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DC wallet

(no description)

Not recommendedlow grade D
modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 4 300 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Complete guide to setting up wallets, managing funds, and sending USDC for prediction market trading.

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ProcedureWriting 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
D
51/100
safety, quality, tests
Safety 60%
85
Quality 40%
0
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

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. Add a description to the frontmatter: without it the skill never triggers.
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 · 7

✓ No critical or high findings

Medium and low: 7
  • medium Exfiltration net-credential-use SKILL.md:358
    Credential used in a network call (verify the destination is the intended service)
    # curl https://manifold.markets/api/v0/me -H "Authorization: Bearer $MANIFOLD_KEY"
  • medium Exfiltration net-credential-use SKILL.md:361
    Credential used in a network call (verify the destination is the intended service)
    # curl https://api.kalshi.com/v1/balance -H "Authorization: Bearer $KALSHI_KEY"
  • low Secrets in code secret-high-entropy-token SKILL.md:108
    High-entropy token-like string (may be an id, hash or a credential)
    clawearn wallet send --to 0x74…aED --amount 100
  • low Secrets in code secret-high-entropy-token SKILL.md:192
    High-entropy token-like string (may be an id, hash or a credential)
    clawearn wallet send --to 0x74…aED --amount 100
  • low Secrets in code secret-high-entropy-token SKILL.md:210
    High-entropy token-like string (may be an id, hash or a credential)
    From: 0x9E…873
  • low Secrets in code secret-high-entropy-token SKILL.md:211
    High-entropy token-like string (may be an id, hash or a credential)
    To:   0x74…aED
  • low Secrets in code secret-high-entropy-token SKILL.md:218
    High-entropy token-like string (may be an id, hash or a credential)
    100 USDC sent to 0x74…aED

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Progress reporting. Says nothing while it works
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4300 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 131 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • -262 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 61 headings
  • +3Step-by-step instructions: 131 items
  • +4Has examples (31 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.