Autoresearch Finalize logo

Autoresearch Finalize

Organization
SpartanLabsXyz
autoresearch-finalize

Finalize an autoresearch session into clean, reviewable branches. Use when asked to "finalize autoresearch", "clean up experiments", or "prepare autoresearch for review".

Overview

PublisherSpartanLabsXyz
Repositorysimmer-sdk
Skill nameautoresearch-finalize
Stars
56
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • 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 SpartanLabsXyz on GitHub. Read the source before you install it.

Installation

Install the Autoresearch Finalize 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/SpartanLabsXyz/simmer-sdk/tree/main/mcp/skills/autoresearch-finalize
  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/SpartanLabsXyz/simmer-sdk.git /tmp/simmer-sdk
mkdir -p .claude/skills
cp -r /tmp/simmer-sdk/mcp/skills/autoresearch-finalize .claude/skills/autoresearch-finalize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Autoresearch Finalize 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 Autoresearch Finalize 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 Autoresearch Finalize 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.

Finalize Autoresearch

Turn a noisy autoresearch branch into clean, independent branches — one per logical change, each starting from the merge-base.

Step 1 — Analyze and propose groups

  1. Read autoresearch.jsonl. Filter to kept experiments only.
  2. Read autoresearch.md for context.
  3. Expand all short commit hashes to full hashes: git rev-parse <short_hash>
  4. Get the merge-base: git merge-base HEAD main
  5. For each kept commit, get the diff stat.
  6. Group kept commits into logical changesets:
    • Preserve application order. Group N comes before Group N+1.
    • No two groups may touch the same file. Each branch is applied to merge-base independently — overlapping files would conflict. If two groups touch the same file, merge them into one group.
    • Watch for cross-file dependencies. If group 1 adds an API in api.js and group 2 calls it in parser.js, group 2's branch won't work in isolation. Flag dependencies.
    • Keep each group small and focused. One idea, one theme per group.

Present the proposed grouping:

Proposed branches (each from merge-base, independent):

1. **<description>** (commits abc1234, def5678)
   Files: file1.py, file2.py
   Metric: 42.3 → 38.1 (-9.9%)

2. **<description>** (commits ghi9012)
   Files: config.json
   Metric: 38.1 → 31.7 (-16.8%)

Wait for approval before proceeding.

Step 2 — Create branches

For each approved group:

bash
BASE=$(git merge-base HEAD main)
git checkout -b autoresearch/final/<group-name> $BASE
git cherry-pick <commit1> <commit2> ...

If cherry-pick conflicts, resolve by taking the experiment's version (the whole point is to preserve the improvement).

Step 3 — Verify each branch

For each branch:

  1. Run the skill command to verify it still works
  2. Check that the metric improvement holds
  3. If it doesn't, flag it — the improvement may have depended on another group's changes

Step 4 — Report

Finalized branches:
1. autoresearch/final/<name> — <metric improvement>, ready to merge
2. autoresearch/final/<name> — <metric improvement>, depends on branch 1

The user can now review and merge each branch independently (or together if there are dependencies).

Frequently asked questions

What does the Autoresearch Finalize AI skill do?

Finalize an autoresearch session into clean, reviewable branches. Use when asked to "finalize autoresearch", "clean up experiments", or "prepare autoresearch for review".

Why use Autoresearch Finalize on TypingMind?

Because you install it once and use it with any model. Autoresearch Finalize 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 Autoresearch Finalize in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpartanLabsXyz/simmer-sdk/tree/main/mcp/skills/autoresearch-finalize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Autoresearch Finalize?

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 Autoresearch Finalize?

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

Is the Autoresearch Finalize AI skill free?

Yes. It is published on GitHub by SpartanLabsXyz under the MIT license. 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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