Files
mcpctl/.taskmaster/tasks/task_049.md
Michal a869f77070 merge: AgentProject membership — the junction is now load-bearing
Merges feat/agent-project-membership (task 166/152). An agent can finally join
many projects: membership routes, per-membership role and optional brain
override, chat resolving context from the membership, and CLI attach-agent /
detach-agent / get memberships. The legacy Agent.projectId fallback is kept for
this release as the schema comment promises.

Conflict resolved in main.ts: that branch added its RBAC case to
mapUrlToPermission inline, while this branch had extracted the function to
middleware/url-permission.ts so it could be tested. Kept the extraction and
ported the case into it — joining a team is `edit:agents:<name>`, not
`create:agents`, which is the authority to mint a whole agent.

Also fixes something the extraction makes possible. security.test.ts contained a
hand-copied reproduction of mapUrlToPermission, because main.ts self-invokes
main() and nothing in it was importable. A security test asserting against a
copy stops testing the system the moment the real one changes, and this copy had
already drifted. It now imports the real function; all 18 assertions still pass,
against the code that actually runs.

Local: build clean, workspace 2550 passed, lint unchanged at 794 errors.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01N4wNHWf7xSwnZCWpJcyv9p
2026-08-09 23:34:18 +01:00

1.8 KiB

Task ID: 49

Title: Implement read_prompts tool for ongoing retrieval

Status: done

Dependencies: 48 ✓

Priority: high

Description: Create the read_prompts MCP tool that allows clients to request additional context by keywords after the session is ungated.

Details:

  1. Add read_prompts tool definition:

    private getReadPromptsTool(): Tool {
      return {
        name: 'read_prompts',
        description: 'Request additional project context by keywords. Use this whenever you need guidelines, policies, or conventions related to your current work.',
        inputSchema: {
          type: 'object',
          properties: {
            tags: {
              type: 'array',
              items: { type: 'string' },
              description: 'Keywords describing what context you need'
            }
          },
          required: ['tags']
        }
      };
    }
    
  2. Implement read_prompts handler:

    • Always use keyword matching (not LLM) for precision
    • Exclude already-retrieved prompts from response
    • Add newly retrieved prompts to session state
    • Include reminder about more prompts available
  3. Response format:

    [Matched prompt content - deduplicated]
    
    Remember: you can request more prompts at any time with read_prompts({ tags: [...] }).
    The project may have additional guidelines relevant to your current approach.
    

Test Strategy:

  • Unit test: read_prompts returns matched prompts by keyword
  • Unit test: Already retrieved prompts excluded from response
  • Unit test: Newly retrieved prompts added to session state
  • Unit test: Response includes reminder text
  • Unit test: read_prompts while gated returns error
  • Unit test: Empty tags returns empty response
  • Unit test: Uses keyword matching not LLM