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AC wisediag-checkup

Medical Checkup Report Analysis — Upload a PDF checkup report (via URL or local file binary upload) for AI-powered health interpretation with abnormal item detection, clinical explanations, lifestyle assessment, and personalized recommendations. Supports health questionnaires for tailored analysis. Triggered when the user asks to analyze a checkup report and provides a PDF URL or local file path. Can also be invoked explicitly: say 'Use WiseAnalyze to analyze this checkup report'.

ClawHub Agent Skills author: wisediag v1.0.1 MIT-0 5 files body ≈ 2 064 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    For the model run — optional
    • 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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Dangerous commands cmd-shell-rc README.md:61
      Writes to a shell startup file
      echo 'export WISEDIAG_API_KEY=your_api_key_here' >> ~/.zshrc

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "registry"
    • note frontmatter-key unknown frontmatter key "env_vars"
    • note frontmatter-key unknown frontmatter key "credentials"

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (wisediag-checkup) differs from the folder (wiseanalyze)
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 30 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 2064 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +3Output format is not stated: the model decides each time
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 485: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 30 items
    • +4Has examples (10 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill openly sends user-selected checkup reports to WiseDiag for cloud analysis and saves the resulting report locally, with the main risk being sensitive health data handling rather than hidden or malicious behavior.
    LLM: benign (high) · 28 May 2026