SKILLEMALL.ai

BC ai-governance-reviewer-carl-ditzler

Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 16 files body ≈ 4 375 tokens Open the sourcegithub.com↗ analyzed 70 min ago

Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI…

As a process C 62/100 · Has gaps — References files that are not bundled: references/official/, references/working/*.md, references/official/*.pdf

AnalyzerWriting and documentsSecurityAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
99
Quality 40%
76
Run on models
none yet
Process rating
C
62/100
Has gaps
References files that are not bundled: references/official/, references/working/*.md, references/official/*.pdf
Tools and files w 18
0
Progress reporting w 2
0
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 Risky intent intent-offensive-security references/working/EU GPAI Code_of_Practice_for_GeneralPurpose_AI_Models_Safety_and_Security_Chapter.md:1977
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    (3) validation of network software integrity, through (a) competitive bug bounty programs to

Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/official/
  • warning missing-ref reference to a missing file: references/working/*.md
  • warning missing-ref reference to a missing file: references/official/*.pdf

Process rating: all ten parameters 62/100

Will not run. References files that are not bundled: references/official/, references/working/*.md, references/official/*.pdf
  • 0Tools and files. 3 referenced file(s) missing: references/official/, references/working/*.md, references/official/*.pdf
  • 0Progress reporting. Says nothing while it works
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 10 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 4375 tokens
  • 100Steps. 184 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 6 branches, has a failure section
  • 100Consistency. Name and required fields are in place

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)
  • +4No input/output examples
  • +2Single-language instructions
  • +3Description length 572: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 184 items
  • +3Output format is stated explicitly
  • +4Reference files are cited in the instructions (7 of 7)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.