SKILLEMALL.ai

AC concussion-return-to-play-protocol

Use this skill when a team physician, athletic trainer, or sports clinician needs to draft a graduated Return-to-Sport and Return-to-Learn plan for a concussed athlete. Aligned to CISG 2023 and SCAT6; produces a DRAFT 6-step RTS / 4-step RTL plan with stage minimums and regression rules for qualified-HCP review — never clears an athlete to play.

ClawHub Agent Skills author: devasher v0.1.1 MIT-0 4 files body ≈ 4 172 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
87
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token CHANGELOG.md:9
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      Initial release. Drafts an individualized graduated Return-to-Sport (RTS) and parallel Return-to-Learn (RTL) staged plan for a concussed athlete aligned to the CISG 2023 Amsterdam consensus and SCAT6,
      detector

    Files scanned: 4. 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 64/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 5 branches
    • 70Execution cost. Instruction body is 4172 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 76 steps
    • 100Consistency. Name and required fields are in place
    • 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 347: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 76 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

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

    External checks

    ClawHub: clean
    This is a markdown-only concussion return-to-play drafting aid with clear clinician-review limits and no hidden code or data-access behavior.
    LLM: benign (high) · VirusTotal: · 28 May 2026