BF agentmm
AgentMM memory & log management skill — gives AI agents persistent memory storage and structured logging. Use when the user asks to remember information, recall memories, or record/query logs. Requires env var AGENTMM_API_KEY (format: amm_sk_xxx).
As a process F 36/100 · Will not run — References files that are not bundled: scripts/agentmm
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The text references files that are not there: add them or drop the references.
- 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
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-credential-usescripts/forget_memory.sh:36Credential used in a network call (verify the destination is the intended service)curl -s -X DELETE "$API_BASE/memory?key=$KEY" \
Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/agentmm - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 36/100
- 0Tools and files. 1 referenced file(s) missing: scripts/agentmm
- 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
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (agentmm) differs from the folder (agentmm-skills)
- 70When it triggers. States when to use, but not when not to
- 100Steps. 40 steps
- 100Execution cost. Instruction body is 991 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- -32 of 9 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 247: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.