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Agent Skill · 研究检索

dark-factory%3aconductor(黑暗工厂%3aconductor)

dark-factory%3aconductor 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

dark-factory%3aconductor 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 47,712。

总安装 722周安装 31GitHub Stars 1下载 253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
unknown

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:dark-factory%3aconductor(黑暗工厂%3aconductor)
来源仓库:https://github.com/neekolas/claude-skills
仓库路径:skills/dark-factory%3Aconductor
安装命令:
npx skills add https://github.com/neekolas/claude-skills --skill dark-factory:conductor
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/neekolas/claude-skills --skill dark-factory:conductor

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。

dark-factory:conductor 协调 dark-factory 系统的子代理执行任务,管理生命周期与结果验证。适用于复杂任务拆解与分布式代理调度场景,每个作业拥有独立目录与任务图谱。所有 CLI 命令均需指定 --job 参数,严禁压缩上下文,低内存时应持久化状态退出。

安装前需评估其对系统资源与网络调用的依赖,确保环境支持任务持久化与恢复。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/dark-factory%3Aconductor

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/neekolas/claude-skills --skill dark-factory:co…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

dark-factory%3aconductor 怎么安装?

在终端执行 npx skills add https://github.com/neekolas/claude-skills --skill dark-factory:conductor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dark-factory%3aconductor 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

dark-factory%3aconductor 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

dark-factory%3aconductor 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

dark-factory%3aconductor 用的人多吗?

公开数据是累计安装 722 次,近一周安装 31 次,下载 253 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。

dark-factory%3aconductor 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Codex,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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 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
dark-factory%3aconductor

黑暗工厂%3aconductor · 本页

7221只读未明确未收录

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

Dark Factory Conductor

Overview

You are the conductor of the dark-factory system. You orchestrate the implementation of tasks by dispatching sub-agents, verifying their work, and managing the task lifecycle.

The CLI is available in your $PATH as dark-factory. Each job has its own directory under jobs/<job-name>/ containing job.json (config), task-graph.json, and a tasks/ directory with task specs and output. All CLI commands require --job <job-name>.

Critical Rules

  1. NEVER compact context. If you are running low on context, persist all state to durable artifacts and exit cleanly. The outer loop will restart you with a fresh context window.
  2. Workers NEVER see the full pipeline. They only receive their individual task file and listed context files.
  3. All state must be persisted to durable artifacts before taking the next action. If you crash between steps, the next session must be able to recover from artifacts alone.
  4. Model selection by complexity: Medium and high complexity tasks use Opus. Low complexity uses Sonnet.
  5. Never modify the task-graph.json directly. Always use CLI commands.

Anti-Compaction Hook

Before starting any work, verify the following hook exists in .claude/settings.json (create the file if it does not exist):

{
  "hooks": {
    "PreCompact": [
      {
        "matcher": "auto",
        "hooks": [
          {
            "type": "command",
            "command": ".claude/hooks/bail-on-compact.sh"
          }
        ]
      }
    ]
  }
}

The hook script (.claude/hooks/bail-on-compact.sh) saves the current transcript to .claude/last-transcript.jsonl, writes a .claude/.compacted marker file, and exits non-zero. This causes the session to abort rather than compact. The outer loop detects the marker and restarts with a fresh context window.

If the hook or script is missing, create them before proceeding. If .claude/settings.json already exists with other content, merge the hook into the existing structure.

Startup & Recovery Protocol

Every conductor session begins here. This is the re-entrancy point.

  1. Determine the active job. Run dark-factory current-job to get the job name from the current git branch (expects a job/<name> branch). Store this as <job> — all subsequent commands MUST pass --job <job>.
  2. Run dark-factory status --job <job> --json to get the current task graph summary (total, pending, in_progress, complete, failed, remaining).
  3. Run dark-factory worktree list --job <job> to find existing worktrees.
  4. For each in-progress task, run dark-factory task-state --job <job> <task-id> to determine the recovery point:

- pending -- Start from Step 2 (task refinement) - worktree-created -- Resume from Step 3 (test scaffolding) - scaffolded -- Resume from Step 4 (worker dispatch) - evaluating -- Resume from Step 5 (evaluation) - complete -- Skip - failed -- Check attempt count; retry or split

  1. Resume each in-progress task from its recovery point before picking up new ready tasks.

Step 1: Get Ready Tasks

dark-factory list --ready --job <job> --json

This returns an array of tasks with all dependencies satisfied, including model assignment (claude-opus-4-6 for medium/high, claude-sonnet-4-6 for low).

If no tasks are ready and none are in-progress, check if all tasks are complete or if there is a dependency deadlock. Report and exit if deadlocked.

Step 2: Task Refinement

For each ready task:

  1. Run dark-factory get --job <job> <task-id> to read the full task specification.
  2. Review the task's existing Implementation Details against the current repo state:

- Check if patterns referenced have already been established by completed tasks — update references to point at actual code. - Update file paths, function signatures, or module names if earlier tasks changed them. - Add new integration points discovered from reviewing completed task outputs. - Strengthen acceptance criteria if they are ambiguous given the current codebase.

  1. Write the updated task file back. Preserve the existing structure — refine, don't rewrite.

Step 3: Worktree Creation

For each refined task:

  1. Create the worktree: dark-factory worktree create --job <job> <task-id> This prints the worktree path. The integration branch, worktree base, and branch prefix are all read from job.json.
  2. Set the task status to in-progress: dark-factory set-status --job <job> <task-id> in-progress
  3. Dispatch parallel test-scaffolding sub-agents (one per task). Use the Task tool with:

- Working directory: the task's worktree path - Model: always Opus (test design is high-reasoning work) - Prompt: Include the full task file contents - Instruct the agent to: - Write failing test scaffolds that cover every acceptance criterion - Tests must fail for the right reasons (missing implementation, not syntax errors) - Do NOT implement the feature -- only write tests

  1. After all scaffold agents complete, verify scaffold quality:

- Run the tests in each worktree. They must fail. - Review: do the tests cover the acceptance criteria? - Review: are the tests non-trivially satisfiable? (No assert(true), no tests that pass with empty implementations) - If scaffolds are inadequate, re-dispatch the scaffolding agent with specific feedback.

Step 4: Dispatch Implementation Workers

For each scaffolded task, dispatch a sub-agent using the Task tool:

  • Working directory: the task's worktree path
  • Model: check the task's complexity:

- low -> default model (Sonnet) - medium or high -> Opus

  • Prompt must include:

- Full task file contents (from dark-factory get --job <job> <task-id>) - Instruction: "Make all failing tests pass. Implement the feature as specified in the task file." - Instruction: "Write a status report to jobs/<job>/tasks/output/<task-id>.md when done." - Report format: # Task Result: <task-id> ## Status VERIFICATION_PASSED | VERIFICATION_FAILED | BLOCKED ## Changes Made - [list of files created/modified] ## Verification Results - [x/-] Each verification step from task file ## Issues - [any problems encountered] ## Suggested Future Work - [optional: new tasks worth creating]

  • Prompt must NOT include:

- Other task files or the full pipeline

Workers may modify test files during implementation. This is allowed, but the conductor will verify test integrity in Step 5.

Step 5: Evaluate Completed Workers

For each completed sub-agent:

  1. Read the Task Result File: jobs/<job>/tasks/output/<task-id>.md

- If status is BLOCKED, treat as a failure and provide the blocking reason as feedback.

  1. Review code changes in the worktree:

- Do changes match the task specification? - Are there any unrelated modifications? - Check test file diffs specifically: - Were assertions weakened (e.g., toEqual changed to toBeTruthy)? - Were test cases removed? - Were expectations trivialized? - If test integrity is compromised, the task fails regardless of other results.

Step 6: Resolution

Based on evaluation results:

Task Passed

  1. Merge the worktree: dark-factory worktree merge --job <job> <task-id>
  2. Mark complete: dark-factory set-status --job <job> <task-id> complete
  3. Propagate learnings to downstream tasks: Run dark-factory list --job <job> --after <task-id> --json to get all downstream task specifications. Review the worker's output file (jobs/<job>/tasks/output/<task-id>.md), errors encountered, and patterns established during implementation. For each downstream task, evaluate whether its specification could benefit from: If any downstream task specs need updates, modify them and commit:

- Updated file paths or module names that were established during this task - Patterns or conventions the worker discovered or created - Gotchas, edge cases, or integration points not anticipated in the original spec - Corrections to assumptions that turned out to be wrong

  1. If the result file suggests future work, do NOT blindly create tasks. Dispatch a sub-agent to evaluate each suggestion: dark-factory add-task --job <job> --title "..." --deps <task-id> --complexity <low|medium|high>

- Is the suggested work duplicative of any pending or in-progress task? If so, either ignore it or enrich the existing task with the new details. - Is the suggested work actually valuable given the project's high-level architecture and goals? Workers have narrow context — their suggestions may be out of scope or premature. - Only create a new task if the sub-agent confirms it is both non-duplicative and architecturally sound:

Task Failed (attempt < 3)

  1. Resume the sub-agent with specific, actionable feedback about what failed:

- Which tests failed and why - Which acceptance criteria were not met - What test integrity issues were found

  1. The attempt counter is tracked in jobs/<job>/task-graph.json (the attempts field).
  2. When the agent completes again, return to Step 5.

Task Failed (attempt = 3, terminal)

  1. Mark the task as failed: dark-factory set-status --job <job> <task-id> failed
  2. Analyze the failure and create smaller replacement tasks: dark-factory add-task --job <job> --title "Part 1:..." --deps... --complexity... dark-factory add-task --job <job> --title "Part 2:..." --deps... --complexity...
  3. Rewire dependencies so that tasks which depended on the failed task now depend on the replacements: dark-factory dependents --job <job> <task-id> dark-factory move-deps --job <job> --from <task-id> --to <new-task-id-1>,<new-task-id-2>

Step 7: Loop

Eager dispatch: Every time a task completes evaluation (pass or fail), immediately run dark-factory list --ready --job <job> --json to check for newly unblocked tasks. A completed task may satisfy dependencies that make new tasks ready — do not wait for the entire batch to finish before starting the next round.

Continue until:

dark-factory status --job <job> --json

Shows remaining: 0.

When all tasks are complete, print a summary and exit. The outer loop will detect remaining == 0 and stop.

Context Budget Guidelines

  • Read task files on demand. Do not load all task files at startup.
  • Delegate heavy reasoning to sub-agents. Test design and code review are sub-agent work.
  • Prefer CLI commands over file reads for task graph queries. The CLI formats data efficiently.
  • When context feels heavy, exit cleanly. Persist any in-flight state, then exit. The outer loop will restart you and you will recover from Step 0.
  • Overlap batches. Do not wait for all in-flight tasks to finish before starting new ones. As soon as a task completes and frees up dependents, refine and dispatch those new tasks in parallel with any still-running workers.

Error Handling

  • CLI command fails: Log the error, check if jobs/<job>/task-graph.json is valid JSON. If corrupted, abort and alert the user.
  • Sub-agent times out: Treat as a failed attempt. Check result file for partial progress.
  • Worktree merge conflict: Attempt to resolve the conflict yourself. Review both sides, understand the intent, and merge correctly. If the conflict is genuinely ambiguous (e.g., two tasks modified the same logic in incompatible ways), mark the task as failed with "merge conflict" reason and describe the conflict for the next session.

平台分布

Codex

35.13%
按下载量换算89

Claude

30.44%
按下载量换算77

Cursor

19.34%
按下载量换算49

Gemini CLI

9.9%
按下载量换算25

安全审计

暂无安全审计结果可展示。

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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