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BC OpenClaw Memory — Agent Skill

Use OpenClaw Memory when:

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 2 765 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Use OpenClaw Memory when:

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

ProcedureMongoDBDockerInfrastructureAI and agentsData and analyticstype 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
30
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 · 0

    ✓ No critical or high findings

    Files scanned: 1. 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)
    • warning description-short description under 40 chars: too little signal for triggering

    Process rating: all ten parameters 53/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (OpenClaw Memory — Agent Skill) differs from the folder (openclaw-memory-skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 110 steps
    • 100Execution cost. Instruction body is 2765 tokens
    • low 11 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
    • +3Description length 25: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • -219 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 29 headings
    • +3Step-by-step instructions: 110 items
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.