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Clinical Research AI Safety Boundary

Review clinical research AI work with evidence-first boundaries so agents do not invent medical sources, expose private data, or turn research notes into patient-specific advice.

难度:intermediate 分类:research 来源:Clinical AI Agent Skills README

完整 Prompt(可直接复制)

/goal
GOAL:
Complete Clinical Research AI Safety Boundary for a research task: Review clinical research AI work with evidence-first boundaries so agents do not invent medical sources, expose private data, or turn research notes into patient-specific advice.

CONTEXT:
- Before editing, read the nearest AGENTS.md/CLAUDE.md, current issue or PLAN.md, and any failing logs already in the repo.
- Inspect source lists, citation notes, evidence files, and acceptance criteria.
- Establish a baseline by running or locating evidence for: `manual review checklist for source facts, uncertainty, safety note, inspected files, and human-review needs`.

CONSTRAINTS:
- Keep the scope limited to this goal; do not expand into unrelated cleanup.
- Do not weaken tests, delete assertions, or mask errors to make verification pass.
- Respect the repository's AGENTS.md/CLAUDE.md instructions and existing patterns.
- Do not present unsourced claims as facts.
- Keep direct quotes short and attach a public URL for every external claim.

DONE WHEN:
- The implementation or documentation directly satisfies: Review clinical research AI work with evidence-first boundaries so agents do not invent medical sources, expose private data, or turn research notes into patient-specific advice.
- The verification command or evidence path succeeds: `manual review checklist for source facts, uncertainty, safety note, inspected files, and human-review needs`.
- The final diff is scoped to the relevant files and has no unrelated formatting churn.

VERIFY:
- Run `manual review checklist for source facts, uncertainty, safety note, inspected files, and human-review needs` or the closest repo-local equivalent if the exact command is not available.
- Capture before/after evidence for the behavior, metric, report, or artifact involved.
- If verification cannot run locally, stop and report the missing dependency instead of guessing success.

OUTPUT:
- Summarize changed files, key decisions, verification output, and remaining risks.
- Include any follow-up that is required for production rollout or human review.

STOP RULES:
- Pause if secrets, production access, stakeholder decisions, or destructive data operations are required.
- Pause after three failed fix attempts on the same symptom and challenge the root-cause hypothesis.
- Do not mark the goal complete until the current repository state has been audited against DONE WHEN.

来源与证据

原始来源: Clinical AI Agent Skills README

证据摘要: Evidence Before Confidence; source: Clinical AI Agent Skills README; type: tool-readme; verification: manual review checklist for source facts, uncertainty, safety note, inspected files, and human-review needs