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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

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Task ID: 46

Title: Implement LLM-based prompt selection service

Status: done

Dependencies: 45 ✓

Priority: high

Description: Create a service that uses the heavy LLM to intelligently select relevant prompts based on tags and the full prompt index, understanding synonyms and context.

Details:

Create /src/mcplocal/src/services/llm-prompt-selector.service.ts:

export class LlmPromptSelectorService {
  constructor(
    private llmClient: LlmClient,
    private fastLlmClient: LlmClient | null,
    private tagMatcher: TagMatcherService  // fallback
  ) {}

  async selectPrompts(tags: string[], promptIndex: PromptIndex[]): Promise<{
    selected: Array<{ name: string; reason: string }>;
    priority10: PromptIndex[];  // Always included
  }> {
    // 1. Extract priority 10 prompts (always included)
    // 2. Generate missing summaries using fast LLM if needed
    // 3. Send to heavy LLM:
    const prompt = `
      Given these keywords: ${tags.join(', ')}
      And this prompt index:
      ${promptIndex.map(p => `- ${p.name}: ${p.summary}`).join('\n')}

      Select the most relevant prompts for someone working on tasks
      related to these keywords. Consider synonyms and related concepts.
      Return a ranked JSON array: [{name: string, reason: string}]
    `;
    // 4. Parse LLM response
    // 5. On LLM error, fall back to tag matcher
  }
}

Handle LLM timeouts and errors gracefully with fallback
Validate LLM response format

Test Strategy:

Unit test: Priority 10 prompts always returned regardless of LLM selection
Unit test: LLM called with correct prompt format (mock)
Unit test: LLM response parsed correctly
Unit test: Invalid LLM response falls back to tag matcher
Unit test: LLM timeout falls back to tag matcher
Unit test: Missing summaries trigger fast LLM generation
Unit test: No LLM available uses tag matcher directly
Integration test: End-to-end selection with mock LLM

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Task ID: 46

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