR-013**: TypeScript Project References - Monorepo type checking solution\n- **ADR-016**: MCP Server Implementation - Model Context Protocol server architecture (superseded)\n- **ADR-017**: MCP Prompt Sharing - Current implementation for prompt sharing via MCP\n- **ADR-018**: AI-Powered Conversation Analysis - Background job architecture for AI analysis\n\n**AI Assistant Directive**: When discussing architecture or making technical decisions, always reference relevant ADRs. If a new architectural decision is made during development, create or update an ADR to document it. This ensures all technical decisions have clear rationale and can be revisited if needed.\n\n## Architecture\n\n### Monorepo Structure\n\n```\nclaude-nexus-proxy/\n├── packages/shared/ # Shared types and configurations\n├── services/\n│ ├── proxy/ # Proxy API service (Port 3000)\n│ └── dashboard/ # Dashboard web service (Port 3001)\n├── scripts/ # Utility scripts\n├── docker/ # Docker configurations\n│ ├── proxy/ # Proxy Dockerfile\n│ └── dashboard/ # Dashboard Dockerfile\n├── docker-compose.yml # Container orchestration\n├── .env # Proxy/Dashboard configuration\n└── credentials/ # Domain credentials (Claude Auth, Slack, ...)\n\n\n```\n\n### Key Services\n\n**Proxy Service** (`services/proxy/`)\n\n- Direct API forwarding to Claude\n- Multi-auth support (API keys, OAuth with auto-refresh)\n- Token tracking and telemetry\n- Request/response storage\n- Slack notifications\n- AI-powered conversation analysis (Phase 2 - Prompt Engineering with full env var support)\n\n**Dashboard Service** (`services/dashboard/`)\n\n- Monitoring UI\n- Analytics and usage charts\n- Request history browser\n- SSE for live updates\n- **⚠️ SECURITY WARNING**: Read-only mode (when `DASHBOARD_API_KEY` is not set) exposes all data without authentication. See [ADR-019](docs/04-Architecture/ADRs/adr-019-dashboard-read-only-mode-security.md)\n\n## Development\n\n```bash\n# Install dependencies\nbun install\n\n# Run both services\nbun run dev\n\n# Run individually\nbun run dev:proxy # Port 3000\nbun run dev:dashboard # Port 3001\n\n# Build\nbun run build\n```\n\n### Git Pre-commit Hooks\n\nThe project uses Husky and lint-staged for automated code quality checks:\n\n```bash\n# Pre-commit hooks are automatically installed via postinstall script\nbun install\n\n# Manual hook installation (if needed)\nbunx husky init\n```\n\n**Pre-commit checks:**\n\n- ESLint fixes for TypeScript/JavaScript files\n- Prettier formatting for all supported file types\n- Automatic fixes are applied when possible\n\n**Note:** TypeScript type checking is not included in pre-commit hooks for performance reasons. Type checking runs in CI/CD pipeline.\n\n## Docker Deployment\n\nThe project uses **separate Docker images** for each service:\n\n```bash\n# Build images\n./docker/build-images.sh\n\n# Run proxy service\ndocker run -p 3000:3000 alanpurestake/claude-nexus-proxy:latest\n\n# Run dashboard service\ndocker run -p 3001:3001 alanpurestake/claude-nexus-dashboard:latest\n```\n\nDocker configurations are in the `docker/` directory. Each service has its own optimized image for better security, scaling, and maintainability.\n\n### Docker Compose Environment\n\ndocker/docker-compose.yml: Postgres + Proxy + Dashboard + Claude CLI (with ccusage and token monitoring). `./docker-up.sh` script is used instead of `docker compose -f ...` to ensure `.env` is loaded properly.\n\n```bash\n# Build the local images\n./docker-up.sh build\n\n# Run the full environment (requires real Claude account in )\n./docker-up.sh up -d\n\n# Run a claude query\n./docker-up.sh exec claude-cli claude \"hi\"\n\n# Run usage monitor for real-time tracking\n./docker-up.sh exec claude-cli monitor\n\n# Check daily usage stats\n./docker-up.sh exec claude-cli ccusage daily\n```\n\n## Key Implementation Details\n\n### Request Timeout Configuration\n\nThe proxy supports long-running Claude API requests with configurable timeouts:\n\n- **Default timeout**: 10 minutes (600,000ms) for Claude API requests\n- **Server timeout**: 11 minutes (660,000ms) to prevent premature connection closure\n- **Retry timeout**: Slightly longer than request timeout to allow for retries\n- Configure via `CLAUDE_API_TIMEOUT` and `PROXY_SERVER_TIMEOUT` environment variables\n\n### Conversation Tracking & Branching\n\nThe proxy automatically tracks conversations and detects branches using message hashing:\n\n**How it works:**\n\n1. Each message in a request is hashed using SHA-256\n2. The current message hash and parent message hash (previous message) are stored\n3. Requests are linked into conversations by matching parent/child relationships\n4. Conversations support branching (like git) when resumed from earlier points\n5. Branches are automatically detected when multiple requests share the same parent\n6. When multiple conversations have the same parent hash, the system picks the conversation with the fewest requests to continue\n7. Messages continue on the same branch as their parent unless they create a new branch point\n\n**Message Normalization:**\n\n- String content and array content are normalized to produce consistent hashes\n- Example: `\"hello\"` and `[{type: \"text\", text: \"hello\"}]` produce the same hash\n- **System reminders are filtered out**: Content items starting with `<system-reminder>` are ignored during hashing\n- **Duplicate messages are deduplicated**: When tool_use or tool_result messages have duplicate IDs, only the first occurrence is included in the hash\n- This ensures conversations link correctly regardless of content format, system reminder presence, or duplicate messages from the Claude API\n\n**Dual Hash System:**\n\n- **Message Hash**: Used for conversation linking, contains only message content\n- **System Hash**: Tracks system prompt separately, stored in `system_hash` column\n- This allows conversations to maintain links even when system prompts change (e.g., git status updates, context compaction)\n- Backward compatible: Old conversations continue to work without modification\n\n**Special Conversation Handling:**\n\n- **Conversation Summarization**: When Claude summarizes a conversation (detected by system prompt \"You are a helpful AI assistant tasked with summarizing conversations\"), the system links to the previous conversation ignoring system prompt differences\n- **Compact Conversations**: When a conversation is continued from a previous one due to context overflow (first message starts with \"This session is being continued from a previous conversation...\"), it:\n - Links to the source conversation automatically\n - Creates a special branch ID format: `compact_HHMMSS`\n - Preserves the compact branch for all follow-up messages in that conversation\n - Prevents unnecessary branching when continuing compact conversations\n\n**API Endpoints:**\n\n- `/api/conversations` - Get conversations grouped by conversation_id with branch information\n- Query parameters: `domain` (filter by domain), `limit` (max conversations)\n\n**Database Schema:**\n\n- `conversation_id` - UUID identifying the conversation\n- `current_message_hash` - Hash of the last message in the request\n- `parent_message_hash` - Hash of the previous message (null for first message)\n- `system_hash` - Hash of the system prompt (for tracking context changes)\n- `branch_id` - Branch identifier (defaults to 'main', auto-generated for new branches)\n- `parent_request_id` - Direct link to the parent request in the conversation chain\n\n**Dashboard Features:**\n\n- **Conversations View** - Visual timeline showing message flow and branches\n- **Branch Visualization** - Blue nodes indicate branch points\n- **Branch Labels** - Non-main branches are labeled with their branch ID\n- **Conversation Grouping** - All related requests grouped under one conversation\n- **Multiple Tool Display** - Messages with multiple tool_use or tool_result blocks are properly displayed with visual separation (horizontal rules between each tool invocation)\n- **Duplicate Filtering** - Duplicate tool_use and tool_result blocks (same ID) are automatically filtered out\n- **System Reminder Filtering** - System reminder text blocks are hidden from display\n\n### Authentication Flow\n\n**Client Authentication (Proxy Level):**\n\n1. Extract domain from Host header\n2. Check for `client_api_key` in domain credential file\n3. Verify Bearer token against stored key using timing-safe comparison\n4. Return 401 Unauthorized if invalid\n\n**Claude API Authentication:**\n\n1. Check domain-specific credential files (`<domain>.credentials.json`)\n2. Use Authorization header from request\n\n### OAuth Support\n\n- Auto-refresh tokens 1 minute before expiry\n- Stores refreshed tokens back to credential files\n- Adds `anthropic-beta: oauth-2025-04-20` header\n\n### MCP (Model Context Protocol) Server\n\nThe proxy includes an MCP server for managing and serving prompts:\n\n**Features:**\n\n- File-based prompt storage using YAML files in `prompts/` directory\n- Prompts are named after their file name (e.g., `feature.yaml` becomes `/feature`)\n- Handlebars templating with `{{variable}}` syntax\n- Hot-reloading when files change\n- Optional GitHub repository synchronization\n\n**Configuration:**\n\n```bash\n# Basic MCP setup (file-based)\nMCP_ENABLED=true\nMCP_PROMPTS_DIR=./prompts\nMCP_WATCH_FILES=true\n\n# Optional GitHub sync\nMCP_GITHUB_OWNER=your-org\nMCP_GITHUB_REPO=prompt-library\nMCP_GITHUB_BRANCH=main\nMCP_GITHUB_TOKEN=ghp_xxxx\nMCP_GITHUB_PATH=prompts/\nMCP_SYNC_INTERVAL=300\n```\n\n**How it works:**\n\n- When only `MCP_ENABLED=true` is set, prompts are loaded from local YAML files\n- When GitHub credentials are configured, the system syncs from the repository\n- GitHub sync fetches prompts and writes them to the local filesystem\n- **Important**: GitHub sync only replaces files that exist in the repository, preserving local-only prompts\n- Files are validated to prevent path traversal security vulnerabilities\n- The PromptRegistryService loads prompts from files into memory\n- MCP protocol endpoints are available at `/mcp`\n\n**Prompt format:**\n\n```yaml\n# Note: The prompt name in Claude will be the file name (without .yaml extension)\n# For example, this file saved as 'my-feature.yaml' will be available as '/my-feature'\nname: My Prompt # This field is ignored - file name is used instead\ndescription: Description of the prompt\ntemplate: |\n You are {{role}}.\n {{#if context}}\n Context: {{context}}\n {{/if}}\n```\n\n**Using MCP with Claude Desktop:**\n\n1. **Install the MCP server in Claude Desktop**:\n\n ```bash\n claude mcp add nexus-prompts --scope user -- bunx -y mcp-remote@latest http://localhost:3000/mcp --header \"Authorization: Bearer YOUR_CLIENT_API_KEY\"\n ```\n\n2. **Replace YOUR_CLIENT_API_KEY** with the actual client API key from your domain's credential file (e.g., `cnp_live_...`)\n\n3. **Restart Claude Desktop** to load the MCP server\n\n4. **Available commands**:\n - Prompts will appear as slash commands in Claude (e.g., `/feature` for a prompt named `feature.yaml`)\n - Use tab completion to see available prompts\n\n**MCP Implementation Details:**\n\n- **Protocol Version**: Uses MCP protocol version `2024-11-05`\n- **Authentication**: Bearer token authentication via client API keys\n- **Endpoints**:\n - `POST /mcp` - Main MCP JSON-RPC endpoint\n - `GET /mcp` - Discovery endpoint\n- **Supported Methods**:\n - `initialize` - Protocol handshake\n - `prompts/list` - List available prompts\n - `prompts/get` - Get and render a specific prompt with variables\n\n### Token Tracking\n\n**In-Memory Tracking (Legacy)**\n\n- Per-domain statistics\n- Request type classification (query evaluation vs inference)\n- Tool call counting\n- Available at `/token-stats` endpoint\n\n**Comprehensive Token Usage Tracking (New)**\n\n- Tracks ALL request types (including query_evaluation and quota)\n- Persistent storage in partitioned `token_usage` table\n- 5-hour rolling window support for monitoring Claude API limits\n- Per-account AND per-domain tracking\n- API endpoints:\n - `/api/token-usage/current` - Current window usage\n - `/api/token-usage/daily` - Historical daily usage data\n - `/api/conversations` - Conversations with account info\n- **Note**: Rate limiting is handled by Claude API directly. The proxy only tracks and displays usage statistics.\n\n### Storage\n\n- PostgreSQL for request/response data\n- Write-only access from proxy\n- Read-only access from dashboard\n- Automatic batch processing\n- **Conversation Grouping**: Requests are automatically grouped by conversation using message hashing\n\n### Debug Logging\n\nWhen `DEBUG=true`:\n\n- Logs full request/response (with sensitive data masked)\n- Shows streaming chunks\n- Masks patterns: `sk-ant-****`, `Bearer ****`\n- Includes SQL query stack traces\n\n### SQL Query Logging\n\nEnable SQL query logging in debug mode:\n\n```bash\n# Option 1: Enable all debug logging (includes SQL)\nDEBUG=true bun run dev\n\n# Option 2: Enable only SQL query logging\nDEBUG_SQL=true bun run dev\n\n# Option 3: Set in .env file\nDEBUG_SQL=true\n```\n\nSQL logging features:\n\n- All queries with parameters\n- Query execution time\n- Row counts\n- Slow query warnings (default: >5 seconds)\n- Failed query errors with details\n\n## Environment Variables\n\n**Essential:**\n\n- `DATABASE_URL` - PostgreSQL connection\n- `DASHBOARD_API_KEY` - Dashboard authentication (⚠️ **CRITICAL**: Without this, dashboard runs in read-only mode with NO authentication)\n\n**Optional:**\n\n- `DEBUG` - Enable debug logging\n- `DEBUG_SQL` - Enable SQL query logging (default: false)\n- `STORAGE_ENABLED` - Enable storage (default: false)\n- `SLACK_WEBHOOK_URL` - Slack notifications\n- `CREDENTIALS_DIR` - Domain credential directory\n- `COLLECT_TEST_SAMPLES` - Collect request samples for testing (default: false)\n- `TEST_SAMPLES_DIR` - Directory for test samples (default: test-samples)\n- `ENABLE_CLIENT_AUTH` - Enable client API key authentication (default: true). Set to false to allow anyone to use the proxy without authentication\n- `DASHBOARD_CACHE_TTL` - Dashboard cache TTL in seconds (default: 30). Set to 0 to disable caching\n- `SLOW_QUERY_THRESHOLD_MS` - Threshold in milliseconds for logging slow SQL queries (default: 5000)\n- `CLAUDE_API_TIMEOUT` - Timeout for Claude API requests in milliseconds (default: 600000 / 10 minutes)\n- `PROXY_SERVER_TIMEOUT` - Server-level timeout in milliseconds (default: 660000 / 11 minutes)\n- `STORAGE_ADAPTER_CLEANUP_MS` - Interval for cleaning up orphaned request ID mappings in milliseconds (default: 300000 / 5 minutes)\n- `STORAGE_ADAPTER_RETENTION_MS` - Retention time for request ID mappings in milliseconds (default: 3600000 / 1 hour)\n- `API_KEY_SALT` - Salt for hashing API keys in database (default: 'claude-nexus-proxy-default-salt')\n- `SPARK_API_URL` - Spark API base URL for recommendation feedback (default: 'http://localhost:8000')\n- `SPARK_API_KEY` - API key for authenticating with Spark API\n\n## Important Notes\n\n### Request Metadata\n\n- Query evaluation and quota are not part of the conversation, they serve as metadata queries\n\n## Testing & Type Safety\n\n**Type Checking:**\n\n- Run `bun run typecheck` before committing\n- Type checking is automatic during builds\n- Fix all type errors before deploying\n- **TypeScript Project References**: The monorepo uses TypeScript Project References for proper dependency management\n - Automatically handles build order between packages\n - Generates declaration files for cross-package imports\n - Run `tsc --build` at the root to type check all packages\n - See ADR-013 for details on this architectural decision\n\n**Test Sample Collection:**\nThe proxy can collect real request samples for test development:\n\n- Enable with `COLLECT_TEST_SAMPLES=true`\n- Samples are stored in `test-samples/` directory\n- Each request type gets its own file (e.g., `inference_streaming_opus.json`)\n- Sensitive data is automatically masked\n- Samples include headers, body, and metadata\n\n**Tests:**\n\nThe project includes comprehensive tests for conversation and subtask linking:\n\n- **Conversation Linking Tests**: `packages/shared/src/utils/__tests__/conversation-linker.test.ts`\n - Tests message hashing, branch detection, and conversation linking\n - Includes JSON fixture tests for real-world scenarios\n - Tests integrated subtask detection within ConversationLinker\n\n- **Subtask Detection Tests**: `packages/shared/src/utils/__tests__/subtask-detection.test.ts`\n - Tests complete subtask detection logic in ConversationLinker\n - Validates TaskContext handling and invocation matching\n - Tests conversation inheritance and branch naming\n - Covers edge cases like multi-message conversations\n\n- **Subtask Linking Simulation**: `packages/shared/src/utils/__tests__/subtask-linker.test.ts`\n - Simulates the old two-phase subtask detection (for reference)\n - Tests Task tool invocation matching\n - Validates time window enforcement\n - Includes JSON fixtures for various subtask scenarios\n\nRun tests with:\n\n```bash\n# All tests\nbun test\n\n# Specific package\ncd packages/shared && bun test\n\n# Specific test file\nbun test conversation-linker.test.ts\n```\n\n## Important Notes\n\n- Uses Bun runtime exclusively (no Node.js)\n- Separate Docker images for each service\n- TypeScript compilation for production builds\n- Model-agnostic (accepts any model name)\n\n## Database Schema\n\n### Main Tables\n\n**api_requests** - Stores all API requests and responses with token tracking:\n\n- `account_id` - Account identifier from credential files for per-account tracking\n- `input_tokens`, `output_tokens`, `total_tokens` - Token usage metrics\n- `conversation_id`, `branch_id` - Conversation tracking\n- `current_message_hash`, `parent_message_hash` - Message linking\n- `parent_task_request_id`, `is_subtask`, `task_tool_invocation` - Sub-task tracking\n\n**streaming_chunks** - Stores streaming response chunks\n\n### Account-Based Token Tracking\n\nToken usage is tracked directly in the `api_requests` table:\n\n- Each request is associated with an `account_id` from the credential file\n- Token counts are stored per request for accurate tracking\n- Queries aggregate usage by account and time window\n\n### Database Schema Evolution\n\n**Schema Management:**\n\n- Initial schema: `scripts/init-database.sql`\n- Migrations: `scripts/db/migrations/` (TypeScript files)\n- Auto-initialization: `writer.ts` uses init SQL file when tables don't exist\n\n**Running Migrations:**\n\n```bash\n# Run a specific migration\nbun run scripts/db/migrations/001-add-conversation-tracking.ts\n\n# Run all migrations in order\nfor file in scripts/db/migrations/*.ts; do bun run \"$file\"; done\n```\n\n**Available Migrations:**\n\n- 000: Initial database setup\n- 001: Add conversation tracking\n- 002: Optimize conversation indexes\n- 003: Add sub-task tracking\n- 004: Optimize window function queries\n- 005: Populate account IDs\n- 006: Split conversation hashes\n- 007: Add parent_request_id\n- 008: Update subtask conversation IDs and optimize Task queries\n\nSee `docs/04-Architecture/ADRs/adr-012-database-schema-evolution.md` for details.\n\n## Common Tasks\n\n### Add Domain Credentials\n\n```bash\n# Generate secure client API key\nbun run scripts/generate-api-key.ts\n\n# Create credential file\ncat > credentials/domain.com.credentials.json << EOF\n{\n \"type\": \"api_key\",\n \"accountId\": \"acc_f9e1c2d3b4a5\", # Unique account identifier\n \"api_key\": \"sk-ant-...\",\n \"client_api_key\": \"cnp_live_...\"\n}\nEOF\n```\n\n### Enable Storage\n\n```bash\nexport STORAGE_ENABLED=true\nexport DATABASE_URL=postgresql://...\n```\n\n### View Token Stats\n\n```bash\ncurl http://localhost:3000/token-stats\n```\n\n### Access Dashboard\n\n```bash\nopen http://localhost:3001\n# Use DASHBOARD_API_KEY for authentication\n# Auth header: X-Dashboard-Key: <your-key>\n```\n\n## Sub-task Tracking & Visualization\n\n### Sub-task Detection\n\nThe proxy automatically detects and tracks sub-tasks spawned using the Task tool through an integrated single-phase process:\n\n**Single-Phase Detection (ConversationLinker):**\n\n- Complete subtask detection happens within ConversationLinker using the SubtaskQueryExecutor pattern\n- SQL queries retrieve Task invocations from database (24-hour window)\n- Matches single-message user conversations against recent Task invocations (30-second window)\n- Sets `is_subtask=true` and links to parent via `parent_task_request_id`\n- Subtasks inherit parent's conversation_id with unique branch naming (subtask_1, subtask_2, etc.)\n\n**Architecture Components:**\n\n- **SubtaskQueryExecutor**: Injected function that queries for Task tool invocations\n- **ConversationLinker**: Central component handling all conversation and subtask linking logic\n- **Optimized SQL Queries**: Uses PostgreSQL `@>` containment operator for exact prompt matching\n- **RequestByIdExecutor**: Fetches parent task details for conversation inheritance\n- **GIN Index**: Full JSONB index on response_body for efficient containment queries\n\n**Query Optimization:**\n\nWhen the subtask prompt is known, the system uses an optimized query:\n\n```sql\nresponse_body @> jsonb_build_object(\n 'content', jsonb_build_array(\n jsonb_build_object(\n 'type', 'tool_use',\n 'name', 'Task',\n 'input', jsonb_build_object('prompt', $4::text)\n )\n )\n)\n```\n\nThis leverages the GIN index for O(log n) lookup performance instead of scanning all Task invocations.\n\n**Database Fields:**\n\n- `parent_task_request_id` - Links sub-task requests to their parent task\n- `is_subtask` - Boolean flag indicating if a request is a confirmed sub-task\n- `task_tool_invocation` - JSONB array storing Task tool invocations (for historical queries)\n\n**Sub-task Linking:**\n\n- Sub-tasks are linked by exact matching of user message to Task tool invocation prompts\n- The system creates parent-child relationships between tasks and their sub-tasks\n- Multiple sub-tasks can be spawned from a single parent request\n- Sub-tasks inherit parent task's conversation_id with sequential branch IDs (subtask_1, subtask_2, etc.)\n\n### Dashboard Visualization\n\n**Conversation Tree:**\n\n- Sub-task nodes appear as separate gray boxes to the right of parent nodes\n- Format: \"sub-task N (M)\" where N is the sub-task number and M is the message count\n- Sub-task boxes are clickable and link to their conversation\n- Hover over sub-task boxes to see the task prompt in a tooltip\n\n**Stats Display:**\n\n- \"Total Sub-tasks\" panel shows count of all sub-tasks in a conversation\n- Sub-task indicators on parent nodes show number of spawned tasks\n\n**Visual Design:**\n\n- Sub-task boxes: 100x36px gray boxes with 150px right offset\n- Tooltips: 250x130px with gradient background, appear above nodes on hover\n- Connected to parent nodes with horizontal edges\n\n## Important Implementation Notes\n\n### Conversation Hash Filtering\n\nWhen generating message hashes for conversation tracking, the system filters out:\n\n- Content items that start with `<system-reminder>`\n- This prevents conversation linking from breaking when Claude adds system reminders\n\n### Dashboard Authentication\n\n- Uses `X-Dashboard-Key` header (not Authorization)\n- Cookie-based auth also supported for browser sessions\n\n### AI-Powered Conversation Analysis\n\nThe proxy supports automated analysis of conversations using AI models (currently Gemini 1.5 Flash or 2.5 Pro):\n\n**Features:**\n\n- Background processing of conversations for insights\n- Status tracking (pending, processing, completed, failed)\n- Token usage tracking for cost management\n- Retry logic with exponential backoff\n- Unique analyses per conversation and branch\n- Comprehensive environment variable configuration for prompt tuning\n- Graceful handling of unparseable JSON responses\n- Automatic failure of jobs exceeding max retries\n- Custom prompt support for targeted analysis\n\n**Error Handling:**\n\n- **JSON Parse Failures**: When the AI model returns malformed JSON, the system stores the raw text response instead of failing\n- **Max Retry Exceeded**: Jobs that exceed `AI_ANALYSIS_MAX_RETRIES` are automatically marked as failed with clear error messages\n- **Non-retryable Errors**: Sensitive information detection and API key issues fail immediately without retries\n\n**Database Schema:**\n\n- `conversation_analyses` table stores analysis results\n- ENUM type for status field ensures data integrity\n- Automatic `updated_at` timestamp via trigger\n- Partial index on pending status for efficient queue processing\n- Supports both structured data (`analysis_data`) and raw text (`analysis_content`)\n\n**API Endpoints:**\n\n- `POST /api/analyses` - Create analysis request (supports `customPrompt`)\n- `GET /api/analyses/:conversationId/:branchId` - Get analysis status/result\n- `POST /api/analyses/:conversationId/:branchId/regenerate` - Force regeneration with optional custom prompt\n\n**Utility Scripts:**\n\n- `scripts/check-analysis-jobs.ts` - Check status of analysis jobs\n- `scripts/check-ai-worker-config.ts` - Verify AI worker configuration\n- `scripts/reset-stuck-analysis-jobs.ts` - Reset jobs stuck with high retry counts\n- `scripts/fail-exceeded-retry-jobs.ts` - Manually fail jobs exceeding max retries\n- `scripts/check-analysis-content.ts` - Inspect analysis content for a conversation\n\n**Implementation Status:**\n\n- ✅ Database schema (Migration 011, 012)\n- ✅ API endpoints with custom prompt support\n- ✅ Prompt engineering with actionable feedback\n- ✅ Background worker with resilient error handling\n- ✅ Dashboard UI with analysis panel\n- ✅ Graceful JSON parse failure handling\n- ✅ Automatic max retry failure\n\nSee [ADR-016](docs/04-Architecture/ADRs/adr-016-ai-powered-conversation-analysis.md) for architectural decisions.\n\n**Background Worker Configuration:**\n\nEnable the AI Analysis background worker by setting these environment variables:\n\n```bash\n# Enable the worker\nAI_WORKER_ENABLED=true\n\n# Worker configuration\nAI_WORKER_POLL_INTERVAL_MS=5000 # Poll every 5 seconds\nAI_WORKER_MAX_CONCURRENT_JOBS=3 # Process up to 3 jobs concurrently\nAI_WORKER_JOB_TIMEOUT_MINUTES=5 # Mark jobs as stuck after 5 minutes\n\n# Resilience configuration\nAI_ANALYSIS_MAX_RETRIES=3 # Retry failed jobs up to 3 times\nAI_ANALYSIS_GEMINI_REQUEST_TIMEOUT_MS=60000 # Gemini API request timeout\n\n# Gemini API configuration\nGEMINI_API_KEY=your-api-key-here\nGEMINI_API_URL=https://generativelanguage.googleapis.com/v1beta/models\nGEMINI_MODEL_NAME=gemini-2.0-flash-exp\n\n# Prompt engineering configuration (optional)\nAI_MAX_PROMPT_TOKENS=855000 # Override calculated token limit\nAI_HEAD_MESSAGES=10 # Messages to keep from start\nAI_TAIL_MESSAGES=30 # Messages to keep from end\n\n# Analysis token limits\nAI_ANALYSIS_INPUT_TRUNCATION_TARGET_TOKENS=8192 # Target token count for input message truncation\nAI_ANALYSIS_TRUNCATE_FIRST_N_TOKENS=1000 # Tokens from conversation start\nAI_ANALYSIS_TRUNCATE_LAST_M_TOKENS=4000 # Tokens from conversation end\n```\n\nThe worker runs in-process with the proxy service and uses PostgreSQL row-level locking to safely process jobs across multiple instances.\n\n### Spark Tool Integration\n\nThe dashboard supports the Spark recommendation tool (`mcp__spark__get_recommendation`):\n\n**Features:**\n\n- Automatic detection of Spark tool usage in conversations\n- Display of recommendations in a formatted view\n- Feedback UI for rating and commenting on recommendations\n- Batch fetching of existing feedback\n- Integration with Spark API for feedback submission\n\n**Configuration:**\n\n1. Set `SPARK_API_URL` and `SPARK_API_KEY` environment variables\n2. The dashboard will automatically detect Spark recommendations in tool_result messages\n3. Users can submit feedback directly from the request details page\n4. The proxy logs Spark configuration at startup:\n - When configured: Shows URL and confirms API key is set\n - When not configured: Shows \"SPARK_API_KEY not set\"\n\n**API Endpoints:**\n\n- `POST /api/spark/feedback` - Submit feedback for a recommendation\n- `GET /api/spark/sessions/:sessionId/feedback` - Get feedback for a specific session\n- `POST /api/spark/feedback/batch` - Get feedback for multiple sessions\n\n**Security Note:**\n\nThe dashboard authentication cookie (`dashboard_auth`) is set with `httpOnly: false` to allow JavaScript access for making authenticated API calls from the browser to the proxy service. This is a security trade-off that enables the inline feedback component to work. Consider implementing a more secure approach such as:\n\n- Using a separate API token for browser-based requests\n- Implementing a server-side proxy endpoint in the dashboard\n- Using session-based authentication with CSRF tokens\n\n### SQL Query Optimization\n\n- Always include all required fields in SELECT statements\n- Missing fields like `parent_task_request_id`, `is_subtask`, `task_tool_invocation` will break sub-task tracking\n- Use the SLOW_QUERY_THRESHOLD_MS env var to monitor query performance\n\n### Check Token Usage\n\n```bash\n# Current 5-hour window usage\ncurl \"http://localhost:3000/api/token-usage/current?accountId=acc_f9e1c2d3b4a5&window=300\" \\\n -H \"X-Dashboard-Key: $DASHBOARD_API_KEY\"\n\n# Daily usage (last 30 days)\ncurl \"http://localhost:3000/api/token-usage/daily?accountId=acc_f9e1c2d3b4a5&aggregate=true\" \\\n -H \"X-Dashboard-Key: $DASHBOARD_API_KEY\"\n\n# View conversations\ncurl \"http://localhost:3000/api/conversations?accountId=acc_f9e1c2d3b4a5\" \\\n -H \"X-Dashboard-Key: $DASHBOARD_API_KEY\"\n```\n\n### Copy Conversation Between Databases\n\n```bash\n# Copy a conversation from one database to another\nbun run db:copy-conversation --conversation-id <uuid> --dest-db <url> [options]\n\n# Example: Copy to staging database (same table names)\nbun run db:copy-conversation --conversation-id 123e4567-e89b-12d3-a456-426614174000 \\\n --dest-db \"postgresql://user:pass@staging-host:5432/staging_db\"\n\n# Dry run to preview what would be copied\nbun run db:copy-conversation --conversation-id 123e4567-e89b-12d3-a456-426614174000 \\\n --dest-db \"postgresql://user:pass@staging-host:5432/staging_db\" --dry-run\n\n# Copy with streaming chunks\nbun run db:copy-conversation --conversation-id 123e4567-e89b-12d3-a456-426614174000 \\\n --dest-db \"postgresql://user:pass@staging-host:5432/staging_db\" --include-chunks\n\n# Use custom table names (e.g., from api_requests to api_requests_backup)\nbun run db:copy-conversation --conversation-id 123e4567-e89b-12d3-a456-426614174000 \\\n --dest-db \"postgresql://user:pass@staging-host:5432/staging_db\" \\\n --source-table api_requests --dest-table api_requests_backup\n```\n\n## Maintenance\n\n### Grooming\n\nThe process of `grooming` is used to keep a clean repository. It should be performed regularly and rely on [GROOMING.md](GROOMING.md)\n\n# important-instruction-reminders\nDo what has been asked; nothing more, nothing less.\nNEVER create files unless they're absolutely necessary for achieving your goal.\nALWAYS prefer editing an existing file to creating a new one.\nNEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User.\n\n \n IMPORTANT: this context may or may not be relevant to your tasks. You should not respond to this context unless it is highly relevant to your task.\n</system-reminder>\n","type":"text"},{"text":"Read through the documentation files and extract meaningful/relevant context for adding a logo next to the dashboard title. The logo should be a simple SVG representing a nexus. Focus on:\n1. Dashboard architecture and structure\n2. Frontend components location and styling approach\n3. Build process and asset handling\n4. Any existing UI patterns or conventions\n5. Testing requirements\n\nLimit your response to 10 paragraphs of the most relevant information.","type":"text"}]},{"role":"assistant","content":[{"text":"I'll search through the documentation to find relevant information about the dashboard architecture, frontend structure, and UI patterns for adding a logo to the 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