SKILLEMALL.ai

BC ai-claims-assessment

Public-document assessment for healthcare-AI vendors. Reads only a company's public product pages, Terms of Service, and Privacy Policy, then finds where its stated use of AI on health data fails to reconcile across three sources — market claims, legal language, and HIPAA requirements. Produces a map of gaps, each cited at both ends, framed as a public-documentation gap a covered entity would hit during vendor review. Self-contained: the regulatory text it checks against is included below.

ClawHub Claude Code author: Dangsllc v1.0.1 MIT-0 2 files body ≈ 8 183 tokens Open the sourceclawhub.ai analyzed 2 d ago

Public-document assessment for healthcare-AI vendors.

As a process C 64/100 · Has gaps — weak spots: failures and branches, execution cost, running it twice

AnalyzerLegalData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
64/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Public-document assessment for healthcare-AI vendors. Reads only a… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning body-long SKILL.md body ≈ 8183 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 64/100

  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 12 mutating operations with no state check
  • 40Execution cost. Instruction body is 8183 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 32 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 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
  • low 13 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 494: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 32 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill is a read-only healthcare compliance review aid that analyzes user-provided public documents and does not request execution, network access, persistence, or sensitive local access.
LLM: benign (high) · VirusTotal: · 20 Jul 2026