Agent skill

Research Thread

by nubjs in nubjs/nub

A skill your agent uses when the deliverable is a FACT — not code, not a design, not a gap catalog.

MITAuto-check passedLegal & Compliance

Install Research Thread

skills CLI
$ npx skills add nubjs/nub --skill research-thread -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nubjs/nub research-thread --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nubjs/nub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/research-thread .claude/skills/research-thread && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research-thread
GitHub stars
4.4k
Token cost
~2.2k tokens
SKILL.md length
1,262 words
Files
1
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the deliverable is a FACT — not code, not a design, not a gap catalog.

  • Works in 6 steps: Search before theorizing. Reach for web… → Read the source locally, never one file… → Read the resolution, not the issue body.… → …
  • The deliverable is a FACT — not code
  • SKILL.md covers Scope gate — is this a…, The method, The publication gate — wiki/… and The write-up, plus 2 more sections
  • Calls git

What it does

Research Thread is an agent skill from nubjs/nub. Use when the deliverable is a FACT — not code, not a design, not a gap catalog. A prior-art survey, "how has X already been solved", "what did they try and abandon", a long empirical sweep, or any non-trivial question whose answer will be cited for months. Produces a living write-up at wiki/research/<topic.md. Auto-triggers on "research this", "prior art", "survey", "find out how X works", "what's the state of the art", "dig into whether".

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Legal & Compliance, covering Intellectual property and Literature review. The repository describes itself as: The fast all-in-one Node.js toolkit. The licence is MIT.

When your agent uses it

  • The deliverable is a FACT — not code
  • Not a gap catalog
  • Find out how X works
  • Whats the state of the art

Example prompts

  • “how has X already been solved”
  • “what did they try and abandon”
  • “research this”
  • “/research-thread”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Search before theorizing. Reach for web search eagerly and repeatedly; one search either hands you the answer or tells you you are first…
  2. Read the source locally, never one file at a time over HTTP. git clone --depth 1 .repos/ (gitignored), then grep and read a whole…
  3. Read the resolution, not the issue body. A body says what someone wanted; the maintainer comments and the reason it closed say what is…
  4. Hunt what was TRIED AND ABANDONED. It lives in issue threads, release notes, and RFCs, and it is invisible in the code. A knob that shrank…
  5. Probe rather than reason. A throwaway fixture, a standalone rustc file, or a differential run against the real tool answers "what does it…
  6. Check whether their constraint is YOUR constraint. Another project's rejected approach may have been rejected for a reason nub does not…

What it can do on your machine

Read from SKILL.md and the folder at commit 568e73a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Research Thread loads about 2.2k tokens when it runs. Until then it costs about 116 tokens; SKILL.md has 1,262 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from nubjs/nub at commit 568e73a, republished under its MIT licence (© nubjs). 1,262 words, ~2,162 tokens.

Download SKILL.mdSave it as .claude/skills/research-thread/SKILL.md (or your agent's skills folder).
name
research-thread
description
Use when the deliverable is a FACT — not code, not a design, not a gap catalog. A prior-art survey, "how has X already been solved", "what did they try and abandon", a long empirical sweep, or any non-trivial question whose answer will be cited for months. Produces a living write-up at `wiki/research/<topic>.md`. Auto-triggers on "research this", "prior art", "survey", "find out how X works", "what's the state of the art", "dig into whether".
metadata.internal
true

Research threads

A research thread is one of the four thread profiles, alongside the implementation thread (build-the-decided-thing, the implementation-thread skill), the plan thread (settle-the-approach, the plan-thread skill), and the audit thread (verify-parity, the audit-thread skill). Its deliverable is a fact, written down — wiki/research/<topic>.md. It is the thread you open when what is true is the open question.

Scope gate — is this a research THREAD?

Most questions are not. The alternative to guessing is not only "dispatch a researcher" — it is "go read it". A few greps and the file they land in answer nearly every question about this codebase, first-hand and faster than a second-hand claim you must re-verify. AGENTS.md's prior-art reflex — spend the first few minutes finding out how a thing has already been solved — fires on EVERY non-trivial work item, and that scan is not a thread.

A research thread earns its own effort when the question needs breadth you cannot hold in one pass: a survey across several projects, independent sources that must be reconciled, a long empirical sweep, or a decision that will be cited for months. If the answer fits in a paragraph of your handoff, write the paragraph and skip the doc.

The method

The order is the point — each step is cheaper than the one after it, and each kills theories the next would otherwise have to disprove.

  1. Search before theorizing. Reach for web search eagerly and repeatedly; one search either hands you the answer or tells you you are first. When a dependency, runtime, or API surprises you, search its issue tracker, release notes, and the integrating projects' issues FIRST. A theory built from local evidence alone produces a confident, wrong story that survives until the next piece of evidence kills it.
  2. Read the source locally, never one file at a time over HTTP. git clone --depth 1 <repo> .repos/<name> (gitignored), then grep and read a whole consistent tree. Check what .repos/ already holds first — it carries 290 clones today, node/, bun/, pnpm/ and tsx/ among them. Never modify anything under .repos/.
  3. Read the resolution, not the issue body. A body says what someone wanted; the maintainer comments and the reason it closed say what is true. An "open feature request" is often a deliberate rejection with the rationale in the thread.
  4. Hunt what was TRIED AND ABANDONED. It lives in issue threads, release notes, and RFCs, and it is invisible in the code. A knob that shrank across releases, or a feature reverted one release after it shipped, tells you more than the current implementation does.
  5. Probe rather than reason. A throwaway fixture, a standalone rustc file, or a differential run against the real tool answers "what does it actually do" faster and more reliably than tracing source. Ground every claim in code or an experiment, never memory — and label UNVERIFIED anything you could not run.
  6. Check whether their constraint is YOUR constraint. Another project's rejected approach may have been rejected for a reason nub does not share, which can make an option they closed off correct here. A survey that only tells you what to copy is half-read.

Reversing a conclusion on new evidence is correct, not flip-flopping. State the current verdict, keep probing, and let evidence move you rather than defend the first answer.

The publication gate — wiki/ is TRACKED and PUBLIC

Read AGENTS.local.md → "What goes in the PUBLIC wiki/ vs the PRIVATE internal/" before writing a line. Default to internal/: a wrong exclusion costs a later copy, a wrong inclusion is permanent. Four things never go public — unimplemented roadmap, the narrative of a dead end pursued too long, competitor SCORECARDS (a factual technical statement about another tool is fine and makes the mechanism legible), and any deliberation about how benchmark results were framed.

A doc that is mostly publishable with one bad section gets the section cut, not the doc dropped — then re-read the remainder for framing that only made sense next to what you removed. Separately, even a perfectly publishable doc about an UNSHIPPED feature stays on that feature's branch until it ships.

Show full SKILL.md (580 more words)Show less

The write-up

wiki/research/<topic>.md, kebab-case slug, never the repo root. Research docs do not carry the YAML front matter that wiki/runtime/ and wiki/commands/ use.

The shape the existing 70 docs converge on:

PartConvention
Title# <topic> — the question or the finding, not "Research doc for X"
Orientation blockDirectly under the title: status + date, the QUESTION it answers, the headline answer, and links to sibling docs
## TL;DRFindings as a short numbered list — 40 of 70 docs. Write one whenever the body runs long
BodyThe evidence, every load-bearing claim carrying its citation or its reproduction
## SourcesThe external links — 31 of 70
## ChangelogMandatory — 68 of 70

Research docs are living documents. Edit in place: the body always reads as current best understanding, with no history inside it. Every change appends - YYYY-MM-DD — <what changed and why> under ## Changelog; a new doc's first entry is - YYYY-MM-DD — Initial write-up. A major reversal gets a leading **REVERSAL:** marker. Never blow away a prior conclusion silently — say that the doc previously said X, now says Y, and what evidence moved it. When two docs overlap, merge into one canonical, record the merge in the survivor's changelog, and note the supersession at the top of the absorbed doc before deleting it.

Boundaries with the other profiles

The open questionThe profile
What is true?research → wiki/research/<topic>.md
How should we do it?plan → a settled design (plan-thread)
Where do we diverge from a reference?audit → a verified gap catalog, also under wiki/research/ (audit-thread)
Build the decided thingimplementation → a held, green PR (implementation-thread)

An audit is the special case of research whose question is parity — it inherits this method and adds five hard gates against false positives. Use audit-thread for it, not this skill. A plan thread that needs a fact to decide spins a research effort, folds the result back, and keeps deciding: the plan owns the decision, the research owns the fact.

A research thread does not land code. But a clear bug with a clear fix found along the way gets run down, not parked under "still open" — the context that found it is the cheapest context that will ever exist for it. That fix is an implementation thread and is held to the implementation gates: reproduce it, prove the fix with a differential, sweep fixtures against a built binary, read the diff. "I chased it and it dissolved" is a first-class successful outcome and usually takes minutes.

Mechanics

  • Terminal state. The thread ends when the doc is written and committed. That artifact outlives the thread, which is why a research thread finishes cleanly where a pre-fix investigation cannot.
  • Landing. wiki/ is markdown, so it commits direct to main with no PR. From the shared tree: sync first (git fetch origin && git merge --ff-only origin/main), commit path-scoped (git commit -- wiki/research/<topic>.md) so a sibling's WIP stays out, push, and read the push's exit code.
  • Tiering. Synthesis and the verdict are Opus at high+ effort. A cheap tier may harvest breadth — a link sweep, a mechanical grep across a reference checkout — but every harvested item is re-verified before it enters the doc. A sub-agent's load-bearing claim is a lead, not a fact.
  • Dispatch. A fresh-context sub-agent inherits neither the survey reflex nor the publication gate, and a child that does not know wiki/ is public will write roadmap into it. Put both in the prompt. If you are yourself a dispatched sub-agent, the repo-wide depth cap in AGENTS.local.md applies: run the method inline and return.

© nubjs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/research-thread of nubjs/nub.

Open the folder on GitHubat commit 568e73a

Compare with similar skills

Research Thread next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research Thread compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Thread this skillnubjs/nub4.4k—~2.2kAutomated safety check: PassMIT
Sciatlas Idea Groundingzjunlp/SciAtlas160—~1.1kAutomated safety check: PassMIT
Mechanical Engineering Researchccplugins/awesome-claude-code-plugins967—~2.9kAutomated safety check: PassApache-2.0
Aminer MCP ResearchDrchronx/ai-agent-research-starter-kit134—~1.1kAutomated safety check: PassCustom licence
Paper to Chinese Patent DrafterYuan1z0825/nature-skills46k1 repos~1.1kAutomated safety check: PassApache-2.0
NeuroarxivUditAkhourii/neuroarxiv433—~3.1kAutomated safety check: PassMIT

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Questions about Research Thread

What does Research Thread do?

A skill your agent uses when the deliverable is a FACT — not code, not a design, not a gap catalog. Research Thread is an agent skill from nubjs/nub. Use when the deliverable is a FACT — not code, not a design, not a gap catalog.

When should I use Research Thread?

Research Thread fits situations like: the deliverable is a FACT — not code; not a gap catalog; find out how X works; whats the state of the art.

How do I install Research Thread in Claude Code?

Run `npx skills add nubjs/nub --skill research-thread -a claude-code`. Or copy the skill folder (.claude/skills/research-thread in nubjs/nub) into .claude/skills/research-thread in your project. Claude Code loads it when a task matches its description.

How do I install Research Thread in Codex?

Run `npx skills add nubjs/nub --skill research-thread -a codex`. Or copy the skill folder (.claude/skills/research-thread in nubjs/nub) into .agents/skills/research-thread in your project. Codex loads it when a task matches its description.

Can I use Research Thread in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nubjs/nub --skill research-thread -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-thread, .gemini/skills/research-thread, .github/skills/research-thread and .opencode/skills/research-thread in your project.

What does Research Thread need to run?

Going by SKILL.md and its folder, Research Thread needs the command-line tools its instructions call (git).

Does Research Thread access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Research Thread safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Research Thread use?

Research Thread is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research Thread use?

About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Research Thread?

Skills that share tags, products or a category with Research Thread: Sciatlas Idea Grounding (zjunlp/SciAtlas, 160 stars), Mechanical Engineering Research (ccplugins/awesome-claude-code-plugins, 967 stars), Aminer MCP Research (Drchronx/ai-agent-research-starter-kit, 134 stars) and Paper to Chinese Patent Drafter (Yuan1z0825/nature-skills, 46k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Thread?

nubjs (a GitHub organization) maintains it in nubjs/nub, which has 4,370 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on October 7, 2026.

Source: nubjs/nub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.