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BD cc-soul

Zero-vector AI memory engine with self-learning. LOCOMO 76.2% (4th place). 15 original algorithms, open source (MIT).

ClawHub Agent Skills author: wenroudeyu-collab v3.2.5 MIT-0 80 files body ≈ 1 947 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubAI and agentstype 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
B
84/100
safety, quality, tests
Safety 60%
98
Quality 40%
62
Run on models
none yet
Process rating
D
49/100
Unfinished process
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

  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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration exfil-secret-in-url cc-soul/benchmark-locomo.js:682
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
    const resp = useGemini ? await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=… {
    placeholder
  • low Exfiltration net-credential-use cc-soul/benchmark-locomo.js:682
    Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)
    const resp = useGemini ? await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=… {
    known service

Files scanned: 80. 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 "slug"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 49/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Failures and branches. 2 branches
  • 100Steps. 39 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1947 tokens
  • low The skill ranks results itself: that belongs to the system behind the tool, not the model

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)
  • +3Description length 117: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
This is a real memory engine, but it exposes and processes sensitive personal memory too broadly for the way it is described.
LLM: suspicious (high) · VirusTotal: · 29 May 2026