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CC pet-me-master

Interactive gotchi petting via Bankr wallet. Check cooldowns, pet when ready, track your kinship journey. Daily ritual for bonding with your Aavegotchi NFTs on Base chain.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 29 files · 19 scripts body ≈ 2 683 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Interactive gotchi petting via Bankr wallet.

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSecurityOperations and projectsWriting and documentstype 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
67/100
safety, quality, tests
Safety 60%
65
Quality 40%
70
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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.

Exfiltration 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 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".

For the author

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

  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.
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 · 14

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:94
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -L https://foundry.paradigm.xyz | bash
Medium and low: 13
  • medium Exfiltration net-credential-use scripts/check-and-remind.sh:77
    Credential used in a network call (verify the destination is the intended service)
    curl -s -X POST "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" \
  • low Secrets in code secret-high-entropy-token manual-pet-batch1.sh:4
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CONTRACT="0xA9…dBF"
    quoted
  • low Secrets in code secret-high-entropy-token pet-now.sh:4
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CONTRACT="0xA9…dBF"
    quoted
  • low Secrets in code secret-high-entropy-token README.md:16
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "contractAddress": "0xA9…dBF",
    quoted
  • low Secrets in code secret-high-entropy-token README.md:82
    High-entropy token-like string (may be an id, hash or a credential)
    - Base Contract: 0xA9…dBF
  • low Secrets in code secret-high-entropy-token references/contract-info.md:5
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **Diamond Contract:** `0xA9…dBF`
    quoted
  • low Secrets in code secret-high-entropy-token scripts/auto-remind-and-pet.sh:9
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CONTRACT="0xA9…dBF"
    quoted
  • low Exfiltration exfil-webhook-url scripts/check-and-remind.sh:77
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    curl -s -X POST "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" \
    placeholder
  • low Secrets in code secret-high-entropy-token scripts/pet-via-bankr.sh:13
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CONTRACT="0xA9…dBF"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:70
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "contractAddress": "0xA9…dBF",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:178
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **Contract:** `0xA9…dBF` (Base mainnet)
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:191
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "to": "0xA9…dBF",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:380
    High-entropy token-like string (may be an id, hash or a credential)
    - **Base Contract:** 0xA9…dBF

Files scanned: 29. 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 107 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2683 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 top-level sections: this looks like several domains in one skill

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
  • -5TODO / placeholder text left in the skill
  • -264 emoji in the instructions: noise for the model
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -313 of 19 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 171: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 107 items
  • +4Has examples (16 code blocks)

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