SKILLEMALL.ai

AC iterate-design-review

Refine architecture designs or execution plans through a context-grounded independent review loop. Use when a draft needs reliable convergence on scope, layering, data ownership, interfaces, completeness, and simplicity before user approval or implementation. Do not use for ordinary code review or a trivial one-off answer.

ClawHub Agent Skills author: Jerry v0.1.0 MIT-0 3 files body ≈ 1 973 tokens Open the sourceclawhub.ai analyzed 4 d ago

Refine architecture designs or execution plans through a context-grounded independent review loop.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerInfrastructureSoftware developmenttype 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
60/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 60/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 42 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1973 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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 324: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 42 items
    • +4Has examples (0 code blocks)

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

    External checks

    ClawHub: clean
    This skill provides a structured design-review workflow and does not show hidden installation, credential access, persistence, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 2 Sept 2026