CD agent-memory-tools
Searches, stores, and manages agent memory across 4 sources (fact store, vector embeddings, BM25, knowledge graph). Runs 100% local via Ollama — no API keys, no cloud dependency. Use when searching workspace knowledge, extracting facts from text, detecting contradictions, auto-ingesting file changes, or building entity graphs. Triggers on memory recall, fact extraction, knowledge search, workspace indexing.
As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
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 · 4
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high Dangerous commands
cmd-persistencereferences/configuration.md:25Persistence mechanism (cron / launchd / scheduled task / autorun registry)<!-- ~/Library/LaunchAgents/com.memory-auto-ingest.plist -->
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high Dangerous commands
cmd-persistencereferences/configuration.md:55Persistence mechanism (cron / launchd / scheduled task / autorun registry)schtasks /create /tn "MemoryAutoIngest" /tr "python scripts/auto_ingest.py --scan" /sc minute /mo 5
Medium and low: 2
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medium Dangerous commands
cmd-pipe-to-shellsetup.sh:40Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)curl -fsSL https://ollama.com/install.sh | sh
vendor-host -
low Dangerous commands
cmd-pipe-to-shellsetup.sh:39Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed; the skill's own vendor host)echo " → Running: curl -fsSL https://ollama.com/install.sh | sh"
code literalvendor-host
Files scanned: 18. 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 45/100
- 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
- 50Steps. 2 steps
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1160 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -31 of 11 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 410: enough signal without eating the budget
- +4Structure: 12 headings
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.