SKILLEMALL.ai

AC edn

Use before and after meaningful implementation work to keep a local engineering notebook synchronized with the repository. Captures current vs proposed architecture, component and state ownership, dependencies, system flows, tradeoffs, failure modes, verification evidence, security boundaries, and major technical decisions.

ClawHub Agent Skills author: Siddhant Kuwar v0.1.0 MIT-0 7 files body ≈ 2 199 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use before and after meaningful implementation work to keep a local engineering notebook synchronized with the repository.

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

AnalyzerData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
59/100
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: 7. 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 59/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Steps. 82 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2199 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 325: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 82 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This skill creates and maintains a local engineering notebook for a repository, with disclosed local file changes and no external service or hidden execution behavior.
    LLM: benign (high) · VirusTotal: · 8 Aug 2026