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AC sushiswap-api

REST API for optimized token swapping (including executable transaction generation), swap quoting, and pricing using the SushiSwap Aggregator. Use this skill when the user wants to: - Get a swap quote between two tokens on 40+ evm networks - Generate executable swap transaction data - Fetch token prices for a specific network or token - Retrieve token metadata - Discover supported AMM liquidity sources - Integrate SushiSwap swapping or pricing logic via HTTP/REST (and not the SushiSwap Javascript API)

modbender/skill-library-mcp Agent Skills author: modbender MIT 3 files body ≈ 645 tokens Open the sourcegithub.com↗ analyzed 3 d ago

REST API for optimized token swapping (including executable transaction generation), swap quoting, and pricing using the SushiSwap Aggregator.

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationSoftware developmentAI 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
A
92/100
safety, quality, tests
Safety 60%
94
Quality 40%
88
Run on models
none yet
Process rating
C
64/100
Has gaps
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

    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 references/openapi.yaml:251
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - address: '0xEe…EeE'
      quoted
    • low Secrets in code secret-high-entropy-token references/openapi.yaml:255
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - address: '0xC0…Cc2'
      quoted
    • low Secrets in code secret-high-entropy-token references/openapi.yaml:259
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - address: '0x6B…fE2'
      quoted
    • low Secrets in code secret-high-entropy-token references/openapi.yaml:316
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - address: '0xEe…EeE'
      quoted
    • low Secrets in code secret-high-entropy-token references/openapi.yaml:320
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - address: '0xC0…Cc2'
      quoted
    • low Obfuscation obf-base64-blob references/openapi.yaml:339
      Long base64-looking blob (quoted — discussed, not commanded)
      data: "0x5f…15d
      quoted

    Files scanned: 3. 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 64/100

    • 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
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 645 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 506: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.