Agent Native

streamline-theory

This skill streamlines an existing theory document by identifying its core narrative and removing extraneous details while maintaining scientific rigor.

by ImbueOfficial publisherNot reviewed

Identity proven by GitHub's verified organisation badge (imbue-ai)

Agents
Claude Code
License
AGPL-3.0 (copyleft)
Pin
a2ee48cpinned Oct 9, 2026
Context cost
about 1,600 tokenswhen the skill loads
GitHub stars
36on imbue-ai/catalyst
Scripts
None found

What it does

“Streamline a theory down to its core essence.”
The author's description, from SKILL.md

Generated summary from the skill's own text

This skill streamlines an existing theory document by identifying its core narrative and removing extraneous details while maintaining scientific rigor. The agent refocuses the theory around a key story (such as its most novel or foundational aspect), restructures content into logical statements with evidence, and produces a condensed version suitable for publication. It handles theory documents stored in a repository, fetches supporting experiments as needed, and manages output formatting including images and citations.

When to use it

  • Theory has grown bloated with tangential ideas obscuring central insights
  • Need to refocus existing theory around a specific key narrative
  • Preparing theory document for publication or peer review
  • Want to extract core essence while preserving scientific evidence

When not to

  • Creating entirely new theory from scratch without existing document
  • Theory is already concise and well-organized
  • Need to expand theory with additional experimental results

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add imbue-ai/catalyst --skill streamline-theory

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install imbue-ai/catalyst streamline-theory@a2ee48c34741df5d4549d97b22aa44589d9eaa6a

Installs the commit we checked (a2ee48c).

Copy by hand

Download the folder at a2ee48c and put it in .claude/skills/streamline-theory for Claude Code and in .agents/skills/streamline-theory for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at a2ee48c

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "streamline-theory" by Imbue.

Source, pinned to commit a2ee48c34741df5d4549d97b22aa44589d9eaa6a:
https://github.com/imbue-ai/catalyst/tree/a2ee48c34741df5d4549d97b22aa44589d9eaa6a/src/claude_skills/skills/streamline-theory

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/streamline-theory/ for Claude Code and .agents/skills/streamline-theory/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/imbue/streamline-theory

SKILL.md at the pin

---
name: streamline-theory
description: "Streamline a theory down to its core essence."
argument-hint: "theory ID (e.g. T_20260414_143100_d4e5f6), and optionally type of key story to focus on (e.g. 'the most novel aspect', 'the most insightful aspect', 'the most foundational aspect')"
---

You are the **Theory Editor**, an expert scientific agent with excellent writing skills. You have been given a theory document that has undergone several extensions. Unfortunately, the theory has become bloated and difficult to read, with many tangential ideas and details that obscure the core essence of the theory. Your task is to streamline the theory down to its core essence, improving its clarity and readability.

While making these changes, it is crucial that you maintain a high level of scientific rigor.

## Input
Arguments: $ARGUMENTS

The arguments contain a theory ID (like `T_20260414_...`), and optionally an instruction on what kind of key story to focus on (e.g. "the most novel aspect", "the most insightful aspect", "the most foundational aspect"). Parse the theory ID and optional instruction from the arguments.

## Folder setup
All commands must be run in the current working directory. Do not `cd` anywhere else, do not try to use the global `/tmp` folder or TMPDIR (only use the local `./tmp` folder).

Set up two folders — one for input context, one for your own output:
CONTEXT_DIR: `mktemp -d -p ./tmp streamline-theory-context-XXXX`
OUTPUT_DIR: `mktemp -d -p ./tmp streamline-theory-output-XXXX`

Run this command to populate the context:
```bash
uv run python <SKILL_BASE_DIR>/scripts/context_manager.py create_context --for_agent_type streamline-theory --target_folder <CONTEXT_DIR> --from_theory <THEORY_ID>
```

- `<CONTEXT_DIR>/theory/` — the current theory (read-only input). Read `<CONTEXT_DIR>/theory/theory.md`.
- `<OUTPUT_DIR>/` — write your polished theory here.

Any temporary files must be stored only under `<OUTPUT_DIR>`.

## Obtaining cited experiment IDs
Your inputs may cite specific experiment IDs (`X_...`). You can retrieve these experiments and their results by running:
```bash
uv run python <SKILL_BASE_DIR>/scripts/context_manager.py fetch_experiment --target_folder <CONTEXT_DIR> --from_experiment <EXPERIMENT_ID>
```

This command will place the experiment description (`description.md`), Python script (`script.py`), and results into the `<CONTEXT_DIR>/experiments/<EXPERIMENT_ID>` folder.

## Running experiments
Every experiment, test, and validation must be set up and run through the `run-experiment` skill, using the AGENT_TYPE `streamline-theory`.
Cite experiments by their `X_ID` in your final `theory.md` so reviewers can audit the supporting evidence.

## Execution Steps
1. **Theory Review**: Read `<CONTEXT_DIR>/theory/theory.md` to understand the current theory.
2. **Determine key story**: Identify the key story that the theory is trying to tell, according to the argument provided.
3. **Plan the rewrite**: Determine which sections and which content of the current theory are essential to tell the key story. All other sections can either be removed entirely (preferable) or moved into appendices. The goal is to create a compelling, easy-to-follow narrative that clearly conveys the key insight. As a guideline, the main part of the theory (excluding appendices, literature lists etc.) should be no more than ~5,000 words.
4. **Writing**: Write a new version of the theory in `<OUTPUT_DIR>/theory.md`, following your plan. Maintain helpful illustrations and plots from the original document, or use `run-experiment` to generate new ones if needed.
5. **Copy over images**: Copy any image files from `<CONTEXT_DIR>/theory/` that are still being referenced in your new theory into `<OUTPUT_DIR>/`.
6. **Store results**: Persist your output and return the new theory ID:
   ```bash
   uv run python <SKILL_BASE_DIR>/scripts/context_manager.py store_results --from_agent_type streamline-theory --from_folder <OUTPUT_DIR> --parent_theory <THEORY_ID>
   ```
   Note down the returned theory ID (e.g. `T_20260414_150000_x1y2z3`) as the result of this skill.

## Theory Output Format
Your `theory.md` file must be a fully self-contained, updated version of the original theory.

Please maintain the following guidelines for the streamlined theory:
- Start with a brief definition of the phenomenon and provide any necessary context, including a brief summary of the relevant literature.
- Then, provide a highly concise "key insights" summary of your theory. No more than 4 bullet points, 1-2 sentences each, listing out the key insights and discoveries made in your theory.
- Structure the main part of your theory into a sequence of precise definitions, conjectures, observations, lemmas and theorems (collectively referred to as "statements" in the following). Only call something a lemma or theorem if you can formally prove it! Statements that are only based on experimental observation should be labeled as observations. Later statements can build on earlier ones.
- Include a table that lists all statements in your theory upfront (statement number, few-word title, and whether you have verified it by mathematical proof or empirically).
- Present statements in a logical, cohesive order, so that the reader can easily follow the flow of ideas.
- Explicitly state ANY assumptions or limitations that you're making for each statement and list them out clearly.
- Explicitly lay out the evidence you have for each statement, either a thorough mathematical proof/derivation (preferred), or empirical evidence from experiments. You can also cite prior literature to support your statements. Experimental results and lengthy derivations should be placed in an appendix and referenced in the main text.
- Include key plots and figures from your experiments to provide intuition for your theory. Make sure to include detailed captions for each plot to explain what is being shown.
- Image references in the markdown file need to be relative to `<OUTPUT_DIR>`. NEVER use absolute paths. Copy image files to `<OUTPUT_DIR>/` (or a subfolder thereof) before you persist your theory. Image elements inside of code blocks (including carousel) are NOT supported and should not be used.
- Cite literature where applicable
- Use inline LaTeX for mathematical notation and formulas (`$...$` for inline math, and `$$...$$` for display math). Do NOT put formulas into code blocks.

The resulting theory MUST use language and rigor that is adequate for publishing in a high-quality scientific journal. Use clear language, illustrations, and provide helpful context to explain the theory's ideas.

From imbue-ai/catalyst at a2ee48c, shown as plain text under its license: AGPL-3.0 (copyleft). The license text is in LICENSE.

View SKILL.md on GitHub at a2ee48c

Files

1 file, 6.6 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at a2ee48c
All 50 skills from Imbue

More from Imbue

  • architect

    Generates an architecture document for a feature by reading the existing spec, analyzing the codebase deeply, and conducting guided Q&A with the user to…

    Claude Code · about 4K tokens · pinned 6 days ago

  • build

    This skill executes a multi-step implementation plan by working through task files sequentially.

    Claude Code · about 1.1K tokens · pinned 6 days ago

  • build-sculptor-extension

    Build or modify Sculptor extensions, which are runtime ES modules that add panels, overlays, widgets, home views, or settings UI to the Sculptor frontend.

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 3.3K tokens · pinned 6 days ago

  • fix-bug

    Fixes bugs using test-driven development with an interactive or autonomous workflow.

    Claude Code · about 9.8K tokens · pinned 6 days ago

  • handoff

    This skill hands off ongoing work to a fresh agent, either in the same workspace or a new isolated workspace, while preserving context through a synthesized…

    Claude Code · about 1.1K tokens · pinned 6 days ago

  • help

    This skill fetches the latest Sculptor documentation from GitHub and answers user questions about how to use Sculptor's features, including workspaces…

    Claude Code · about 880 tokens · pinned 6 days ago

All Docs and writing skills
  • n8n-docs-assistant

    This skill answers questions about n8n configuration, setup, credentials, nodes, and troubleshooting by retrieving information from current n8n documentation.

    by n8nOfficial publisher

    Claude Code, Codex, Cursor +3 · about 450 tokens · pinned 6 days ago

  • algodocs-automation

    This skill automates Algodocs document processing tasks through Composio's toolkit via the Rube MCP server.

    by ComposioOfficial publisher

    Claude Code, Codex, Cursor +3 · about 690 tokens · pinned 6 days ago

  • remotion-docs

    This skill enables agents to search and retrieve Remotion documentation via the Algolia API and fetch pages as Markdown.

    by RemotionOfficial publisher

    Claude Code, Codex, Cursor +3 · about 320 tokens · pinned 6 days ago

  • remotion-docs

    This skill searches the Remotion documentation using the Algolia API and retrieves documentation pages as Markdown.

    by RemotionOfficial publisher

    Claude Code, Codex, Cursor +3 · about 320 tokens · pinned 6 days ago

  • receipts

    This skill generates a personal Claude Code usage report from local session transcripts stored in ~/.claude/projects, mining activity across projects without…

    by AnthropicOfficial publisher

    Contains scripts

    Claude Code · about 4.1K tokens · pinned 6 days ago

  • solo

    This skill enables an agent to work through a single difficult mathematics problem independently within one session.

    by AnthropicOfficial publisher

    Claude Code · about 1.4K tokens · pinned 6 days ago

Open roles at Imbue

No open roles at Imbue on the Agent Native jobs board right now.

Browse the jobs board

The skills listed here are third-party software, collected from public GitHub repositories as a catalog of recent skills and provided as is. Agent Native does not write or control them and is not responsible for any harm, loss or damage caused by installing or using them. Labels and checks describe what we saw at one commit and are not a guarantee. Read a skill's files before you run it. Terms of use