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CD OpenClaw Advanced Memory

Three-tier AI agent memory system — real-time capture, vector search, and LLM-curated long-term recall.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 10 files · 1 script body ≈ 649 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Three-tier AI agent memory system — real-time capture, vector search, and LLM-curated long-term recall.

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

ProcedureDockerAI and agentsInfrastructuretype 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
72/100
safety, quality, tests
Safety 60%
79
Quality 40%
61
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 4

  • high Dangerous commands cmd-persistence scripts/install.sh:43
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null | grep -v "mem_warm.py" | grep -v "mem_curate.py"; echo "$WARM_CRON"; echo "$CURATE_CRON") | crontab -
Medium and low: 3
  • low Risky intent intent-offensive-security README.md:219
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    "context": "A/B tested both architectures on the Volt red team suite",
    quoted
  • low Dangerous commands cmd-cron-mention scripts/install.sh:43
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null | grep -v "mem_warm.py" | grep -v "mem_curate.py"; echo "$WARM_CRON"; echo "$CURATE_CRON") | crontab -
  • low Risky intent intent-offensive-security SKILL.md:76
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    "context": "A/B tested both architectures on red team suite",
    quoted

Files scanned: 10. 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-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 40Consistency. Frontmatter name (OpenClaw Advanced Memory) differs from the folder (openclaw-advanced-memory)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 9 steps
  • 100Execution cost. Instruction body is 649 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)
  • +3Description length 103: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -36 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.