write-report-zeroshot
Write a chest X-ray report grounded in MedImageInsight (MI2) zero-shot classifier scores. Invoke whenever drafting a CXR report when MI2 is available — get vision-grounded per-finding probabilities, then delegate the prose to `write-report-simple`.
- License 许可
- MIT
- 最近更新
- 2026-09-02
- Stars
- ★ 6
- Forks
- 0
01 前言 Front Matter
- name
- write-report-zeroshot
- description
- Write a chest X-ray report grounded in MedImageInsight (MI2) zero-shot classifier scores. Invoke whenever drafting a CXR report when MI2 is available — get vision-grounded per-finding probabilities, then delegate the prose to `write-report-simple`.
- argument-hint
- - image_path: required path to the CXR image (PNG or JPEG) - extra_labels: optional list of additional MI2-format label strings to score alongside the default set
02 资源文件 10
- 参考文档references/architecture-design.md4.6 KB
- 参考文档references/azure-service-mappings.md606 B
- 参考文档references/best-practices.md1.6 KB
- 参考文档references/deployment-operational.md3.2 KB
- 参考文档references/event-driven.md715 B
- 参考文档references/labels.md767 B
- 参考文档references/messaging-integration.md4.5 KB
- 参考文档references/performance.md6.6 KB
- 参考文档references/reliability-resilience.md6.2 KB
- 参考文档references/security.md1.8 KB
03 SKILL.md 正文
write-report-zeroshot
Two-step skill: (1) call MI2 to get per-finding probabilities for the image, then (2) hand those off to the existing write-report-simple skill to produce the actual report. The report itself never mentions MI2 — it reads as the radiologist's direct read of the image.
Budget
- Tool calls: 1 — exactly one
mcp_medimageinsig_zeroshot_classifycall per image. - Output: ≤ 200 words for the full report.
- Do not re-invoke skills already used in this turn.
- Do not retry tool calls on success.
How to use
-
Resolve the image to an absolute path. The MCP tool runs in a different working directory than the agent. If
image_pathis not absolute, resolve it (e.g. viarealpath) before calling the tool. If you can't resolve it, ask the user. -
Get scores from MI2.
- Read the canonical label list from
references/labels.mdand use those strings verbatim. - If the caller provided
extra_labels, append them. - Call
mcp_medimageinsig_zeroshot_classifywithfile_path= the absolute path from step 1 andlabels= the assembled list. - Bucket the returned scores using the cutoffs below.
- Read the canonical label list from
-
Hand off to
write-report-simple. Invoke thewrite-report-simpleskill (already in the workspace skill drawer at.github/skills/write-report-simple/). Pass:findings: the bucketed list (positives + possibles), using the original MI2 label names.scores: the raw per-finding probabilities (so the report skill can calibrate hedging).
The downstream skill derives confidence from
scores. -
Return what
write-report-simplereturns. Do not re-wrap, re-format, or annotate the report. The downstream skill emits the<confidence>and<report>blocks; pass them through unchanged.
Score buckets
Probabilities sum to ~1.0 across the label set. With the default label list, use these cutoffs:
- ≥ 0.20 → positive finding (pass to
write-report-simpleas a confident finding). - 0.08 – 0.20 → possible finding (pass through; the report skill hedges accordingly).
- < 0.08 → absent (omit from
findings).
Critical rule
The report must not mention MI2, zero-shot scores, or any model output. That's the responsibility of write-report-simple (which has the rule baked in), but it's worth restating here: this skill exists to ground the report in vision-model evidence, not to surface that evidence in the prose. If you want to attribute or caveat the model in the chat reply outside the <report> tags, that's fine.
04 同仓库更多 Skills
write-report-with-ehr
Write a context-aware chest X-ray report grounded in the trained MedImageInsight (MI2) adapter AND the patient's EHR record. Adds a COMPARISON section and uses the most recent prior report to call out interval change.
lookup-patient-history
Load a synthetic patient EHR record (demographics, HPI, problems, meds, devices, prior imaging studies and reports) for a given chest X-ray. Invoke as the first step of any context-aware reporting flow that needs patient history. No model calls.
write-report-zeroshot
Write a chest X-ray report grounded in MedImageInsight (MI2) zero-shot classifier scores. Invoke whenever drafting a CXR report when MI2 is available — get vision-grounded per-finding probabilities, then delegate the prose to `write-report-simple`.
write-report-adapter
Write a chest X-ray report grounded in the trained MedImageInsight (MI2) adapter. Invoke whenever drafting a CXR report when the adapter is available — get vision-grounded per-finding positive/possible/negative calls, then delegate the prose to `write-report-simple`.
write-report-adapter
Write a chest X-ray report grounded in the trained MedImageInsight (MI2) adapter. Invoke whenever drafting a CXR report when the adapter is available — get vision-grounded per-finding positive/possible/negative calls, then delegate the prose to `write-report-simple`.
write-report-simple
TODO