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BC qr-auction-bidder

Bid on $QR auctions at qrcoin.fun. Place bids on Base mainnet using USDC. Uses Bankr for transaction execution — no wallet management needed.

modbender/skill-library-mcp Agent Skills author: modbender MIT 3 files body ≈ 2 158 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Bid on $QR auctions at qrcoin.fun. Place bids on Base mainnet using USDC. Uses Bankr for transaction execution — no wallet management needed.

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ProcedureGitHubSoftware developmenttype 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
82/100
safety, quality, tests
Safety 60%
92
Quality 40%
68
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 8

✓ No critical or high findings

Medium and low: 8
  • low Secrets in code secret-high-entropy-token references/contract-addresses.md:7
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | QRAuctionV5 | `0x73…176` |
    table
  • low Secrets in code secret-high-entropy-token references/contract-addresses.md:8
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | USDC | `0x83…913` |
    table
  • low Secrets in code secret-high-entropy-token references/contract-addresses.md:9
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Treasury | `0x2C…1B1` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:28
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | QRAuctionV5 | `0x73…176` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:29
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | USDC (Base) | `0x83…913` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:65
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    -d '{"jsonrpc":"2.0","method":"eth_call","params":[{"to":"0x73…176","data":"0xe4b8f0de"},"latest"],"id":1}' \
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:75
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    -d '{"jsonrpc":"2.0","method":"eth_call","params":[{"to":"0x73…176","data":"0x91a3823f"},"latest"],"id":1}' \
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:83
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    -d '{"jsonrpc":"2.0","method":"eth_call","params":[{"to":"0x73…176","data":"0x4b6014f6"},"latest"],"id":1}' \
    quoted

Files scanned: 3. 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 61/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 20 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 31 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2158 tokens
  • 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
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 141: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.