wiki-research-loop
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.
Install / Use
npx skills add rohitg00/pro-workflow --skill wiki-research-loopInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of wiki-research-loop
wiki-research-loop scores 90/100 on our quality scale, 884th of 2,250 Automation skills we index (top 40%).
Its SKILL.md is 5.8 KB long, well organised into 15 sections with 6 code examples: a solid amount of guidance for an agent.
With 2,876 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so wiki-research-loop is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
wiki-research-loop compared with similar skills
All 4 of these similar skills score higher than wiki-research-loop; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| wiki-research-loop (this skill)by rohitg00 | 90 | 2.9k | 5d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.1k | 14d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.5k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 84.5k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 7d ago | SKILL.md |
Frequently asked questions
- How do I install wiki-research-loop?
- Run
npx skills add rohitg00/pro-workflow --skill wiki-research-loop. The install tabs above show the steps for each supported agent. - Which AI agents does wiki-research-loop work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is wiki-research-loop safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is wiki-research-loop still maintained?
- The repository was last updated 5 days ago, so wiki-research-loop is actively maintained.
Skill content
View source on GitHubname: wiki-research-loop description: 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. user-invocable: true
Wiki Research Loop
Driver that turns a wiki into an auto-grown knowledge base. Layers on top of wiki-builder and wiki-query.
Loop semantics
seed-queue (pending) → next-seed
→ fetch sources via plugins (web | arxiv | github)
→ extract claims
→ dedupe vs index (FTS5; later vector via 3.3.2)
→ compile new page or amend existing
→ upsert page (auto-FTS-index)
→ enqueue follow-up seeds (max-depth gate)
→ mark seed done
→ if budget OR convergence OR kill-switch → halt
Halt conditions (any one trips)
budget_usdexceeded (loop tracks per-fetcher cost estimate)max_pages_per_runwrittenmax_depthreached on every active branch- 3 consecutive pages add < 5 % new claims (convergence)
- File
~/.pro-workflow/STOPexists (operator kill-switch) wiki.config.mdauto_research.enabled: false- Wiki
private: trueAND any non-local fetcher selected
Commands
In a plugin session, call the providers MCP server's run_provider_task tool with task: "research" and the runner arguments below, for example args: ["run", "agent-memory", "--fetchers", "github"]. Its optional GitHub token comes from the plugin configuration dialog. The direct CLI uses PRO_WORKFLOW_GITHUB_TOKEN when explicitly supplied. Never retrieve tokens from existing machine credentials.
node $SKILL_ROOT/scripts/research-loop.js run <slug> [--max-pages N] [--max-depth N] [--budget-usd 0.50] [--fetchers web,arxiv,github]
node $SKILL_ROOT/scripts/research-loop.js seed <slug> "<query>" [--depth 0] [--parent-id N]
node $SKILL_ROOT/scripts/research-loop.js seeds <slug> [--status pending|active|done|failed]
node $SKILL_ROOT/scripts/research-loop.js cancel <slug>
node $SKILL_ROOT/scripts/research-loop.js status
CLI flags override wiki.config.md for one run only.
Source fetchers
Pluggable. Each lives at scripts/source-fetchers/<name>.js. Interface:
module.exports = {
name: 'web',
match: (q) => true, // is this fetcher useful?
estimateCost: (q) => ({ usd: 0, tokens: 0 }),
fetch: async (q, opts) => [ // returns RawDoc[]
{ url, title, content, fetched_at }
]
};
Built-in:
web.js— Fetches via the user's availableWebFetchtool through a stdin/stdout shim. Treats result as plain text/markdown.arxiv.js—https://export.arxiv.org/api/query(free, public, no key). Returns abstract + metadata.github.js—https://api.github.com/search/repositories+ README pull (uses the explicitly configured GitHub token, otherwise unauthenticated rate limit).
Standalone CLI runs load custom fetchers from ~/.pro-workflow/fetchers/<name>.js. The plugin MCP server uses only bundled fetchers so configured tokens are not handed to user-supplied modules.
Budget enforcement
Pre-iteration: sum estimateCost across selected fetchers. If projected cumulative cost would exceed budget_usd, halt.
Post-iteration: track tokens used by the LLM compile step (Anthropic/OpenAI passthrough). Hard-kill on overrun.
Per-fetcher overrides via env: WIKI_LOOP_BUDGET_USD, WIKI_LOOP_MAX_PAGES, WIKI_LOOP_MAX_DEPTH.
Seed queue
SQLite-backed via wiki_seeds table:
| field | meaning |
|-------|---------|
| query | natural-language seed |
| status | pending → active → done|failed |
| parent_id | seed that produced this one |
| depth | BFS depth from root |
Loop pops by (depth ASC, created_at ASC) so it explores breadth-first.
Convergence detection
After each compiled page, compute Jaccard overlap of claim-text tokens vs the prior 3 pages. If < 5 % novel content for 3 consecutive pages, halt and report converged.
Kill switch
touch ~/.pro-workflow/STOP
Loop checks per-iteration and halts gracefully. Remove file to resume next run.
Privacy guard
If wiki.config.md has private: true, the loop refuses any non-local fetcher and emits a warning. Only raw/ ingestion via manual seeds is allowed.
Reactive trigger (Phase 3.3.4)
scripts/file-watcher.js watches wiki/<slug>/wiki/**/*.md. On user-edited claim, enqueues a verification seed (verify: <claim>) at depth 0. Wired through pro-workflow's file-watcher.js hook.
Cron tick (Phase 3.3.4)
scripts/research-tick.js is launchable from any cron-style runner. Picks the oldest opted-in wiki with pending seeds and runs a single iteration. Hook event: pro-workflow:research-tick.
Output
Each run writes:
<wiki-root>/logs/research-<UTC-timestamp>.md # human-readable run log
<wiki-root>/derived/run-<UTC-timestamp>.json # structured stats
Run log lines:
[2026-05-08T10:42Z] seed-3 (depth=1) "memory consolidation in agents"
fetcher=arxiv hits=3
fetcher=web hits=2
compiled wiki/concepts/memory-consolidation.md (claims=7, novel=4)
enqueued 2 follow-up seeds
cost so far: $0.04 / $0.50
Integration with wiki-query
Every compiled page goes through wiki-cli.js page so FTS5 stays consistent. The dedupe step calls searchWiki with the candidate claim text to find near-duplicates.
Status (Phase 3.3.1)
Ships: loop driver, seed queue, web/arxiv/github fetchers, budget caps, convergence detector, kill-switch, manual run command.
Defers:
- Vector dedupe (Phase 3.3.2 via sqlite-vec)
- LLM-judged claim novelty (current = Jaccard token overlap)
- Cron + reactive (Phase 3.3.4)
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
