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AF fde-operator-os

Applied AI operator playbook for delivery leads who need to qualify an AI opportunity, turn messy operational reality into a structured business system, design a minimum viable loop, and define a delivery-ready expansion path. Use when the user needs full-cycle FDE judgment, operator-grade artifacts, state-action-evidence framing, pilot design, or a cross-industry method for taking an AI use case from opportunity to closed-loop delivery.

ClawHub Agent Skills author: lingxiaodu v0.1.0 MIT-0 2 files body ≈ 4 030 tokens Open the sourceclawhub.ai↗ analyzed 25 h ago

Applied AI operator playbook for delivery leads who need to qualify an AI opportunity, turn messy operational reality into a structured business system…

As a process F 66/100 · Will not run — References files that are not bundled: assets/templates/

ProcedureWriting and documentsSoftware developmenttype 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%
100
Quality 40%
81
Run on models
none yet
Process rating
F
66/100
Will not run
References files that are not bundled: assets/templates/
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/templates/

Process rating: all ten parameters 66/100

Will not run. References files that are not bundled: assets/templates/
  • 0Tools and files. 1 referenced file(s) missing: assets/templates/
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 6 mutating operations with no state check
  • 70Execution cost. Instruction body is 4030 tokens
  • 100Steps. 193 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 22 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 441: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 193 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a text-only consulting playbook for AI delivery work and shows no evidence of hidden execution, data access, persistence, or credential handling.
LLM: benign (high) · VirusTotal: · 9 Jul 2026