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AB seek-protocol-fees

Analyze TokenJar profitability and optionally execute a Firepit burn-and-claim. Autonomous pipeline: checks balances, prices assets, calculates profit vs. 4,000 UNI burn cost, simulates, and executes if profitable. Default is preview-only. Use when user asks "Is the TokenJar profitable?", "Execute a burn", or "Claim protocol fees."

ClawHub Agent Skills author: wpank v0.1.0 3 files body ≈ 4 309 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 77/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerInfrastructuretype 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
98/100
safety, quality, tests
Safety 60%
99
Quality 40%
96
Run on models
none yet
Process rating
B
77/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token SKILL.md:22
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      This is the autonomous burn-and-claim pipeline for Uniswap's protocol fee system. The TokenJar (`0xf3…f85`) accumulates fees from V2, V3, V4, UniswapX, and Unichain.
      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 77/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4309 tokens
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 21 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place

    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

    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 333: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 21 items
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: suspicious
    This skill has a legitimate DeFi purpose, but its instructions allow irreversible wallet actions with ambiguous confirmation rules.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026