SkillAgentSearch skills...

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-loop

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Category

Automation

Supported Platforms

Universal

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.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

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.

SkillScoreStarsUpdatedFormat
wiki-research-loop (this skill)by rohitg00902.9k5d agoSKILL.md
Agent-Reachby Panniantong10086.1k14d agoCLAUDE.md
rufloby ruvnet10073.5ktodayCLAUDE.md
Scraplingby D4Vinci10084.5ktodayMCP Server
algorithmic-artby anthropics100177.9k7d agoSKILL.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.

name: 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_usd exceeded (loop tracks per-fetcher cost estimate)
  • max_pages_per_run written
  • max_depth reached on every active branch
  • 3 consecutive pages add < 5 % new claims (convergence)
  • File ~/.pro-workflow/STOP exists (operator kill-switch)
  • wiki.config.md auto_research.enabled: false
  • Wiki private: true AND 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 available WebFetch tool 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)

Related Skills

View on GitHub
GitHub Stars2.9k
CategoryAutomation
Updated5d ago
Forks289

Languages

JavaScript

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium