SKILLEMALL.ai

AB preflight-client-endpoint-before-integration

Verifies a client’s newly supplied public FHIR endpoint’s declared conformance surface before integration work begins. Use when a client gives a public FHIR base URL or metadata URL and asks what the named server declares, whether its metadata is valid, whether US Core resource types or SMART discovery fields are present, why authorization endpoints cannot be discovered, or whether the endpoint is in good shape before onboarding. Not for validating an individual FHIR resource against its declared profile.

ClawHub Agent Skills author: PowMCP v1.0.0 MIT-0 4 files body ≈ 3 259 tokens Open the sourceclawhub.ai analyzed 3 d ago

Verifies a client’s newly supplied public FHIR endpoint’s declared conformance surface before integration work begins.

As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions

IntegrationData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
40
When it triggers w 12
50
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: 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 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 39 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3259 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 510: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 39 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This is a narrow, disclosed FHIR endpoint preflight helper, with the main cautions being its PowMCP connection and unpinned setup command.
    LLM: benign (high) · VirusTotal: · 10 Sept 2026