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CC algorithm-filing

AI large model / algorithm regulatory filing assistant for China's CAC requirements. Helps determine filing type, prepare required materials, generate security assessment report frameworks, guide system submission, and manage post-filing compliance. Triggered by: 算法备案, 大模型备案, 深度合成备案, 生成式AI备案, 安全评估报告, 算法合规, beian.cac

ClawHub Claude Code author: bettermen v1.0.0 MIT-0 9 files body ≈ 1 082 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

AI large model / algorithm regulatory filing assistant for China's CAC requirements.

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticsSecurityLegaltype 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
C
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
74
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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/security-assessment-framework.md:132
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - 红队测试（Red Teaming）过程

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1082 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 317: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (4 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a coherent regulatory-filing guidance skill with no executable code or hidden data-handling behavior found.
LLM: benign (high) · VirusTotal: · 10 Jul 2026