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AC soc2-evidence-collector

Generate SOC2 evidence collection checklists, automate evidence gathering scripts, and produce audit-ready evidence packages. Covers all 5 Trust Service Criteria (Security, Availability, Processing Integrity, Confidentiality, Privacy). Use when preparing for SOC2 Type I/II audits, maintaining continuous compliance, or building evidence collection automation. Built by AfrexAI.

ClawHub Agent Skills author: Shark1973 v1.0.0 MIT-0 4 files body ≈ 3 276 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: when it triggers, consistency, running it twice

GeneratorInfrastructureSecuritytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
87
Run on models
none yet
Process rating
C
62/100
Has gaps
When it triggers w 12
20
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: soc2-evidence-collector (ClawHub)

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Risky intent intent-offensive-security SKILL.md:71
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Penetration test reports | Security vendor | PDF reports with remediation tracking |

    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 62/100

    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (soc2-evidence-collector) differs from the folder (afrexai-soc2-evidence-collector-skip)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 29 steps
    • 100Execution cost. Instruction body is 3276 tokens
    • 100Progress reporting. Reports progress

    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 378: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 29 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)

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

    External checks

    ClawHub: clean
    This SOC2 audit helper is coherent and purpose-aligned, but it can help generate scripts that collect sensitive cloud, GitHub, and identity evidence.
    LLM: benign (high) · VirusTotal: · 29 May 2026