SKILLEMALL.ai

AC data-privacy-law-explainer

Explain U.S. state-by-state consumer data-privacy law (CCPA/CPRA, TDPSA, VCDPA, CPA, and the other comprehensive state acts) — who a law covers, applicability thresholds, privacy-policy requirements, consumer rights and opt-outs, private rights of action, and who enforces. Reads a bundled, source-cited snapshot per state. Use when the user says "CCPA," "CPRA," "state privacy law," "privacy policy," "data subject request," "consumer rights request," "opt-out of sale," "data broker," "sensitive data," asks "do I need to comply with <state>'s privacy law," or names a U.S. state together with privacy.

ClawHub Agent Skills author: Steven Obiajulu v0.3.0 MIT-0 55 files body ≈ 1 156 tokens Open the sourceclawhub.ai analyzed 19 h ago

Explain U.S. state-by-state consumer data-privacy law (CCPA/CPRA, TDPSA, VCDPA, CPA, and the other comprehensive state acts) — who a law covers, applicability…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureLegaltype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
84
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Risky intent intent-offensive-security content/north-dakota.md:75
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      The chapter is built on the model of the federal GLBA Safeguards Rule, which likewise requires designating a qualified individual to oversee, implement, and enforce the information security program [^
    • low Risky intent intent-offensive-security content/north-dakota.md:145
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      [^stat…ing]: **N.D. Cent. Code § 13-01.2-03(6)** — "Information systems monitoring and testing must include continuous monitoring or periodic penetration testing, and vulnerability assessm
      detector

    Files scanned: 55. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "catalog_group"
    • note frontmatter-key unknown frontmatter key "catalog_order"

    Process rating: all ten parameters 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1156 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 604: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 23 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is an offline legal-information skill with state privacy-law notes and no executable code, credential handling, persistence, or hidden data flow.
    LLM: benign (high) · VirusTotal: · 13 Jun 2026