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AC FarmDash Trail Marshal

Use when composing multi-step DeFi workflows from FarmDash tools: plan, run, inspect supervised pipelines. Wallet steps stay policy-gated, preview-only.

ClawHub Agent Skills author: FarmDash v0.1.9 MIT-0 3 files body ≈ 4 813 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedureInfrastructuretype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
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 · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "icon"
    • note frontmatter-key unknown frontmatter key "env"

    Process rating: all ten parameters 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (FarmDash Trail Marshal) differs from the folder (farmdash-trail-marshal)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70Execution cost. Instruction body is 4813 tokens
    • 100Steps. 37 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 8 branches, has a failure section
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 152: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 37 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

    External checks

    ClawHub: clean
    This skill is a disclosed DeFi workflow planner that records guarded workflow sessions but does not itself execute wallet transactions.
    LLM: benign (high) · VirusTotal: · 7 Sept 2026