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Distill Opus-level reasoning into optimized instructions for Haiku 4.5 (and Sonnet). Generates explicit, procedural prompts with n-shot examples that maximize smaller model performance on a given task. Use when user says "down-skill", "distill for Haiku", "optimize for Haiku", "make this work on Haiku", "generate Haiku instructions", or needs to delegate a task to a smaller model with high reliability.

Use this Skill: https://skilld.dev/gh/oaustegard/claude-skills/down-skilling

This session only. Nothing lands on disk.

examplesmeeting-notes.md

≈718 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Meeting Notes Generation

Task type: Information extraction with multiple output sections Key gaps addressed: parallel-consistency, summarization-fidelity, counting-enumeration

Original (Opus-level)

"Turn this meeting transcript into clean notes with decisions, action items, and next steps."

Distilled Haiku Prompt

<role>
You are a meeting notes assistant that converts transcripts into
structured summaries.
</role>

<task>
Convert the meeting transcript into structured notes with five sections.
Follow the output template exactly.
</task>

<rules>
1. Output exactly these sections in this order:
   **Meeting**: [title] | [date] | [attendees]
   **Summary**: 2-3 sentences, max 50 words
   **Decisions**: numbered list of decisions made
   **Action Items**: numbered list, format: "[Person] — [task] — [deadline or 'TBD']"
   **Next Steps**: numbered list of upcoming milestones or follow-ups
2. Each section must have at least one item. If none exist, write "None identified."
3. Attendees: list only names that speak in the transcript.
4. Decisions: must be something the group agreed to, not proposals or ideas.
5. Action items: must have an assigned person. If no person named, attribute
   to "Team" and flag with "(unassigned)".
6. Do not include side conversations, jokes, or off-topic discussion.
7. Maximum 250 words total.
</rules>

<examples>
<example>
<input>
[Transcript excerpt]
Sarah: OK so we're going with the new vendor for Q2. Mike, can you get
the contract reviewed by legal by next Friday?
Mike: Sure. Oh hey did anyone see the game last night?
Sarah: Ha, no. Anyway, we also need to decide on the launch date.
Lisa: I think March 15th works. Everyone agree?
Sarah: Works for me. Mike?
Mike: Yep, March 15th.
</input>
<o>
**Meeting**: Vendor & Launch Planning | [date not specified] | Sarah, Mike, Lisa
**Summary**: Team confirmed new vendor for Q2 and set March 15th as launch date. Mike to get contract through legal review.
**Decisions**:
1. New vendor selected for Q2.
2. Launch date set for March 15th.
**Action Items**:
1. Mike — Get contract reviewed by legal — by next Friday
**Next Steps**:
1. Legal contract review completion (next Friday)
2. Launch preparation for March 15th
</o>
<reasoning>
"Did anyone see the game" excluded per rule 6. Vendor selection and
launch date both qualify as decisions (explicit agreement). Only Mike
has a named action item.
</reasoning>
</example>
</examples>

<context>
{{transcript}}
</context>

Why it works for Haiku

  • Five sections with exact formatting prevents structural drift
  • Action item format is fully specified (person — task — deadline)
  • Rule 4 distinguishes decisions from proposals (Haiku would conflate them)
  • Rule 5 handles unassigned actions with explicit default
  • Example excludes off-topic content, demonstrating rule 6 in practice

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub12d

    The skill provides guidelines and templates for optimizing AI prompts for smaller models by distilling complex reasoning into explicit procedures and many-shot examples. No security issues were detected.

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    Risk: LOW · No issues

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Signed by skilld at 5e58100. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 weeks ago
metadata
{
  "author": "Oskar Austegard and Opus",
  "version": "1.3.1"
}

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