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CF humanize

Detect and remove AI writing patterns from academic manuscripts and response-to-reviewers letters. Scans for 27 common AI-generated text patterns and rewrites flagged passages to sound naturally human-written while preserving technical accuracy, bounding how much of the text a rewrite is allowed to touch.

Aperivue/medsci-skills Agent Skills author: Aperivue MIT 15 files · 4 scripts body ≈ 4 629 tokens Open the sourcegithub.com↗ analyzed 32 h ago

Detect and remove AI writing patterns from academic manuscripts and response-to-reviewers letters.

As a process F 45/100 · Will not run — References files that are not bundled: scripts/check_rhetorical_density.py, scripts/check_paren_spans.py, references/r2r_voice.md

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
F
45/100
Will not run
References files that are not bundled: scripts/check_rhetorical_density.py, scripts/check_paren_spans.py, references/r2r_voice.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/check_rhetorical_density.py
  • warning missing-ref reference to a missing file: scripts/check_paren_spans.py
  • warning missing-ref reference to a missing file: references/r2r_voice.md
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 45/100

Will not run. References files that are not bundled: scripts/check_rhetorical_density.py, scripts/check_paren_spans.py, references/r2r_voice.md
  • 0Tools and files. 3 referenced file(s) missing: scripts/check_rhetorical_density.py, scripts/check_paren_spans.py, references/r2r_voice.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 18 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 4629 tokens
  • 100Steps. 33 steps
  • 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
  • low 10 top-level sections: this looks like several domains in one skill
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 306: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 33 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.