SKILLEMALL.ai

AC anti-slop

Detects and removes "AI slop" — the formulaic vocabulary, sentence structures, sycophantic openers/closers, over-formatting (bullet walls, bold spam, needless headers), and code anti-patterns (over-engineering, swallowed errors, hallucinated APIs, dead code) that make writing or code read as generic and machine-produced. Use this proactively as a self-edit pass on any substantial prose (essays, articles, emails, reports, marketing copy, creative writing, documentation) or any non-trivial code you write or review — don't wait to be asked. Also trigger explicitly whenever the user asks to make text "sound more human," "less like ChatGPT/AI," wants a "slop pass," asks you to de-slop, humanize, or tighten writing, or asks you to clean up bloated, over-engineered, or "vibe-coded" code. Do not use for one-line answers or trivial snippets where there's nothing to edit.

ClawHub Agent Skills v1.0.0 8 files body ≈ 2 494 tokens Open the sourceclawhub.ai analyzed 2 d ago

Detects and removes "AI slop" — the formulaic vocabulary, sentence structures, sycophantic openers/closers, over-formatting (bullet walls, bold spam, needless…

As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
C
53/100
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: 8. 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 53/100

    • 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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (python) 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 2494 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

    • +3Description length 874: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 23 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.

    External checks

    ClawHub: clean
    This skill is a disclosed editing aid that reviews writing or code for generic AI-style patterns and does not show hidden, destructive, persistent, or exfiltrating behavior.
    LLM: benign (high) · VirusTotal: