SKILLEMALL.ai

AB medical-appointment-advocate

Prepare to get the most out of a medical appointment — for yourself or someone you care for — with the right questions, the information to bring, and how to make sure you're heard. Use when asked help me prepare for a doctor's appointment, questions to ask the doctor, advocate for my parent at the doctor, or how do I get the most from this appointment. Produces a focused list of what to raise and ask (prioritized, since time is short), the history and info to bring, note-taking and 'teach-back' tactics so you actually understand, how to speak up if dismissed, and what to confirm before leaving — not medical advice, but better navigation of care.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 1 094 tokens Open the sourcegithub.com analyzed 2 d ago

Prepare to get the most out of a medical appointment — for yourself or someone you care for — with the right questions, the information to bring, and how to…

As a process B 72/100 · Nearly there — weak spots: when it triggers, running it twice, progress reporting

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
72/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: medical-appointment-advocate (mohitagw15856/pm-claude-skills)

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: 1. 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 72/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1094 tokens

    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 653: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 33 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

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