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BC FarmDash Autonomous Operator

Orchestrate policy-bounded DeFi sessions, OODA plans, intent state, circuit breakers, and recovery; execution stays status-gated and separately authorized.

ClawHub Agent Skills author: FarmDash v1.0.11 MIT-0 3 files body ≈ 4 389 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, consistency, running it twice

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
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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 · 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)
  • 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 "icon"
  • note frontmatter-key unknown frontmatter key "env"

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 13 mutating operations with no state check
  • 40Consistency. Frontmatter name (FarmDash Autonomous Operator) differs from the folder (farmdash-autonomous-operator)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Failures and branches. 6 branches
  • 70Execution cost. Instruction body is 4389 tokens
  • 100Steps. 61 steps
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 155: enough signal without eating the budget
  • +4Structure: 48 headings
  • +3Step-by-step instructions: 61 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
This skill is a disclosed DeFi session operator with high-impact financial automation features, but its artifacts consistently require scoped grants or user signatures and do not show hidden or destructive behavior.
LLM: benign (high) · VirusTotal: · 6 Sept 2026