SKILLEMALL.ai

AC spec-executor

Execution companion for spec-workflow: state navigation, task tracking via tasks.md, incremental delivery, and session recovery. Use after spec-workflow produces the plan.

ClawHub Agent Skills author: Naozi v1.0.1 MIT-0 3 files body ≈ 4 167 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Inputs and preconditions w 11
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 · 0

    ✓ No critical or high findings

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

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "created"

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 16 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Execution cost. Instruction body is 4167 tokens
    • 100Steps. 72 steps
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 171: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 72 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    The skill is a coherent spec-first coding workflow; its file edits, testing, and commits are expected for that purpose and are paired with phase checks and user confirmation.
    LLM: benign (medium) · VirusTotal: · 29 May 2026