SKILLEMALL.ai

AC minimalist

Subtraction-first engineering for any coding task. Channels an engineer who ships by deleting: question whether the change needs to exist (YAGNI), reuse what the codebase already has, prefer stdlib and native platform features over new dependencies, and write the minimum code that fully works — with every safety guard intact. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "minimalist", "minimal mode", "less code", "simplest thing", "yagni", "trim it", or complains about over-engineering, bloat, boilerplate, or dependency creep. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries).

ClawHub Claude Code author: Divyesh Jayswal v1.0.0 MIT-0 2 files body ≈ 1 252 tokens Open the sourceclawhub.ai analyzed 35 h ago

Subtraction-first engineering for any coding task.

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 2. 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 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 100Steps. 23 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1252 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • high The skill tells the model to perform an irreversible action with no human approval
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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

    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 793: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 23 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill is a disclosed coding-style helper that pushes for smaller code changes and does not show hidden access, network activity, credential use, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026