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AC share-health-qr

Generate a patient-controlled SMART Health Link (SHL) QR code for sharing health records with a clinic or provider. Use when: (1) A patient asks to share their records via QR for clinic check-in, (2) A patient asks to generate a health QR code, (3) A patient asks to "share my records" or "generate a QR with my records". Covers the full consent → fhir_get_token → shl_generate → QR render + manage-link delivery loop. Never direct-encodes PHI into a QR image — the QR encodes only the encrypted shlink:/ pointer.

ClawHub Agent Skills author: Eugene Vestel v1.6.0 MIT-0 2 files body ≈ 2 213 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Generate a patient-controlled SMART Health Link (SHL) QR code for sharing health records with a clinic or provider.

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmenttype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2213 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 513: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is a clearly scoped health-record QR sharing workflow with strong consent and privacy guardrails, and no executable install behavior in the artifact.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026