Run ff2241bc-7cef-4327-a983-45a075457b58

Raw output

{"duration_api_ms":31985,"stop_reason":"end_turn","session_id":"29e2cbdf-f4fa-43c7-ad77-9e642af2b186","total_cost_usd":0.7303820000000001,"usage":{"input_tokens":8,"cache_creation_input_tokens":59241,"cache_read_input_tokens":153762,"output_tokens":2364,"output_tokens_details":{"thinking_tokens":540},"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":59241,"ephemeral_5m_input_tokens":0},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":1500,"cache_read_input_tokens":53345,"cache_creation_input_tokens":5896,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":5896},"type":"message"}],"speed":"standard"},"modelUsage":{"claude-haiku-4-5-20251001":{"inputTokens":1881,"outputTokens":14,"cacheReadInputTokens":0,"cacheCreationInputTokens":0,"webSearchRequests":0,"costUSD":0.001951,"contextWindow":200000,"maxOutputTokens":32000,"thinkingTokens":0,"canonicalModel":"claude-haiku-4-5","provider":"firstParty","costBasis":"list"},"claude-opus-5[1m]":{"inputTokens":8,"outputTokens":2364,"cacheReadInputTokens":153762,"cacheCreationInputTokens":59241,"webSearchRequests":0,"costUSD":0.7284310000000002,"contextWindow":1000000,"maxOutputTokens":64000,"thinkingTokens":540,"canonicalModel":"claude-opus-5","provider":"firstParty","costBasis":"list"}},"permission_denials":[],"terminal_reason":"completed","fast_mode_state":"off","fast_mode_disabled_reason":"sdk_opt_in_required","subagent_stats":{"spawned":0,"requested":{"background":0,"foreground":0,"unset":0},"started_in_background":0,"max_depth":0,"spawned_by_subagents":0,"completed":0,"failed":0,"killed":{"parent":0,"user":0,"system":0},"refused":{"depth_limit":0,"concurrency_limit":0,"budget":0},"by_type":{}},"is_error":false,"num_turns":7,"subtype":"success","api_error_status":null,"result":"{\"current_state_summary\": \"The core RAG stack is complete and substantial: tier-aware retrieval (embed + vectorstore + bm25 + rerank), the full anti-hallucination guardrail chain (grounding, hallucination, citation, confidence, doctrinal, self-refusal, tier-sufficiency), an answer pipeline, an eval harness with journaled runs, Alembic migrations, and a FastAPI service exposing /v1/answer plus health/stats/version. A CLI exists at packages/core/src/lds_rag_core/cli.py. No MCP wrapper exists anywhere in the repo.\", \"gap_analysis\": \"Two verifiable code gaps remain against the definition of done. (1) The MCP wrapper is entirely absent — no module, no tool definitions, no entry point, no packaging metadata (already the existing task). (2) 'Tested' is not met at the transport/plumbing layer: packages/api/tests has no test for the /v1/answer route at all (only health, stats, version), and the core plumbing modules (cli, eval, chat, prompts, answer_pipeline, ingest, index_pipeline, embed, rerank, retrieval, vectorstore, bm25) carry little or no unit coverage, holding the suite at roughly half the project's 80% gate. The accuracy substrate itself is well covered and needs no further work.\", \"completion_percent\": 80, \"estimated_hours_remaining\": 14, \"confidence\": \"medium\", \"tasks_to_mark_complete\": [], \"proposed_tasks\": [{\"title\": \"Cover the /v1/answer route and the retrieval/generation plumbing with unit tests\", \"description\": \"The guardrail and scoring modules are well tested, but the transport and plumbing layers are not. packages/api/tests contains no test for the /v1/answer endpoint, so request validation, pipeline caching, the 503 pipeline-unavailable path, and the Answer response shape are unverified. In core, the modules that move data (retrieval, vectorstore, bm25, rerank, embed, answer_pipeline, prompts, chat) have little or no coverage, which is what holds the suite below the project's 80% gate. Add focused unit tests with the external backends (Postgres, Qdrant, the model server) mocked at their client boundaries — these are external dependencies, not our own code.\", \"estimated_minutes\": 480, \"subtasks\": [{\"title\": \"Test /v1/answer: request-model validation bounds, happy path against a stubbed pipeline, and the 503 when _build_pipeline raises\", \"estimated_minutes\": 120}, {\"title\": \"Test get_pipeline lazy-init/caching and _build_pipeline's env-driven reranker and GROUNDING_THRESHOLD wiring\", \"estimated_minutes\": 60}, {\"title\": \"Test AnswerPipeline orchestration end-to-end with a fake retriever and fake chat client, including the guardrail-refusal path\", \"estimated_minutes\": 120}, {\"title\": \"Test Retriever tier/source_class filtering and hybrid merge, plus bm25 and rerank ordering, against fixture hits\", \"estimated_minutes\": 120}, {\"title\": \"Test prompts.assemble_user_prompt and the chat client's request construction and error handling\", \"estimated_minutes\": 60}]}]}","ttft_ms":1234,"type":"result","duration_ms":32028,"uuid":"a7e25472-cd0a-460f-9db7-5c5da228796f","ttft_stream_ms":896,"time_to_request_ms":50,"first_content_frame_ms":896,"queued_turn_count":0,"result_index":0}

Parsed result

{
  "confidence": "medium",
  "operational": {
    "kind": "none",
    "drift": "n/a",
    "score": null,
    "checks": [],
    "status": "not_applicable",
    "latest_tag": null,
    "deployed_version": null
  },
  "gap_analysis": "Two verifiable code gaps remain against the definition of done. (1) The MCP wrapper is entirely absent — no module, no tool definitions, no entry point, no packaging metadata (already the existing task). (2) 'Tested' is not met at the transport/plumbing layer: packages/api/tests has no test for the /v1/answer route at all (only health, stats, version), and the core plumbing modules (cli, eval, chat, prompts, answer_pipeline, ingest, index_pipeline, embed, rerank, retrieval, vectorstore, bm25) carry little or no unit coverage, holding the suite at roughly half the project's 80% gate. The accuracy substrate itself is well covered and needs no further work.",
  "proposed_tasks": [
    {
      "title": "Cover the /v1/answer route and the retrieval/generation plumbing with unit tests",
      "subtasks": [
        {
          "title": "Test /v1/answer: request-model validation bounds, happy path against a stubbed pipeline, and the 503 when _build_pipeline raises",
          "estimated_minutes": 120
        },
        {
          "title": "Test get_pipeline lazy-init/caching and _build_pipeline's env-driven reranker and GROUNDING_THRESHOLD wiring",
          "estimated_minutes": 60
        },
        {
          "title": "Test AnswerPipeline orchestration end-to-end with a fake retriever and fake chat client, including the guardrail-refusal path",
          "estimated_minutes": 120
        },
        {
          "title": "Test Retriever tier/source_class filtering and hybrid merge, plus bm25 and rerank ordering, against fixture hits",
          "estimated_minutes": 120
        },
        {
          "title": "Test prompts.assemble_user_prompt and the chat client's request construction and error handling",
          "estimated_minutes": 60
        }
      ],
      "description": "The guardrail and scoring modules are well tested, but the transport and plumbing layers are not. packages/api/tests contains no test for the /v1/answer endpoint, so request validation, pipeline caching, the 503 pipeline-unavailable path, and the Answer response shape are unverified. In core, the modules that move data (retrieval, vectorstore, bm25, rerank, embed, answer_pipeline, prompts, chat) have little or no coverage, which is what holds the suite below the project's 80% gate. Add focused unit tests with the external backends (Postgres, Qdrant, the model server) mocked at their client boundaries — these are external dependencies, not our own code.",
      "estimated_minutes": 480
    }
  ],
  "completion_percent": 80,
  "current_state_summary": "The core RAG stack is complete and substantial: tier-aware retrieval (embed + vectorstore + bm25 + rerank), the full anti-hallucination guardrail chain (grounding, hallucination, citation, confidence, doctrinal, self-refusal, tier-sufficiency), an answer pipeline, an eval harness with journaled runs, Alembic migrations, and a FastAPI service exposing /v1/answer plus health/stats/version. A CLI exists at packages/core/src/lds_rag_core/cli.py. No MCP wrapper exists anywhere in the repo.",
  "tasks_to_mark_complete": [],
  "estimated_hours_remaining": 14
}