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BC haggle-protocol

On-chain negotiation protocol for AI agents. Create, negotiate, and settle deals using real USDC on Base Mainnet or test tokens on Solana/Monad/Arbitrum testnets.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files · 1 script body ≈ 2 213 tokens Open the sourcegithub.com↗ analyzed 2 d ago

On-chain negotiation protocol for AI agents.

As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureGitHubSales and CRMAI 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
84/100
safety, quality, tests
Safety 60%
95
Quality 40%
67
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token SKILL.md:22
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base | **Mainnet** | `0xB7…514` | USDC (`0x83…913`) |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:23
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Solana | Devnet | `DRXG…Gbq` | SPL Token |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:24
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Monad | Testnet | `0x30…CeC` | MockERC20 |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:25
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Base | Sepolia | `0x30…CeC` | MockERC20 |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:26
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | Arbitrum | Sepolia | `0x30…CeC` | MockERC20 |
    table

Files scanned: 2. 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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "files"

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 26 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2213 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 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
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 162: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.