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nm-conjure-delegation-corenm 召唤委托核心

Agent Skill

nm-conjure-delegation-core 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。

总安装

2,491

周安装

107

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下载量

873
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-conjure-delegation-core(nm 召唤委托核心)
来源仓库:https://github.com/athola/nm-conjure-delegation-core
安装命令:
openclaw skills install nm-conjure-delegation-core
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-conjure-delegation-core

简介

将任务委托给 Gemini 或 Qwen 等外部 LLM 服务。

  • 适合在 OpenClaw 中突破本地模型能力限制时使用。
  • 核心能力是统一管理跨厂商 API 配额与日志。
  • 使用 clawhub 安装,需预先配置第三方密钥。
  • 注意关注网络延迟与计费策略的影响。nm-conjure-delegation-core 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
delegation-core
description
Delegate tasks to external LLM services (Gemini, Qwen) with quota, logging,
version
1.8.2
triggers
metadata
{"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/conjure", "emoji": "\�\�", "requires": {"config": ["night-market.leyline:quota-management", "night-market.leyline:usage-logging", "night-market.leyline:service-registry", "night-market.leyline:error-patterns", "night-market.leyline:authentication-patterns"]}}}
source
claude-night-market
source_plugin
conjure
Night Market Skill — ported from claude-night-market/conjure. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Table of Contents

Delegation Core Framework

Overview

A method for deciding when and how to delegate tasks to external LLM services. Core principle: delegate execution, retain high-level reasoning.

When To Use

  • Before invoking external LLMs for task assistance.
  • When operations are token-heavy and exceed local context limits.
  • When batch processing benefits from different model characteristics.
  • When tasks require routing between models.

When NOT To Use

  • Task requires reasoning by Claude

Philosophy

Delegate execution, retain reasoning. Claude handles architecture, strategy, design, and review. External LLMs perform data processing, pattern extraction, bulk operations, and summarization.

Delegation Flow

  1. Task Assessment: Classify task by complexity and context size.
  2. Suitability Evaluation: Check prerequisites and service fit.
  3. Handoff Planning: Formulate request and document plan.
  4. Execution & Integration: Run delegation, validate, and integrate results.

Quick Decision Matrix

ComplexityContextRecommendation
HighAnyKeep local
LowLargeDelegate
LowSmallEither

High Complexity: Architecture, design decisions, trade-offs, creative problem solving.

Low Complexity: Pattern counting, bulk extraction, boilerplate generation, summarization.

Detailed Workflow Steps

1. Task Assessment (delegation-core:task-assessed)

Classify the task:

  • See modules/task-assessment.md for classification criteria.
  • Use token estimates to determine thresholds.
  • Apply the decision matrix.

Exit Criteria: Task classified with complexity level, context size, and delegation recommendation.

2. Suitability Evaluation (delegation-core:delegation-suitability)

Verify prerequisites:

  • See modules/handoff-patterns.md for checklist.
  • Evaluate cost-benefit ratio using modules/cost-estimation.md.
  • Check for red flags (security, real-time iteration).

Exit Criteria: Service authenticated, quotas verified, cost justified.

3. Handoff Planning (delegation-core:handoff-planned)

Create a delegation plan:

  • See modules/handoff-patterns.md for request template.
  • Document service, command, input context, expected output.
  • Define validation method.

Exit Criteria: Delegation plan documented.

4. Execution & Integration (delegation-core:results-integrated)

Execute and validate results:

  • Run delegation and capture output.
  • Validate format and correctness.
  • Integrate only after validation passes.
  • Log usage.

Exit Criteria: Results validated and integrated, usage logged.

MCP Authentication

OAuth Client Credentials (Claude Code 2.1.30+)

For MCP servers that don't support Dynamic Client Registration (e.g., Slack), pre-configured OAuth client credentials can be provided:

claude mcp add <server-name> --client-id <id> --client-secret <secret>

This enables delegation workflows through MCP servers that require pre-configured OAuth, expanding the range of external services available for task delegation.

Claude.ai MCP Connectors (Claude Code 2.1.46+)

As an alternative to manual OAuth setup, users can configure MCP servers directly in claude.ai at claude.ai/settings/connectors. These connectors are automatically available in Claude Code when logged in with a claude.ai account — no claude mcp add or credential management required. This provides a browser-based auth flow that may be simpler for services with complex OAuth requirements.

Worktree Isolation for File-Modifying Delegations (Claude Code 2.1.49+)

When delegating tasks that modify files to subagents, use isolation: worktree in the agent frontmatter to run each agent in a temporary git worktree. This prevents file conflicts when multiple delegated agents operate in parallel on overlapping paths. The worktree is auto-cleaned if no changes are made; preserved with commits if the agent produces changes.

# Agent frontmatter for isolated delegation
isolation: worktree

Leyline Infrastructure

Conjure uses leyline infrastructure:

Leyline SkillUsed For
quota-managementTrack service quotas and thresholds.
usage-loggingSession-aware audit trails.
service-registryUnified service configuration.
error-patternsConsistent error handling.
authentication-patternsAuth verification.

See modules/cost-estimation.md for leyline integration examples.

Service-Specific Skills

For detailed service workflows:

  • Skill(conjure:gemini-delegation): Gemini CLI specifics.
  • Skill(conjure:qwen-delegation): Qwen MCP specifics.

Execution Modes

When delegating to multiple agents, choose the appropriate execution mode:

ModeWhen to UseHow It Works
single-sessionSequential tasks, same-file editsClaude works through tasks in order
subagentsParallel independent tasksAgents work independently, report back
agent-teamParallel coordinated tasksAgents can communicate with each other

See references/execution-modes.md for the selection decision matrix, mode compatibility notes, and anti-patterns to avoid.

Module Reference

  • task-assessment.md: Complexity classification, decision matrix.
  • cost-estimation.md: Pricing, budgets, cost tracking.
  • handoff-patterns.md: Request templates, workflows.
  • troubleshooting.md: Common problems, service failures.

Exit Criteria

  • [ ] Task assessed and classified.
  • [ ] Delegation decision justified.
  • [ ] Results validated before integration.
  • [ ] Lessons captured.

适合场景

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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

77.21%
按下载量换算674

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可疑

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安装前确认

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