How do I install the Style Learning Loop skill?

Run npx skillmds@latest add folken2/style-learning-loop-3 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Style Learning Loop safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Style Learning Loop?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Style Learning Loop free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Style Learning Loop?

Folken2 (@folken2) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Style Learning Loop by folken2 — Agent Skill

Name: Style Learning Loop
Author: Folken2

File contents

The style learning loop

The agent gets better at sounding like the user over time. The mechanism is a markdown topic called writing-style that accumulates fingerprints and gets compressed into rules.

Stage 1 — collect fingerprints (every send)

For each sent email, call learn_style_from_sent_email(body, recipient, subject). This appends a structured note like:

## Sent sample
- to: anna@…
- subject: Q3 budget
- words/sentences: 84/6 (avg 14.0 w/s)
- opener: "Hi Anna,"
- signoff: "Thanks, J"
- punctuation: 0! / 1? / 6 contractions / 2 em-dashes / 0 bullet lines

These are raw signals, not rules. Don't show them to the user; they're working memory.

Stage 2 — consolidate (every ~10 samples)

When fingerprints accumulate, read them and derive durable rules. Then call consolidate_writing_style(distilled_markdown) with a tight rulebook.

A good rulebook looks like:

# User voice — rulebook (v3)

## Opener
- Default: `Hi <name>,` on first-touch threads.
- In replies, no opener — jumps straight in.

## Sign-off
- Almost always: `Thanks, J`
- Casual / one-liner: just `J`
- Never: `Best regards`, `Sincerely`, `Kind regards`

## Sentence shape
- Average 14 words per sentence; cap at 25.
- 5–8 sentences per email is the common shape.

## Voice tics
- Uses contractions freely (~6 per email).
- Em-dashes for asides — comfortably.
- Zero exclamation marks. Convert ! → . if drafting.
- One rhetorical question per email is fine; more is rare.

## Recipient-specific overrides
- See `recipient-<email>` memories for one-off calibrations.

Keep it under ~2KB. Rules the drafting/coaching tools can apply mechanically.

Stage 3 — when the user edits before sending

If the taskpane reports an edit (sent body ≠ drafted body), the edit is the strongest learning signal. Save the delta as a memory note:

recall_memory → check for "edit-patterns" topic
save_memory(topic="edit-patterns", content="Cut 'Just wanted to check in — ' from openers. User prefers cold-start.")

These get folded into the rulebook on the next consolidation.

Anti-patterns

Over-fitting to one email. One short reply doesn't mean the user always wants short replies. Wait for ≥5 samples before claiming a rule.
Treating subject lines as rules. Subjects are highly contextual; don't generalize from them.
Burying durable rules in raw fingerprints. That's why Stage 2 exists. The rulebook is what recall_writing_style returns to drafting/coaching; raw fingerprints should be pruned.
Forgetting to consolidate. If the writing-style topic grows past ~5KB, consolidate now.

---name: style-learning-loop-3description: How to learn and refine the user's writing style from their sent emails, and when to consolidate fingerprints into a tight rulebook---# The style learning loopThe agent gets better at sounding like the user over time. The mechanism is a markdown topic called `writing-style` that accumulates fingerprints and gets compressed into rules.## Stage 1 — collect fingerprints (every send)For each sent email, call `learn_style_from_sent_email(body, recipient, subject)`. This appends a structured note like:```## Sent sample- to: anna@…- subject: Q3 budget- words/sentences: 84/6 (avg 14.0 w/s)- opener: "Hi Anna,"- signoff: "Thanks, J"- punctuation: 0! / 1? / 6 contractions / 2 em-dashes / 0 bullet lines```These are raw signals, not rules. Don't show them to the user; they're working memory.## Stage 2 — consolidate (every ~10 samples)When fingerprints accumulate, read them and derive durable rules. Then call `consolidate_writing_style(distilled_markdown)` with a tight rulebook.A good rulebook looks like:```markdown# User voice — rulebook (v3)## Opener- Default: `Hi <name>,` on first-touch threads.- In replies, no opener — jumps straight in.## Sign-off- Almost always: `Thanks, J`- Casual / one-liner: just `J`- Never: `Best regards`, `Sincerely`, `Kind regards`## Sentence shape- Average 14 words per sentence; cap at 25.- 5–8 sentences per email is the common shape.## Voice tics- Uses contractions freely (~6 per email).- Em-dashes for asides — comfortably.- Zero exclamation marks. Convert ! → . if drafting.- One rhetorical question per email is fine; more is rare.## Recipient-specific overrides- See `recipient-<email>` memories for one-off calibrations.```Keep it under ~2KB. Rules the drafting/coaching tools can apply mechanically.## Stage 3 — when the user edits before sendingIf the taskpane reports an edit (sent body ≠ drafted body), the edit is the strongest learning signal. Save the *delta* as a memory note:```recall_memory → check for "edit-patterns" topicsave_memory(topic="edit-patterns", content="Cut 'Just wanted to check in — ' from openers. User prefers cold-start.")```These get folded into the rulebook on the next consolidation.## Anti-patterns- **Over-fitting to one email.** One short reply doesn't mean the user always wants short replies. Wait for ≥5 samples before claiming a rule.- **Treating subject lines as rules.** Subjects are highly contextual; don't generalize from them.- **Burying durable rules in raw fingerprints.** That's why Stage 2 exists. The rulebook is what `recall_writing_style` returns to drafting/coaching; raw fingerprints should be pruned.- **Forgetting to consolidate.** If the writing-style topic grows past ~5KB, consolidate now.

Frequently asked questions

Style Learning Loop