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Outline Budgeter

Community
WILLOSCAR
outline-budgeter

Merge/simplify an over-fragmented outline to hit a paper-like section budget (NO PROSE): target final ToC ~6–8 H2, fewer thicker H3.

Overview

PublisherWILLOSCAR
Repositoryresearch-units-pipeline-skills
Skill nameoutline-budgeter
Stars
513
Forks
39
Bundled files
Instructions only
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by WILLOSCAR on GitHub. Read the source before you install it.

Installation

Install the Outline Budgeter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/outline-budgeter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/WILLOSCAR/research-units-pipeline-skills.git /tmp/research-units-pipeline-skills
mkdir -p .claude/skills
cp -r /tmp/research-units-pipeline-skills/.codex/skills/outline-budgeter .claude/skills/outline-budgeter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Outline Budgeter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Outline Budgeter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Outline Budgeter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Outline Budgeter (NO PROSE)

Triggers & routing

  • Trigger: outline budget, merge sections, too many sections, H3 explosion, 大纲预算, 合并小节, 大纲太碎.
  • Use when: outline/outline.yml exists but would produce thin sections (too many H2/H3); before (or immediately after) section-mapper.

Purpose: prevent the most common survey failure mode: H3 explosion (too many tiny subsections) leading to a thin, outline-like PDF.

This skill rewrites outline/outline.yml into a paper-like budget:

  • Final ToC target: ~6–8 H2 sections (Intro / Related Work + 3–4 core chapters + Discussion + Conclusion)
  • H3 target: fewer, thicker subsections (per draft_profile: course_paper<=6, survey<=10, deep<=12)

Important: Discussion/Conclusion are appended in C5 merge (global sections), so the outline itself should usually be <=6 H2.

Inputs

  • outline/outline.yml
  • Optional (helps make merges evidence-aware):
    • queries.md (optional: if it sets draft_profile, use it to choose the H3 budget)
    • outline/mapping.tsv
    • outline/coverage_report.md
    • GOAL.md

Outputs

  • outline/outline.yml (updated in place)
  • outline/OUTLINE_BUDGET_REPORT.md (bullets-only; what was merged and why)

Workflow (NO PROSE)

  1. Read the outline and compute a simple budget snapshot:
  • If queries.md sets draft_profile (course_paper/survey/deep), use it to decide the H3 budget target.
  • H2 count (excluding Discussion/Conclusion, which are not in the outline)
  • Total H3 count
  • H3 count per H2 chapter
  1. Decide a merge plan (structure-first, evidence-aware):
  • Prefer merging adjacent H3s that share similar axes/keywords.
  • Prefer merging H3s with weak mapping coverage (if mapping.tsv exists).
  • If outline/coverage_report.md exists (from outline-refiner), use it to identify weak-coverage or high-reuse subsections to merge.
  • Use GOAL.md as the scope constraint: avoid merges that mix distinct research questions or scope boundaries.
  • Prefer moving fine-grained distinctions into bullets/axes instead of creating new subsections.
  1. Apply merges in outline/outline.yml:
  • Merge titles into a clearer, thicker subsection title.
  • Merge bullets (dedupe templates; keep Stage A fields: Intent/RQ/Evidence needs/Expected cites).
  • Keep ids stable when possible.
    • If you must change ids, record it explicitly in the report and assume mapping.tsv must be regenerated.
  1. Write outline/OUTLINE_BUDGET_REPORT.md:
  • Before/after counts.
  • List of merges (old ids/titles -> new id/title).
  • Any risks (e.g., mapping reset required).

Quality checklist

  • No placeholders (TODO/…/(placeholder)).
  • Outline budget matches the paper-like target.
  • Each remaining H3 is thick enough to sustain evidence-first writing (its bullets mention concrete comparisons + eval anchors + failure modes).

Troubleshooting

Issue: merging makes a subsection too broad

Fix:

  • Keep one H3, but split its bullets into explicit comparison axes and required evidence fields; defer fine-grained splits to later if evidence is strong enough.

Issue: mapping breaks after id changes

Fix:

  • Rerun section-mapper to regenerate outline/mapping.tsv, then rerun outline-refiner.

Frequently asked questions

What does the Outline Budgeter AI skill do?

Merge/simplify an over-fragmented outline to hit a paper-like section budget (NO PROSE): target final ToC ~6–8 H2, fewer thicker H3.

Why use Outline Budgeter on TypingMind?

Because you install it once and use it with any model. Outline Budgeter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Outline Budgeter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/outline-budgeter. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Outline Budgeter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Outline Budgeter?

As many as you like. As long as a model supports skills, you can use Outline Budgeter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Outline Budgeter AI skill free?

It is published on GitHub by WILLOSCAR. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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