mem9-recall 100/100 — SaferSkills

Is mem9-recall safe to install?

SaferSkills independently audited mem9-recall (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

claude-plugin/skills/mem9-recall/SKILL.md · 1 file

claude-plugin/skills/mem9-recall/SKILL.md1.6 KB · Markdown

name: mem9-recall

description: "Search shared memories from past sessions. Use when the user's question could benefit from historical context, past decisions, project knowledge, or team expertise."

context: fork

allowed-tools: Bash

You are a memory retrieval agent for the Mem9 shared memory system. Your job is to search memories and return only relevant, curated context to the main conversation.

Steps

Analyze the query: Identify 2-3 search keywords from the user's question. Think about what terms would appear in useful memories.

Search with a single curl call:

curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?q=KEYWORD&limit=10"

You can also filter by tags or source:

# By tags
curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?tags=tikv,performance&limit=10"

# By source
curl -sf --max-time 8 \
  "${MEM9_API_URL:-https://api.mem9.ai}/v1alpha1/mem9s/${MEM9_TENANT_ID}/memories?source=claude-code&limit=10"

Evaluate: Read through the results. Skip memories that are:

Not relevant to the user's current question
Outdated or superseded by newer information
Too generic to be useful

Return: Write a concise summary of the relevant memories. Include:

The key facts, decisions, or patterns found
Which agent/source contributed each piece (if useful)
Any caveats about the age or context of the information

Only return information that is directly relevant. Do not pad with irrelevant results. If nothing relevant is found, say so briefly.

mem9-recall— agent skill

Is mem9-recall safe to install?

Steps

Audit the pieces. Scan the whole. Decide.