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Agent Skill · 开发

summon(summon 命令行)

summon 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

summon 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 21,446。

总安装 188周安装 8GitHub Stars 264下载 66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:summon(summon 命令行)
来源仓库:https://github.com/athola/claude-night-market
仓库路径:skills/summon
安装命令:
npx skills add https://github.com/athola/claude-night-market --skill summon
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/athola/claude-night-market --skill summon

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于 orchestrate 多技能协同完成端到端工作流。读取清单文件选择下一项任务并映射专长模块。动态监控上下文与 token 预算防止意外截断。自身不包含阶段逻辑实现,仅负责调度职责。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。

summon 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/summon

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/athola/claude-night-market --skill summon;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

summon 怎么安装?

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

summon 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。

summon 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。

summon 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。

summon 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 次,GitHub 264 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。

summon 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

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。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
summon

summon 命令行 · 本页

188264需要联网未明确有提醒

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

Table of Contents

Summon

Overview

Summon is the egregore orchestration loop. It reads the manifest (.egregore/manifest.json), selects the next active work item, maps the current pipeline step to a specialist skill, and invokes that skill. After each step it advances the pipeline, checks context and token budgets, and repeats until all items are completed or the budget is exhausted.

The orchestrator never re-implements phase logic. Each pipeline step delegates to an existing skill via Skill() calls. Summon only manages state transitions, retries, and budget guards.

When To Use

  • Processing one or more work items through the full intake-build-quality-ship pipeline.
  • Resuming an interrupted egregore session (manifest already exists with active items).
  • Running autonomously under a watchdog that relaunches on exit.

When NOT To Use

  • Running a single skill in isolation (call the skill directly instead).
  • Exploratory work where the pipeline does not apply.
  • When human review is needed before every step (use manual skill invocations).

Launching the Orchestrator

Always launch the orchestrator agent in the FOREGROUND. Do not use run_in_background: true. The main session becomes the egregore -- it blocks on the orchestrator agent until the egregore finishes or is dismissed.

Agent(
  subagent_type: "egregore:orchestrator",
  prompt: "<context about work items and current state>",
  run_in_background: false   // Required
)

If you launch the orchestrator in the background, the main session will have nothing to do and will stop. This defeats the entire purpose of the egregore. The stop hook cannot prevent this because background agents are detached.

Manifest Mode

Before launching the orchestrator, ensure the manifest has the correct run mode:

  • Default (no --bounded flag): set "indefinite": true in the manifest. The egregore will scan for new work after completing all items and run until dismissed.
  • With --bounded flag: set "mode": "bounded" in the manifest. The egregore stops after all items are completed or failed.

If the manifest already exists and has "mode": "bounded" but the user did NOT pass --bounded, update the manifest to "indefinite": true before launching.

After launching, do NOT produce any summary, status table, or "what's happening" output. The orchestrator IS the session now. Let it run.

Orchestration Loop

Follow these steps exactly. Each iteration processes one pipeline step for one work item.

1. Load state

manifest  = Read(".egregore/manifest.json")
config    = Read(".egregore/config.json")
budget    = Read(".egregore/budget.json")

If manifest.json does not exist, stop with an error: "No manifest found. Run egregore init first."

2. Pick the next work item

item = manifest.next_active_item()

If item is None, all work is done. Save the manifest, report completion, and exit.

3. Map current step to a skill

Look up item.pipeline_stage and item.pipeline_step in the Pipeline-to-Skill Mapping table below. Determine the skill name or action to invoke.

4. Invoke the skill

Call Skill() or execute the mapped action. Pass any required context (branch name, issue ref, etc.) from the work item.

5. Handle the result

On success:

  • Call manifest.advance(item.id) to move to the next step.
  • Reset item.attempts to 0.
  • Save the manifest.

On failure:

  • Call manifest.fail_current_step(item.id, reason).
  • If item.attempts < item.max_attempts, retry the same step on the next iteration.
  • If item.status is now "failed", log the failure and move to the next work item.
  • Save the manifest.

6. Check context budget

Estimate context window usage. If usage exceeds 80%:

  1. Save the manifest to disk.
  2. Write a continuation note to .egregore/continuation.json with the current item ID, stage, and step.
  3. Invoke Skill(conserve:clear-context).
  4. The watchdog or caller will relaunch a fresh session that resumes from the saved state.

7. Check token budget

If the last skill call returned a rate limit error:

  1. Record the rate limit in budget.json via budget.record_rate_limit(cooldown_minutes).
  2. Save budget.json.
  3. Alert the overseer (see notify.py).
  4. Schedule in-session recovery (2.1.71+): use CronCreate to schedule a one-shot resume prompt at the cooldown expiry time. The session stays alive and resumes automatically with context preserved.
  5. Fallback (pre-2.1.71 or cooldown > 7 days): exit gracefully. The watchdog checks cooldown before relaunching.

8. Repeat

Go back to step 2. Continue until all items are completed, all items are failed, or a budget limit is reached.

Pipeline-to-Skill Mapping

StageStepSkill/Action
intakeparseParse prompt or fetch issue via gh issue view
intakevalidateValidate requirements are actionable
intakeprioritizeOrder by complexity (single item = skip)
buildbrainstormSkill(attune:project-brainstorming)
buildspecifySkill(attune:project-specification)
buildblueprintSkill(attune:project-planning)
buildexecuteSkill(attune:project-execution)
qualitycode-reviewSkill(pensive:code-refinement)
qualityunbloatSkill(conserve:bloat-detector)
qualitycode-refinementSkill(pensive:code-refinement)
qualityupdate-testsSkill(sanctum:test-updates)
qualityupdate-docsSkill(sanctum:doc-updates)
shipprepare-prSkill(sanctum:pr-prep)
shippr-reviewSkill(sanctum:pr-review)
shipfix-prApply review fixes
shipmergegh pr merge (if auto_merge enabled)

The intake stage steps (parse, validate, prioritize) are handled inline by the orchestrator. See modules/intake.md for details.

Context Overflow Protocol

The orchestrator runs inside a finite context window. To avoid losing state when the window fills:

  1. Monitor usage. After each skill invocation, estimate how much of the context window has been consumed.
  2. At 80% capacity, trigger a context save:

- Persist the full manifest to disk. - Write .egregore/continuation.json with a snapshot of the current position. - Invoke Skill(conserve:clear-context).

  1. On relaunch, load continuation.json and resume from the saved position. The manifest on disk is the source of truth for pipeline progress.
  2. Increment manifest.continuation_count each time a context-overflow handoff occurs.

This protocol ensures zero lost progress across context boundaries.

Progress Monitoring & Self-Healing (2.1.71+)

After loading state (step 1), schedule a recurring heartbeat that both reports status and recovers stalled pipelines:

CronCreate(
  cron: "*/5 * * * *",
  prompt: "Check .egregore/manifest.json. If there are pending or active items that are not being processed, resume the orchestration loop by invoking Skill(egregore:summon). Otherwise, report status via /egregore:status.",
  recurring: true
)

This serves two purposes:

  1. Visibility: emits a status summary every 5 minutes so autonomous runs are observable.
  2. Self-healing: if a user prompt, context compaction, or unexpected error breaks the orchestration loop, the next heartbeat detects stalled items and re-enters the pipeline automatically.

The cron task auto-expires after 7 days by default. Use durable: true to persist across restarts, or CronDelete to cancel early.

Token Budget Protocol

Egregore sessions consume API tokens across a budget window (default: 5 hours). The budget protocol prevents runaway spending:

  1. Before each skill call, check budget.json for an active cooldown. If is_in_cooldown(budget) returns true, exit and let the watchdog retry later.
  2. On rate limit error, record the event via budget.record_rate_limit(cooldown_minutes). The cooldown duration equals the API retry-after header plus config.budget.cooldown_padding_minutes.
  3. Save and exit. Write budget.json, alert the overseer, and exit with code 0.
  4. The watchdog checks budget.json before relaunching. It will not start a new session until the cooldown expires.

See modules/budget.md for the full calculation and state schema.

Failure Handling

Each work item allows up to max_attempts retries per step (default: 3, configurable in config.json).

  • Retry: If a step fails and attempts < max_attempts, the orchestrator retries the same step on the next iteration. The manifest is saved between retries.
  • Mark failed: If attempts >= max_attempts, the item status changes to "failed" and failure_reason is set. The orchestrator moves to the next active item.
  • Alert: On failure, notify the overseer via the configured notification channel.
  • Never block: The orchestrator must never wait for human input. If a step requires clarification, record a decision (see modules/decisions.md) and proceed with the best available option.

Module Reference

  • pipeline.md: Stage and step definitions, transition rules, idempotency guarantees.
  • budget.md: Token window management, rate limit detection, cooldown calculation, graceful shutdown.
  • intake.md: Work item parsing for prompts and GitHub issues, brainstorm skip logic.
  • decisions.md: Autonomous decision-making framework, decision log format, examples.

平台分布

Codex

35.65%
按下载量换算24

Claude

29.28%
按下载量换算19

Cursor

19.41%
按下载量换算13

Gemini CLI

9.05%
按下载量换算6

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

可疑

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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