| name | inlab-human-bundle |
| description | Freeze a review_bundle.json for an in-lab reading session: sample de-identified cases, score each via the endpoint-predict tool (live endpoint, deterministic), add narrator-agent explanations, validate schema invariants, freeze. v0.1 source mode: the Endpoint_Set package's own examples/. Called by /inlab-human orchestrator; also directly. Trigger: build bundle, freeze bundle, review bundle, /inlab-human-bundle. |
| argument-hint | <endpoint_path> [--endpoint-url URL] [--bundle-id ID] [--out PATH] |
| allowed-tools | Bash, Read, Write, Grep, Glob, Agent |
| metadata | {"version":"0.1.0","last_updated":"2026-07-10","summary":"Builder: cases -> endpoint scores -> narratives -> frozen review_bundle.json."} |
Skill: inlab-human-bundle
Produces the single artifact a reading session consumes. Deterministic parts
(sampling, scoring, de-id shaping, validation) run in scripts/build_bundle.py;
the ONLY LLM-produced field is model_output.narrative, merged afterwards.
Procedure
1. Locate the endpoint.
- live URL given -> use it. else: is a local server up? (predict_cli.py ping)
- if not, offer to start one (the study project's serve_endpoint task, or
/haipipe-end-deploy-local) and wait for /ping healthy.
2. Deterministic build (Bash):
python3 scripts/build_bundle.py \
--endpoint-path <Endpoint_Set dir> --endpoint-url <URL> \
--bundle-id <id> --out <study>/bundles/review_bundle_<id>.json \
--task-description "<what the model predicts, clinician-facing>" \
--horizon "<prediction horizon>"
The script POSTs every case through the SAME code path as the
endpoint-predict MCP tool, writes the bundle + a .build_log.json
(case_id ↔ raw score audit trail), and validates the schema invariants.
A validation error is a HARD STOP — fix, rebuild; never hand-edit a bundle.
3. Narratives — dispatch the narrator agent (agents/inlab-narrator-agent.md),
one call per case or batched. Input per case: presentation + model_output
(score, band, shap_top if any). The agent NEVER sees gold. Write
{case_id: {narrative, agent}} to narratives.json, then:
python3 scripts/build_bundle.py --merge-narratives narratives.json --out <bundle>
No SHAP from the endpoint? The narrative may DESCRIBE the case alongside the
score but must not claim feature attributions the model didn't provide.
4. Freeze: report bundle path, n cases, strata table, validation status.
A frozen bundle is immutable — changes mean a new --bundle-id.
Output contract: ../../ref/review-bundle-schema.md (v0.1).
Return contract
status: ok | blocked | failed
summary: bundle id, n cases, strata counts, narrative coverage
artifacts: [review_bundle_<id>.json, .build_log.json]
next: /inlab-human review <bundle path>
