SKILLEMALL.ai
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Autonomous wallet operations for AI agents on Monad — swap, stake, deploy wallets, trade memecoins, and manage spending policies via natural language.

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 2 155 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Autonomous wallet operations for AI agents on Monad — swap, stake, deploy wallets, trade memecoins, and manage spending policies via natural language.

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureAI 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
B
86/100
safety, quality, tests
Safety 60%
94
Quality 40%
73
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-high-entropy-token package-lock.json:51
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…KLN+g+y7a7…rLk+m3yr0gt+/h9ST…oRw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:248
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-fFd+k9gtczqlr0/BruW…lNZ+bTkG…pHU+jA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:733
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…p81+8Ob3…L40/b0i7…gQw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:795
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-+lF0B…kdX+94aG…d8c+B3KT…U6A==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:917
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…jgR+Mkmf+D189…ihQ==",
    detector
  • low Secrets in code secret-high-entropy-token skill.json:353
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "description": "Orderbook contract address (e.g. 0x06…394)"
    quoted

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 48/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 19 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 73 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2155 tokens
  • 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
  • +2Single-language instructions
  • +3Description length 150: enough signal without eating the budget
  • +4Structure: 48 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.