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Research Queue

作者 Mozi Arasaka · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install research-queue
功能描述
Structured background research queue for unresolved technical, product, algorithmic, mathematical, and workflow questions. Use when the user wants to capture...
使用说明 (SKILL.md)

Research Queue

Use this skill when work produces unresolved questions that deserve deliberate investigation instead of ad-hoc guessing.

Core workflow

  1. Read QUESTIONS.md.
  2. If the file is missing, initialize it using the format in references/queue-format.md.
  3. Select at most one question unless the user explicitly asks for batch processing.
  4. Prefer the highest-priority open question with the strongest practical value.
  5. Investigate using only the minimum tools needed.
  6. Update the question entry in place with:
    • status
    • startedAt / completedAt when applicable
    • evidence summary
    • conclusion or blocked reason
    • memory note path if something durable was learned
  7. If the final status is done or wontfix, move the entire question block from ## Active Questions to ## Completed Questions in the same edit pass.
  8. Write durable findings to memory/YYYY-MM-DD.md when they are worth remembering.

Allowed investigation methods

Choose the lightest method that can answer the question:

  • web_search for fast grounded search
  • web_fetch for reading specific pages
  • browser only when a real browser is needed
  • read for local docs/config/code
  • exec for bounded local experiments, scripts, benchmarks, math checks, and repro steps

Allowed local coding includes short Python, Rust, JavaScript, or shell experiments when they directly help answer the selected question.

Hard rules

  • Investigate one question at a time by default.
  • Do not silently delete old questions.
  • Do not mark a question done without a concrete conclusion or result.
  • Distinguish clearly between verified findings, hypotheses, and blocked work.
  • When a question becomes done or wontfix, move it out of ## Active Questions immediately; do not leave completed items in the active section.
  • Use plausible real timestamps only; never write a completedAt in the future relative to the current run.
  • Do not modify production code or config unless the user explicitly asks for implementation work; research mode may create bounded scratch experiments or propose diffs instead.
  • Do not let the queue turn into vague brainstorming sludge; rewrite unclear entries into concrete answerable questions.

Status model

Use only these statuses in QUESTIONS.md:

  • open — not started yet
  • investigating — currently being worked
  • blocked — cannot finish without missing input/access/time
  • done — answered well enough for now
  • wontfix — intentionally dropped

First-use initialization

If QUESTIONS.md does not exist:

  1. Read references/queue-format.md.
  2. Create QUESTIONS.md from the canonical template.
  3. Keep the initial headings and status conventions intact.
  4. Add only the starter examples or the user’s real questions; do not pad it with fake research tasks.

Automation

Prefer OpenClaw cron when the user wants this queue processed automatically.

  • Default to cron, not HEARTBEAT.
  • Use HEARTBEAT only if the user explicitly wants main-session, drift-tolerant background attention.
  • Be explicit that this means the OpenClaw cron tool, not Unix crontab.
  • Prefer isolated cron runs so research work does not pollute the main conversation.
  • For scheduling details and the minimal run prompt, read references/automation.md.

What good completion looks like

A finished question should leave behind:

  • a stable answer or a bounded partial answer
  • the evidence source or experiment basis
  • completion time that matches the actual run window
  • relocation of finished work into ## Completed Questions
  • durable memory only if the result is likely to matter later

References

  • Queue structure and canonical template: references/queue-format.md
  • Automation and OpenClaw cron guidance: references/automation.md
安全使用建议
This skill appears coherent and appropriate for managing a research queue, but it permits the agent to read local files and run short commands as part of investigations. Before installing or enabling autonomous cron runs: (1) review QUESTIONS.md and any queued 'links' to ensure they don't reference sensitive config or credential files (e.g., ~/.openclaw/openclaw.json); (2) run the skill manually first so you can observe what files it reads and commands it runs; (3) prefer isolated cron runs (the skill recommends this) rather than embedding background work in your main session; and (4) avoid storing secrets or credentials in the queue or memory notes the agent will write. If you need stricter limits, restrict allowedTools (deny exec/read) or require manual invocation only.
功能分析
Type: OpenClaw Skill Name: research-queue Version: 1.0.1 The research-queue skill bundle provides a structured framework for an AI agent to manage and investigate technical questions using a markdown-based queue (QUESTIONS.md). While it utilizes high-risk capabilities like local code execution (exec) and web browsing, these are strictly aligned with its stated purpose of performing research and experiments. The instructions in SKILL.md and references/automation.md include safety boundaries, such as advising against modifying production code and preferring platform-native cron over system-level persistence (crontab).
能力评估
Purpose & Capability
Name/description align with the instructions: the skill reads and updates a local QUESTIONS.md, can run small local experiments (exec/read), and fetch web resources. No unrelated binaries, env vars, or installs are requested.
Instruction Scope
The SKILL.md explicitly allows local reads and bounded execs and recommends writing to QUESTIONS.md and memory/YYYY-MM-DD.md. This is coherent for a research workflow, but it does give the agent the ability to read local files and run commands — including any paths listed in question 'links' (the example references ~/.openclaw/openclaw.json). Users should be aware the agent can access local files and networked pages as part of investigations.
Install Mechanism
No install spec and no code files are present. Instruction-only skills have low install risk because nothing new is written to disk by the skill package itself.
Credentials
The skill declares no environment variables, credentials, or config paths. However, its allowed-tools policy (read/exec/browser/web_fetch) enables reading arbitrary local files if a question links to them; the example includes ~/.openclaw/openclaw.json. Though plausible for debugging research, this could expose agent/config secrets if referenced in the queue.
Persistence & Privilege
always: false and no changes to other skills or global configuration are requested. The skill recommends using OpenClaw cron for autonomous runs and even prefers isolated runs, which limits cross-session pollution. Autonomous invocation is allowed (platform default) but not elevated here.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install research-queue
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /research-queue 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Questions marked as `done` or `wontfix` must now be immediately moved from `## Active Questions` to `## Completed Questions` in the same edit. - Added a rule to use only plausible real timestamps; never write a `completedAt` in the future. - Updated completion criteria: finished entries must be relocated to the completed section, and their completion time must match the actual run. - Minor clarifications and rule emphasis to improve queue cleanliness and accuracy.
v1.0.0
- Initial release of the structured research queue skill. - Enables capturing, investigating, and tracking open technical and workflow questions. - Enforces high-quality research workflow with strict status management and evidence requirements. - Supports web/local investigation tools and bounded experiments. - Integrates with OpenClaw cron for autonomous background research. - Clearly distinguishes verified answers, hypotheses, and blocked work.
元数据
Slug research-queue
版本 1.0.1
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 2
常见问题

Research Queue 是什么?

Structured background research queue for unresolved technical, product, algorithmic, mathematical, and workflow questions. Use when the user wants to capture... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 99 次。

如何安装 Research Queue?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install research-queue」即可一键安装,无需额外配置。

Research Queue 是免费的吗?

是的,Research Queue 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Research Queue 支持哪些平台?

Research Queue 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Research Queue?

由 Mozi Arasaka(@mozi1924)开发并维护,当前版本 v1.0.1。

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