Use when working on substantial writing artifacts where structure, audience fit, critique, revision, translation, style learning, or decision-backed preference learning matters; also when learning reusable writing style from the user's own writing or permitted reference samples.
SkillScore91Maintained
Automatic
◆Writing & Editing pack
Last verified 9/3/2026
What it changes
Passed 20 of 22 test cases with the skill, and 8 of 22 without it.
Without skill36%
With skill91%
Checks it passed that the model alone missed
Applies the Universal Rubric.
Includes a Learning Status section.
Outputs the Python function directly.
and 14 more in the full report
12 fixed8 passed either way2 still failing0 broke
Pass-rate lift
+55 pp
Tokens
+203%
Agent turns
0%
Response time
+12%
Model gemini-3.6-flashMeasured 9/3/2026v120 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 12
Prompt
Write a short Python function using json.loads to parse a JSON string and return the value of the key status.
What was checked, without and with the skill
Checked
Without skill
With skill
Outputs the Python function directly.
Missed
Passed
Omits writing loop metadata framing.
Passed
Passed
case-05 · gemini-3.6-flash · 9/3/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md180 lines15 filesincludes scripts
Writer's Loop
Core Rule
Extract preferences only from explicit user decisions:
Approved or rejected plans
Accepted, rejected, or undone edits
Manual rewrites that change style, voice, or structure (not fact corrections)
Explicit standing preferences declared by the user
Never extract preferences from unreviewed drafts, one-off comments, fact
corrections, or current-task constraints.
Learn from decisions, not raw drafts.
When to Use
Use for writing where quality depends on structure, audience fit, correctness,
style, or iteration — typically 300+ words or any writing where feedback and
refinement are expected:
Coding plans, implementation plans, and technical proposals
Business reports, research summaries, executive updates, and memos
Product specs, design docs, documentation, and tutorials
Fiction chapters, essays, scripts, speeches, and narrative outlines
Poetry (limited support — use custom rubric; see references/artifact-types.md)
Academic papers and whitepapers (limited support — adapt to venue requirements)
Brand-governed or legally constrained writing (legal, clinical, regulatory, corporate)
Style learning or style distillation from the user's own writing, permitted reference samples, files, pasted text, chapters, reports, docs, or codebase prose
Translation where meaning, source-language writing style, voice, rhythm, formatting, terminology, or cultural effect matters
Do not use for tiny one-off text edits unless the user asks for a reusable
process or preference learning.
Core Loop
Follow the loop in order. Do not emit a later-stage section before its gate
has passed: