Curate Research Trace logo

Curate Research Trace

OrganizationPopular
NeuroAIHub
curate-research-trace

Curate BrainPilot Trace Events into human-readable research Episodes, appropriately granular nodes, and direct depends_on relationships. Use when a report contains multiple settings, results, analyses, visualizations, findings, or conclusions; when Episode placement is unclear; or when deciding whether new evidence should create parallel/sequential nodes or update an existing node.

Overview

PublisherNeuroAIHub
RepositoryBrainPilot
Skill namecurate-research-trace
Stars
1.1K
Forks
74
Bundled files
2
LicenseAGPL-3.0
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Curate Research Trace 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/NeuroAIHub/BrainPilot/tree/main/packages/plugin-got/skills/curate-research-trace
  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/NeuroAIHub/BrainPilot.git /tmp/BrainPilot
mkdir -p .claude/skills
cp -r /tmp/BrainPilot/packages/plugin-got/skills/curate-research-trace .claude/skills/curate-research-trace
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Curate Research Trace 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 Curate Research Trace 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 Curate Research Trace 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.

Curate Research Trace

Turn reported research work into a compact derivation graph. Preserve scientific units rather than tool chronology.

Curate one Trace Event

  1. Inspect the active graph and reuse established Episode names and nodes.
  2. Extract units that can be inspected, cited, reproduced, or revoked independently.
  3. Assign every new unit to one research work-package Episode.
  4. Update an existing node when the report adds evidence to the same unit.
  5. Create parallel nodes when neither unit consumes the other.
  6. Create sequential dependencies only when the downstream unit consumes or requires the upstream unit.
  7. Add only direct parents. Never copy all transitive ancestors.

Select an Episode

Treat an Episode as one coherent research subquestion or experiment family, not as a time period or causal node.

  • Use Literature Review — <topic> for evidence synthesis around one question.
  • Use Method Design — <method> for reusable method or protocol decisions.
  • Use Environment & Reproducibility for shared runtime, dependency, hardware, and reproducibility setup.
  • Use Data Preparation — <dataset> for a dataset version, split, or material preprocessing pipeline.
  • Use Main Experiment — <question> for settings and outputs testing one main hypothesis.
  • Use Ablation — <factor> for all settings, results, comparisons, visualizations, and local findings in one ablation family.
  • Use Robustness — <factor> for sensitivity or robustness settings and outputs.
  • Use Cross-experiment Analysis — <question> only when an analysis consumes results from multiple experiment families.
  • Use Final Synthesis for conclusions that integrate findings across Episodes.

Use the session language. Prefer an existing exact Episode name. Do not create Episodes based only on Agent, tool, file, timestamp, or generic lifecycle phase. Dependencies may cross Episode boundaries.

Decide node boundaries

Create separate parallel nodes for:

  • distinct settings, conditions, or model variants;
  • the independently inspectable result of each setting;
  • analyses that answer different scientific questions;
  • findings that can independently hold or be refuted.

Create separate sequential nodes when one report contains independently reviewable configuration, result, analysis/visualization, finding, and conclusion units. Connect them only in the order in which outputs are actually consumed.

Update one existing node for:

  • seeds, folds, replicates, and repeated runs of the same setting and outcome;
  • additional evidence or a correction for the same result or finding;
  • multiple export formats of one result or figure;
  • immediate retries, formatting changes, and non-meaningful intermediates.

Keep multiple metrics in one result when they jointly describe one run. Split them only when they are reused independently or support independently falsifiable findings. Make a visualization a node only when it performs an independent analysis or carries an independently cited interpretation; otherwise attach it as an artifact.

Select direct parents

Apply this counterfactual: if the parent disappeared, would the child lose its evidence or need recomputation?

  • A result depends on the setting and concrete method/data/environment inputs it used.
  • An analysis depends on the result nodes it consumes.
  • A visualization depends on the result or analysis used to generate it.
  • A finding depends on its direct result or analysis evidence.
  • A conclusion depends on direct findings, not every underlying result.

Do not connect nodes because they are adjacent, share an Episode or author, use similar words, or occurred in order. Parallel settings share parents and do not depend on one another.

Read references/examples.md when a report mixes multiple research phases, contains an ablation, or leaves node boundaries unclear.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Curate Research Trace AI skill do?

Curate BrainPilot Trace Events into human-readable research Episodes, appropriately granular nodes, and direct depends_on relationships. Use when a report contains multiple settings, results, analyses, visualizations, findings, or conclusions; when Episode placement is unclear; or when deciding whether new evidence should create parallel/sequential nodes or update an existing node.

Why use Curate Research Trace on TypingMind?

Because you install it once and use it with any model. Curate Research Trace 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 Curate Research Trace in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/plugin-got/skills/curate-research-trace. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Curate Research Trace?

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 Curate Research Trace?

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

Is the Curate Research Trace AI skill free?

Yes. It is published on GitHub by NeuroAIHub under the AGPL-3.0 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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