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Agent skill

Wiki Research Loop

by rohitg00 in rohitg00/pro-workflow

Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub).

No licenceAuto-check passedKnowledge Management

Install Wiki Research Loop

skills CLI
$ npx skills add rohitg00/pro-workflow --skill wiki-research-loop -a claude-code

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

GitHub CLI
$ gh skill install rohitg00/pro-workflow wiki-research-loop --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/rohitg00/pro-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/wiki-research-loop .claude/skills/wiki-research-loop && 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
wiki-research-loop
GitHub stars
2.9k
Token cost
~1.5k tokens
SKILL.md length
463 words
Files
5 (incl. scripts)
Skills in repo
41
Repo updated
First seen
Licence
None found

At a glance

Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub).

  • The user says research <topic
  • SKILL.md covers Loop semantics, Halt conditions (any one trips), Commands and Source fetchers, plus 10 more sections
  • Runs JavaScript scripts from its folder; calls node; reaches export.arxiv.org and api.github.com; needs PRO_WORKFLOW_GITHUB_TOKEN
  • Grow the <slug wiki

What it does

Wiki Research Loop is an agent skill from rohitg00/pro-workflow. Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Each iteration pops a seed from the queue, fetches sources, drafts a wiki page, dedupes claims against existing pages, enqueues follow-up seeds. Halts on budget cap, depth cap, or convergence. Use when the user says "research <topic", "grow the <slug wiki", "auto-research", or wants a knowledge base that builds itself overnight.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `scripts/research-loop.js`, `scripts/source-fetchers/arxiv.js` and `scripts/source-fetchers/github.js`).

It sits in Knowledge Management, covering LLM wikis, Academic paper search and Knowledge bases. It works with GitHub and arXiv. The repository describes itself as: Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested…

When your agent uses it

  • The user says research <topic
  • Grow the <slug wiki
  • Wants a knowledge base that builds itself overnight

Example prompts

  • “research <topic”
  • “grow the <slug wiki”
  • “auto-research”
  • “/wiki-research-loop”

Requirements

  • Node.js
  • A credential in PRO_WORKFLOW_GITHUB_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit 86d5f27. 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

    Ships 4 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • node

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • export.arxiv.org
    • api.github.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • PRO_WORKFLOW_GITHUB_TOKEN

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

Context cost

Wiki Research Loop loads about 1.5k tokens when it runs. Until then it costs about 120 tokens; SKILL.md has 463 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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); the scripts in this folder are not scanned.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 463 words (~1,482 tokens).

“Driver that turns a wiki into an auto-grown knowledge base. Layers on top of wiki-builder and wiki-query.”

— opening of SKILL.md by rohitg00
name
wiki-research-loop
user-invocable
true

Read the full SKILL.md on GitHub

Files

SKILL.md and 4 other files (scripts) in skills/wiki-research-loop of rohitg00/pro-workflow.

  • SKILL.md
  • scripts/research-loop.js
  • scripts/source-fetchers/arxiv.js
  • scripts/source-fetchers/github.js
  • scripts/source-fetchers/web.js

Open the folder on GitHubat commit 86d5f27

Compare with similar skills

Wiki Research Loop 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.

Wiki Research Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Wiki Research Loop this skillrohitg00/pro-workflow2.9k—~1.5kAutomated safety check: PassNone
Paper LensYSQ-boop/paper-lens101—~1.3kAutomated safety check: PassApache-2.0
LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything86k1 repos~1.5kAutomated safety check: PassMIT
LLM Wikilewislulu/llm-wiki-skill655—~3.7kAutomated safety check: PassNone
Rival Search MCPdamionrashford/RivalSearchMCP1321 repos~796Automated safety check: PassMIT
Arkon Editnduckmink/arkon1.5k—~1.6kAutomated safety check: PassCustom licence

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Works with

Categories

Questions about Wiki Research Loop

What does Wiki Research Loop do?

Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Wiki Research Loop is an agent skill from rohitg00/pro-workflow. Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub).

When should I use Wiki Research Loop?

Wiki Research Loop fits situations like: the user says research <topic; grow the <slug wiki; wants a knowledge base that builds itself overnight.

How do I install Wiki Research Loop in Claude Code?

Run `npx skills add rohitg00/pro-workflow --skill wiki-research-loop -a claude-code`. Or copy the skill folder (skills/wiki-research-loop in rohitg00/pro-workflow) into .claude/skills/wiki-research-loop in your project. Claude Code loads it when a task matches its description.

How do I install Wiki Research Loop in Codex?

Run `npx skills add rohitg00/pro-workflow --skill wiki-research-loop -a codex`. Or copy the skill folder (skills/wiki-research-loop in rohitg00/pro-workflow) into .agents/skills/wiki-research-loop in your project. Codex loads it when a task matches its description.

Can I use Wiki Research Loop 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 rohitg00/pro-workflow --skill wiki-research-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wiki-research-loop, .gemini/skills/wiki-research-loop, .github/skills/wiki-research-loop and .opencode/skills/wiki-research-loop in your project.

What does Wiki Research Loop need to run?

Going by SKILL.md and its folder, Wiki Research Loop needs JavaScript for the scripts in its folder, the command-line tools its instructions call (node) and credentials named PRO_WORKFLOW_GITHUB_TOKEN. Our summary lists: Node.js; A credential in PRO_WORKFLOW_GITHUB_TOKEN.

Does Wiki Research Loop access the network?

SKILL.md names 2 domains. In commands or code: export.arxiv.org and api.github.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Wiki Research Loop 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Wiki Research Loop use?

No licence was found for Wiki Research Loop or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Wiki Research Loop use?

About 1.5k tokens (SKILL.md is roughly 5.9k 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 Wiki Research Loop?

Skills that share tags, products or a category with Wiki Research Loop: Paper Lens (YSQ-boop/paper-lens, 101 stars), LLM Wiki Knowledge Graph (Egonex-AI/Understand-Anything, 86k stars), LLM Wiki (lewislulu/llm-wiki-skill, 655 stars) and Rival Search MCP (damionrashford/RivalSearchMCP, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wiki Research Loop?

rohitg00 (a GitHub user) maintains it in rohitg00/pro-workflow, which has 2,906 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on September 29, 2026.

Source: rohitg00/pro-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.