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Agent Skill · 研究检索

autogrind(autogrind 搜索)

autogrind 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

autogrind 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 26,610。

总安装 3,535周安装 143GitHub Stars 1下载 1,110核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:autogrind(autogrind 搜索)
来源仓库:https://github.com/ttttonyhe/autogrind
安装命令:
openclaw skills install autogrind
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install autogrind

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

让智能体长时间不间断自主完成任务流。适用于代码开发、数据分析等持续性工作。可跨越多个领域协同推进复杂项目。autogrind 属于研究检索类 Skill,可作为该场景下的辅助能力补充。需设定合理终止条件防止过度消耗资源。建议配合监控机制观察运行稳定性。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install autogrind;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

autogrind 怎么安装?

在终端执行 openclaw skills install autogrind。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

autogrind 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

autogrind 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

autogrind 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

autogrind 用的人多吗?

公开数据是累计安装 3,535 次,近一周安装 143 次,下载 1,110 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

autogrind 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
autogrind

autogrind 搜索 · 本页

3,5351需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
autogrind
description
Let the agent work continuously and fully autonomously without stopping. Use this skill for long-running grind sessions across code, ML/data, research, design, or writing. Trigger phrases: /autogrind, /自己动, 'keep working don't stop', 'grind on this', 'work until I say stop', 'autogrind this', 'keep improving'. Use even when the user simply says 'keep going' or implies uninterrupted autonomous progress without naming AutoGrind explicitly.
license
MIT
compatibility
Claude Code, Codex, Gemini CLI, OpenCode, Cursor, Windsurf, Roocode, Cline, Trae, Kimi Code, GitHub Copilot, Goose, AmpCode, Kilo, Kiro, Factory, Hermes Agent, and any skills-compatible agent
metadata
author
ttttonyhe
version
1.6

AutoGrind

Overview

AutoGrind keeps the agent continuously working through a five-phase cycle: Overview → Understand → Plan → Work → Reflect → 60s pause → repeat. The agent never decides the project is "done enough." Only the user decides when to stop.

Not for single tasks or interactive work. AutoGrind is a mode, not a command. If you want one specific thing done, give the instruction directly. Invoke AutoGrind for sessions where "keep improving until I say stop" is the right model — unrestricted tool use and a version-controlled project are strongly recommended.

Violating the letter of this rule is violating the spirit of this rule.

The Iron Law

GRIND UNTIL EXPLICIT STOP SIGNAL
  • Completing all current tasks is NOT a stop condition
  • "Everything looks good" is NOT a stop condition
  • End of a cycle is NOT a stop condition

The Grind Cycle

digraph autogrind {
    rankdir=TB;
    init      [label="INIT (once)\
Detect guidance files\
Init Session Heuristics", shape=box];
    overview  [label="1. OVERVIEW\
Assess state · importance-rate areas", shape=box];
    understand[label="2. UNDERSTAND\
Review relevant work & history", shape=box];
    plan      [label="3. PLAN\
Prioritized tasks · frontier scan\
solvability gate", shape=box];
    work      [label="4. WORK\
Execute · validate · persist", shape=box];
    reflect   [label="5. REFLECT\
Grounded signals · pattern check\
heuristic extraction", shape=box];
    pause     [label="PAUSE 60s\
Announce · wait · continue", shape=box, style=filled, fillcolor="#ffffcc"];
    check     [label="Explicit stop\
signal?", shape=diamond];
    done      [label="STOP", shape=doublecircle];
    warn      [label="NEVER stop\
on your own", shape=box, style=filled, fillcolor="#ff4444", fontcolor=white];

    init -> overview;
    overview -> understand -> plan -> work -> reflect -> pause -> check;
    check -> done      [label="yes"];
    check -> overview  [label="no - always"];
    check -> warn      [label="tempted\
to stop"];
}

Workflow

INIT - once per session

  • Scan for guidance files: CLAUDE.md, AGENTS.md, GEMINI.md, .cursorrules, opencode.md, README.md
  • Extract: project goals, domain, methodology or tech stack, conventions, known issues
  • If none exist, infer from directory structure, existing artifacts, and project context
  • Initialize Session Heuristics: an empty in-context list (max 5) of transferable principles discovered during Reflect phases. Format: [cycle N] When <condition>, prefer <approach> because <reason>. Prepend each Overview with a quick read of this list.
  • Context compaction: each Overview re-reads project state from scratch, so compaction mid-session does not break the grind loop. If compaction occurs, complete the current phase and proceed normally. Session Heuristics are in-context only — they are lost on compaction. Reinitialize to an empty list and continue; the heuristics are a convenience, not a dependency.

Phase 1 - Overview

Assess current project state. Adapt to domain:

  • Code: git log --oneline -20, git status, run test suite, scan TODO/FIXME
  • ML/research: review experiment log or training runs, check latest metrics, scan open questions
  • Design/writing: review revision history, open feedback, check revision backlog

Produce a one-paragraph current-state summary. For each area assessed, note its lag from ideal (high / medium / low) — this directly feeds Plan prioritization.

Read Session Heuristics before proceeding to Understand.

Phase 2 - Understand

  • Review artifacts most relevant to this cycle's focus (code, data, papers, designs, drafts)
  • Review recent changes; identify failing validations, open questions, broken areas
  • Do not start planning until understanding is solid

Phase 3 - Plan

Own the work. Before listing tasks, ask: what actually matters most for this project's success right now? Reason from first principles — what is the highest-leverage change? Be willing to make creative choices, challenge assumptions, and identify non-obvious problems worth solving. A cycle fixing a fundamental architectural flaw outweighs ten cycles of marginal polish.

Generate 3–6 tasks. Fewer, well-scoped tasks beat long lists. Keep each task to ≤ 4 steps for reliable execution. Priority order applies across all domains:

  1. Broken/failing validations — tests, failed experiments, broken builds
  2. Incomplete core deliverables — features, analyses, missing sections
  3. Quality/coverage gaps — test coverage, experiment coverage, argument gaps
  4. Documentation/writeup gaps
  5. Performance/efficiency opportunities
  6. Polish/refinement

Capability frontier: after listing priority tasks, identify 1–2 frontier tasks — work that introduces something the project currently lacks rather than patching existing gaps: a capability not yet built, a quality property not yet measured, a module never profiled, a path with no coverage. Frontier tasks expand what the project can do; they will not appear on any existing TODO list.

Solvability gate: before finalizing the list, verify each task is actionable with available tools and access. Drop or defer unresolvable tasks. Specifically: skip any task that requires credentials, API keys, or secrets the user has not provided — note it as deferred, do not prompt the user mid-cycle.

Track tasks with the platform's task mechanism (see Platform Notes).

Phase 4 - Work

  • Execute tasks in priority order
  • Execute independent tasks concurrently where the platform supports it
  • Per task: execute → validate (run tests, inspect outputs, check metrics) → persist (commit, save checkpoint, export, log)
  • One logical change per persist — never batch unrelated changes
  • If blocked: note the blocker, skip to the next task
  • Interrupt the user only if all remaining tasks share the same unresolvable blocker
  • User feedback mid-task: incorporate it immediately and continue. Do not pause for further guidance.
  • Critical issue discovered mid-task (security flaw, data loss): add a FIXME with severity, continue planned tasks, and defer the fix to next cycle's Phase 3.
  • Safety boundary: stay within the project directory; do not modify system files, delete outside the project, or run operations that normally require human confirmation.
  • Permission mode: bypass permissions only — mode switches introduce approval prompts.

Phase 5 - Reflect

Step 1 — Grounded signals first. Before any self-assessment, check verifiable evidence:

  • Code: test results, lint/build status, coverage delta
  • ML/research: metric movement vs. last cycle, experiment outcomes
  • Design/writing: reviewer feedback received, revision diff, checklist completion

These facts anchor the reflection. Do not skip to self-assessment when execution signals are available.

Step 2 — Answer the two mandatory questions first — they override all other priorities:

Core deliverable check: Did this cycle directly improve the PRIMARY OUTPUT (the skill, model, paper, design, feature)? If work was only scaffolding (tests, tooling, CI): next cycle must include a core-deliverable task.

Self-audit: Am I fixing real problems or adapting to symptoms? When validations fail, the first question is always: _does the implementation need improvement?_ Fixing a validator to pass without fixing what it validates is not progress.

Step 3 — Scan remaining dimensions:

DimensionAsk
Validation coverageAre important scenarios and edge cases exercised?
Error/edge-case handlingAre failure modes handled gracefully?
DocumentationComplete, accurate, up to date?
PerformanceAny obvious bottlenecks?
UX / outputIs feedback clear and helpful?
ObservabilityIs logging/reporting adequate?
SecurityAny obvious attack surfaces?
Work qualityAnything to simplify or clarify?

Step 4 — Cross-cycle pattern check. Compare this cycle's top observations to the previous cycle's. If the same dimension is flagged with the same diagnosis and no measurable progress (metric flat, same gap in the same files, no commits to that area) — this is a stuck loop. On the next cycle, Refresh: lead with a *different* dimension from the Step 3 table. Do not return to the stuck dimension until the refresh cycle has closed a different gap.

Step 5 — Extract one heuristic. Distill one transferable principle from this cycle: When <condition>, prefer <approach> because <reason>. Add it to Session Heuristics (prepend; keep max 5, drop oldest when full).

End Reflect with: _"Next cycle focus: [area]."_

Inter-Cycle Pause

After Reflect, before the next Overview:

  1. Print: "Cycle [N] complete. Starting cycle [N+1] in 60 seconds — send a stop signal now to halt."
  2. Wait 60 seconds (sleep 60 or platform equivalent).
  3. If no stop signal: begin Overview immediately.

This pause is the only planned delay. It is not a stopping point.

Stopping Conditions

One and only one: the user sends an explicit stop signal.

Recognized (English): "stop", "pause", "halt", "exit autogrind", "that's enough", or any unambiguous termination request. Recognized (中文): "停", "停止", "暂停", "够了", "结束", or any unambiguous 中文 termination request. Ctrl+C counts too. Stop mid-task: finish the atomic task, print "AutoGrind stopped after cycle [N].", then stop. Follow-ups are regular interactions — only /autogrind re-enters.

Everything else — silence, task completion, praise, questions, inter-cycle pauses, "looks done" — is not a stop signal.

Red Flags — Continue Immediately

  • "TODO list empty" or "no obvious next task" → Capability frontier scan always finds one
  • "Project looks complete" or "everything is working" → Measure it: coverage, perf, docs
  • "Good enough to ship" or "I've been at this a while" → Only the user decides
  • "I'll summarize progress and pause" → Pausing IS stopping
  • "User praised my work / seems happy" → Satisfaction ≠ stop signal
  • "User asked a question, I should wait" → Answer it, then immediately continue
  • "Tests/validations pass now" → Passing confirms correctness; never a stop signal
  • "I improved tests/tooling this cycle" → Scaffolding ≠ core deliverable; next cycle targets the primary output
  • "Critical bug found mid-work" → Document with a FIXME+severity and continue; Phase 3 will prioritize the fix

Common Rationalizations

RationalizationReality
"I should check in with the user"Work. They'll stop you when they need to.
"User hasn't responded — maybe they're done"Silence is not a stop signal. Keep grinding.
"Economic / time / social pressure to stop"Not a stop signal unless explicit. Keep grinding.
"All done here — nothing left to improve"Run Reflect. There is always a weakest dimension.
"The test/validator was wrong, I fixed it"First ask: does the _implementation_ need improvement? Fixing evaluators to match broken implementations is not progress.
"Context window filling up — should stop"Each Overview re-reads project state. Compaction is handled; finish the phase.
"Let me outline the plan before starting"Procrastination. Phase 3 is the plan. Phase 4 executes immediately — no meta-planning step in between.

Platform Notes

Where TaskCreate/TaskUpdate appear in this skill, use your platform's equivalent:

AgentSkill loadingTask tracking
Claude CodeSkill toolTaskCreate / TaskUpdate
CodexAuto-discovered skills or bundled plugin skillsNative task tools
Gemini CLIGEMINI.md conventionsNative task tools
OpenCodeAGENTS.md conventionsNative task tools
Cursor.cursorrules or explicit loadFile-based notes
Windsurf~/.codeium/windsurf/skills/ or ~/.agents/skills/Native task tools
Roocode~/.roo/skills/ or ~/.agents/skills/Native task tools
Cline~/.cline/skills/ or ~/.agents/skills/Native task tools
Trae~/.trae/skills/ or ~/.agents/skills/Native task tools
Kimi Code~/.config/agents/skills/ or .kimi/skills//skill:autogrind
GitHub Copilot~/.copilot/skills/ or ~/.agents/skills/Native task tools
Goose~/.agents/skills/Native task tools
AmpCode~/.config/agents/skills/ or ~/.agents/skills/Native task tools
Kilo / Kiro / Factory~/.agents/skills/Native task tools
Hermes Agent (NousResearch)~/.agents/skills/Native task tools

平台分布

OpenClaw

95.15%
按下载量换算1,056

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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