BC openclaw-mem0
Install, configure, diagnose, and operate the openclaw-mem0 long-term memory plugin for OpenClaw agents. Use when the user wants to set up mem0 memory (platform or open-source/self-hosted mode), configure OSS components (embedder, vector store, LLM, historyDbPath), debug memory issues (SQLITE_CANTOPEN crash loops, memories not being stored or recalled, Qdrant/Ollama connectivity), use the `openclaw mem0` CLI (search, stats), or understand how auto-recall and auto-capture work in agent sessions.
As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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.
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.
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
- 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.
- 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
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high Dangerous commands
cmd-persistencereferences/troubleshooting.md:130Persistence mechanism (cron / launchd / scheduled task / autorun registry)launchctl bootstrap gui/$UID ~/Library/LaunchAgents/ai.openclaw.gateway.plist
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 50/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (openclaw-mem0) differs from the folder (mem0-config)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 4 steps
- 100Execution cost. Instruction body is 1104 tokens
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
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 499: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 4 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.