不会让AI说任何无法引用的工具。
The tool that won't let AI say anything it can't cite

原始链接: https://github.com/grainulation/grainulator

## Grainulator:基于AI的Claude研究工具 Grainulator是为Claude设计的研究冲刺编排器,旨在通过结构化的、基于证据的过程提供可用于决策的简报。它作为一个Claude插件运行,无需任何第三方依赖,并提供交互式演示:[grainulator.app](https://grainulator.app)。 Grainulator的核心是“主张”——类型的知识单元(事实、估计、风险等),这些主张经过严格跟踪、对抗性挑战和置信度分级(从‘声明’到‘生产’)。一个7步编译程序通过检查类型覆盖率、证据强度和潜在偏差来确保质量,并在冲突解决前阻止输出。 用户通过自然语言提示与Grainulator交互,例如“研究X”或“挑战r003”。一个自主的子代理管理研究冲刺,决定采取哪些行动(研究、挑战、见证),直到达到高置信度水平。 Grainulator是更大的研究和知识管理工具生态系统中的一部分,该生态系统包含八个工具,全部基于Node.js构建,并设计为可灵活部署——从通过插件安装的个人使用,到团队范围乃至气隙环境。

一种新工具旨在通过强制人工智能仅陈述其能引用来源的主张来防止其“幻觉”。该工具(在GitHub上可用)发布在Hacker News上,引发了用户们不一的反应。 早期测试显示出局限性:它未能回答“洗车”问题,而是专注于诸如燃油消耗等相关数据,并且错误地识别了1932年《疤面》的导演。 评论者质疑其有效性,将其比作仅仅在提示中指示人工智能不要产生幻觉。一位用户指出其中的讽刺,注意到即使像Claude这样的模型也难以进行基本的身份识别,有时甚至会将*用户*作为来源引用。虽然该概念很有趣,但初步反馈表明该工具并非确保人工智能事实准确性的万无一失的解决方案。
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原文

Glitchy — the Grainulator mascot

version demo license CI Docs on DeepWiki

Research sprint orchestrator for Claude Code.

Ask a question, get a decision-ready brief. Every finding is tracked as a typed claim, adversarially challenged, confidence-graded, and compiled into self-contained output. Zero third-party dependencies.

grainulator.app — interactive demo with in-browser AI. No install needed.

Step 1 — Add the marketplace

claude plugin marketplace add https://github.com/grainulation/grainulator/blob/main/.claude-plugin/marketplace.json

Step 2 — Install the plugin

claude plugin install grainulator

Requirements: Node.js >= 20 (needed for MCP servers that run via npx).

Troubleshooting: SSH permission denied

If you see [email protected]: Permission denied (publickey), the plugin installer is trying SSH but you don't have SSH keys set up with GitHub. Fix with one command:

git config --global url."https://github.com/".insteadOf "[email protected]:"

Then retry claude plugin install grainulator. This tells git to use HTTPS instead of SSH for all GitHub repos.

Alternatively, clone manually:

git clone https://github.com/grainulation/grainulator.git ~/.claude/plugins/grainulator
claude plugin add ~/.claude/plugins/grainulator

For team-wide deployment, commit to your project's .claude/settings.json:

{
  "enabledPlugins": ["grainulator@grainulation-marketplace"]
}

Once installed, just talk to Claude:

  • "research how our auth system works" — runs a multi-pass research sprint
  • "challenge r003" — adversarial testing of a specific claim
  • "what are we missing?" — blind spot analysis
  • "write it up" — generates a compiled brief

No slash syntax required. The intent router detects what you want and runs the right workflow.

Claims are the unit of knowledge. Every finding from research, challenges, witnesses, and prototypes is stored as a typed claim in claims.json.

Claim type What it means
constraint Hard requirements, non-negotiable boundaries
factual Verifiable statements about the world
estimate Projections, approximations, ranges
risk Potential failure modes, concerns
recommendation Proposed courses of action
feedback Stakeholder input, opinions

Evidence tiers grade confidence: statedwebdocumentedtestedproduction.

The compiler runs 7 passes over your claims — type coverage, evidence strength, conflict detection, bias scan — and produces a confidence score. If there are unresolved conflicts, it blocks output until you resolve them.

Skill Description
/init Start a new research sprint
/research Multi-pass investigation with evidence gathering
/challenge Adversarial testing of a claim
/witness Corroborate a claim against an external source
/blind-spot Structural gap analysis
/brief Generate a compiled decision brief
/present Generate a presentation deck
/status Sprint dashboard snapshot
/pull Import knowledge from external sources (DeepWiki, Confluence)
/sync Publish artifacts to external targets
/calibrate Score predictions against actual outcomes
/resolve Adjudicate conflicts between claims
/feedback Record stakeholder input

The grainulator subagent (agents/grainulator.md) runs multi-pass research sprints autonomously. It reads the compiler output to decide what command to run next — research, challenge, witness, blind-spot — until the sprint reaches decision-ready confidence.

Launch it from Claude Code with: "research X using grainulator".

grainulator.app is a PWA that demos the research sprint concept in-browser:

  • Mobile-first chat interface — no shader on mobile, dark background
  • In-browser AI via WebLLM (SmolLM2-360M, ~200MB download)
  • 50 pre-generated demo topics with fuzzy matching (instant Track A)
  • Live local inference when model downloads (Track B)
  • Conversational responses with progressive claim disclosure
  • Compile flow with 7-pass confidence scoring
  • Plugin manifest: .claude-plugin/plugin.json
  • MCP servers: wheat (claims engine), mill (format conversion), silo (knowledge store), DeepWiki (codebase research)
  • Skills: skills/<name>/SKILL.md — 13 prompt-engineered workflows
  • Agent: agents/grainulator.md — autonomous sprint subagent
  • Hooks: Auto-compile on claim mutation, write-guard on claims.json and compilation.json
  • Orchard: Multi-sprint orchestration via orchard.json dependency graphs

Part of the grainulation ecosystem. Eight tools, each does one thing.

Tool What it does Install
wheat Research engine — grow structured evidence npx @grainulation/wheat init
farmer Permission dashboard — approve AI actions in real time npm i -g @grainulation/farmer
barn Shared tools — templates, validators, sprint detection npm i -g @grainulation/barn
mill Format conversion — export to PDF, CSV, slides npm i -g @grainulation/mill
silo Knowledge storage — reusable claim libraries and packs npm i -g @grainulation/silo
harvest Analytics — cross-sprint patterns and prediction scoring npm i -g @grainulation/harvest
orchard Orchestration — multi-sprint coordination npm i -g @grainulation/orchard
grainulation Unified CLI — single entry point npm i -g @grainulation/grainulation

You don't need all eight. Start with claude plugin install grainulator. That's it.

Three levels:

  1. Team lead: Commit .claude/settings.json with enabledPlugins to your repo
  2. IT admin: Deploy managed settings via MDM with pre-approved permissions
  3. Air-gapped: Use CLAUDE_CODE_PLUGIN_SEED_DIR with the plugin baked into container images

Every grainulation tool runs on Node built-ins only. No npm install waterfall. No left-pad. No supply chain anxiety. The MCP servers download on first use via npx — no global install required.

MIT

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