version: "1.0.0" 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

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_classify call 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

1. Resolve the image to an absolute path. The MCP tool runs in a different working directory than the agent. If image_path is not absolute, resolve it (e.g. via realpath) before calling the tool. If you can't resolve it, ask the user.

1. Get scores from MI2.

• Read the canonical label list from `references/labels.md` and use those strings verbatim.
• If the caller provided extra_labels, append them.
• Call mcp_medimageinsig_zeroshot_classify with file_path = the absolute path from step 1 and labels = the assembled list.
• Bucket the returned scores using the cutoffs below.

1. Hand off to `write-report-simple`. Invoke the write-report-simple skill (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.

1. Return what `write-report-simple` returns. 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-simple as 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.