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nm-egregore-summonnm 埃格雷戈召唤

Agent Skill

nm-egregore-summon 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

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2,085

周安装

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下载量

681
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:nm-egregore-summon(nm 埃格雷戈召唤)
来源仓库:https://github.com/athola/nm-egregore-summon
安装命令:
openclaw skills install nm-egregore-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 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 nm-egregore-summon

简介

自主协调全生命周期任务清单并进行预算追踪。

  • 适合在 OpenClaw 中管理多阶段复杂项目时使用。
  • 核心能力是分解目标并动态调整资源分配。nm-egregore-summon 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 使用 clawhub 安装,需提供初始任务树结构。
  • 注意核实预算计算模型是否匹配实际成本结构。

SKILL.md

name
summon
description
|
version
1.8.2
triggers
metadata
{"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/egregore", "emoji": "\�\�", "requires": {"config": ["night-market.attune:project-brainstorming", "night-market.attune:project-specification", "night-market.attune:project-planning", "night-market.attune:project-execution", "night-market.pensive:code-refinement", "night-market.conserve:bloat-detector", "night-market.sanctum:pr-prep", "night-market.sanctum:pr-review", "night-market.sanctum:commit-messages", "night-market.conserve:clear-context"]}}}
source
claude-night-market
source_plugin
egregore
Night Market Skill — ported from claude-night-market/egregore. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

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.

  1. Invoke Skill(conserve:clear-context).
  2. 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).

  1. Save budget.json.
  2. Alert the overseer (see notify.py).
  3. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. Save and exit. Write budget.json, alert the

overseer, and exit with code 0.

  1. 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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

73.23%
按下载量换算499

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可疑

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可疑

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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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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