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CC AB-Agents-Memory

🧠 Long-term memory system for OpenClaw agents. Manages entities, context, and knowledge base with Obsidian integration. By AB-Agents (Alex Burr).

Not recommendedcritical or high security findings
ClawHub Agent Skills author: alexburrstudio v1.0.5 MIT-0 16 files · 2 scripts body ≈ 706 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationObsidianAI and agentstype 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
70/100
safety, quality, tests
Safety 60%
74
Quality 40%
63
Run on models
none yet
Process rating
C
54/100
Has gaps
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.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 5

  • high Dangerous commands cmd-persistence setup.sh:98
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null | grep -v "AB-Memory-Vault"; echo "0 3 * * * cd $VAULT_DEST && bash $NIGHTLY_SCRIPT >> $VAULT_DEST/Memory/Processing/Nightly/logs/\$(date +\%Y-\%m-\%d).log 2>&1") | crontab -
Medium and low: 4
  • medium Broad scope meta-agent-memory-dump agents/AB-Archivus/IDENTITY.md
    Agent memory / workspace files bundled with the skill (2) — likely a workspace dump with personal data or tokens
    agents/AB-Archivus/IDENTITY.md, agents/AB-Archivus/SOUL.md
  • low Dangerous commands cmd-cron-mention setup.sh:98
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null | grep -v "AB-Memory-Vault"; echo "0 3 * * * cd $VAULT_DEST && bash $NIGHTLY_SCRIPT >> $VAULT_DEST/Memory/Processing/Nightly/logs/\$(date +\%Y-\%m-\%d).log 2>&1") | crontab -
  • low Secrets in code secret-high-entropy-token SKILL.md:88
    High-entropy token-like string (may be an id, hash or a credential)
    🥝 TON: UQDH…yfr
  • low Secrets in code secret-high-entropy-token SKILL.md:89
    High-entropy token-like string (may be an id, hash or a credential)
    🥝 USDT TRC20: TE1m…HZc

Files scanned: 16. 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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "acceptLicenseTerms"

Process rating: all ten parameters 54/100

  • 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
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 706 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)
  • +3Output format is not stated: the model decides each time
  • -218 emoji in the instructions: noise for the model
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +3Description length 146: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (3 code blocks)
  • +1License stated
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This memory skill appears purpose-aligned, but it installs a persistent agent and cron job by default while handling long-term local memory and session data with weak consent and retention boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026