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BC OpenClawdy

Give your agent persistent memory that survives sessions. Store facts, preferences, decisions, and learnings - recall them semantically whenever needed. Advanced features include reputation trackin...

modbender/skill-library-mcp Agent Skills author: modbender MIT 44 files body ≈ 3 171 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Give your agent persistent memory that survives sessions.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureAI 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%
92
Quality 40%
72
Run on models
none yet
Process rating
C
52/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Secrets in code secret-labelled-token scripts/sync-all-acp-agents.ts:15
      Labelled token / key literal (vendor format unknown — verify it is not a live credential)
      const API_KEY = 'acp-…4a2'
    • low Secrets in code secret-high-entropy-token scripts/full-reputation-sync.ts:26
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const USDC_ADDRESS = '0x83…913'
      quoted
    • low Secrets in code secret-password-literal scripts/sync-all-acp-agents.ts:15
      Hard-coded password / key literal (may be an example)
      const API_KEY = 'acp-…4a2'
    • low Secrets in code secret-high-entropy-token src/lib/acp-indexer.ts:13
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const USDC_ADDRESS = '0x83…913'
      quoted

    Files scanned: 44. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 52/100

    • 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
    • 30Running it twice. 20 mutating operations with no state check
    • 40Consistency. Frontmatter name (OpenClawdy) differs from the folder (hub1)
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 58 steps
    • 100Execution cost. Instruction body is 3171 tokens
    • low 12 top-level sections: this looks like several domains in one skill

    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
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -34 of 4 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 200: enough signal without eating the budget
    • +4Structure: 44 headings
    • +3Step-by-step instructions: 58 items
    • +4Has examples (33 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.