BF health-report-reader
AI-driven health checkup report interpreter. Input report images, indicator values, or natural language descriptions to generate interactive HTML visualization reports with comprehensive indicator interpretation, risk assessment, and personalized health recommendations. Triggers: 体检报告, 体检报告解读, 帮我看看体检, 检查报告分析, 化验单解读, 体检结果, 报告解读, health checkup, 看不懂报告, 指标解读.
AI-driven health checkup report interpreter.
As a process F 35/100 · Will not run — References files that are not bundled: references/indicators.md, references/template.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: references/indicators.md - warning
missing-refreference to a missing file: references/template.md - note
frontmatter-keyunknown frontmatter key "description_zh"
Process rating: all ten parameters 35/100
- 0Tools and files. 2 referenced file(s) missing: references/indicators.md, references/template.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 778 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 358: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.