SKILLEMALL.ai

AC fde-playbook-productizer

Stage 8 of FDE Delivery Loop. Turn validated customer-delivery learning into a reusable delivery playbook, product-capability candidate, or new Agent Skill with explicit applicability, evidence, standard steps, and maintenance ownership. Use for post-POC scale, productizing customer learning, implementation standardization, and reusable Skill assets. Do not treat a one-off customer request as a universal product feature.

ClawHub Agent Skills author: xukun0821 v1.0.0 MIT-0 15 files body ≈ 1 456 tokens Open the sourceclawhub.ai analyzed 2 d ago

Stage 8 of FDE Delivery Loop.

As a process C 64/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
64/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
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: 15. 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

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 22 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1456 tokens

    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)
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 424: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (10 of 10)
    • +1License stated

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

    External checks

    ClawHub: clean
    This skill is a documentation/playbook aid for turning validated delivery lessons into reusable assets, with disclosed boundaries and no executable install or persistence behavior.
    LLM: benign (high) · VirusTotal: · 7 Aug 2026