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multi-agent-observability多智能体可观测性

Agent Skill

multi-agent-observability 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。

总安装

386

周安装

8

GitHub Stars

61

下载量

65
CodexClaudeCursorGemini CLI

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

unknown

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:multi-agent-observability(多智能体可观测性)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/multi-agent-observability
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill multi-agent-observability
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/melodic-software/claude-code-plugins --skill multi-agent-observability

简介

multi-agent-observability 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 中围绕仓库状态、代码变更或协作事项进行整理时使用。
  • 通过 GitHub API 获取仓库元数据、分支信息和协作动态,支持多 Agent 环境下的协同开发场景。
  • 安装命令为 npx skills add https://github.com/melodic-software/claude-code-plugins --skill multi-agent-observability。
  • 使用前需确认权限范围、维护状态,注意可能触发联网、命令执行或文件读写操作。

SKILL.md

Multi-Agent Observability Skill

Build observability interfaces for monitoring and measuring multi-agent systems.

Purpose

Guide the design and implementation of observability layers that provide real-time visibility into multi-agent execution.

When to Use

  • Designing monitoring for agent fleets
  • Building metrics dashboards
  • Implementing logging architecture
  • Creating cost tracking systems

Prerequisites

  • Understanding of the Three Pillars (@three-pillars-orchestration.md)
  • Familiarity with results-oriented patterns (@results-oriented-engineering.md)
  • Access to Claude Agent SDK documentation

SDK Requirement

Implementation Note: Full observability requires Claude Agent SDK with custom MCP tools and UI components. This skill provides design patterns.

The Critical Principle

"If you can't measure it, you can't improve it. If you can't measure it, you can't scale it."

What to Observe

Per-Agent Metrics

MetricPurposeHow to Track
StatusKnow stateAgent state enum
Context usageToken consumptionAPI response
CostFinancial impactAPI usage data
Tool callsWhat it's doingHook logging
ResultsOutput verificationResult parsing
DurationExecution timeTimestamps

Aggregate Metrics

MetricPurposeCalculation
Total agentsScaleCount active
Total durationEnd-to-end timeFirst to last
Total costFinancial totalSum per-agent
Success rateReliabilitySuccess / total
CoverageScopeFiles touched

Observability Components

1. Agent Cards

Real-time status for each agent:

┌─────────────────────────────────────┐
│ scout_1                 [EXECUTING] │
├─────────────────────────────────────┤
│ Template: scout-fast                │
│ Model: haiku                        │
│ Context: 12,500 / 100,000 tokens    │
│ Cost: $0.05                         │
│ Duration: 45s                       │
│ Tool calls: 15                      │
└─────────────────────────────────────┘

Required fields:

  • Agent ID and template
  • Status (idle, executing, complete, error)
  • Model being used
  • Context usage (current / max)
  • Running cost
  • Execution duration
  • Tool call count

2. Event Stream

Real-time log of all activities:

[10:30:00] scout_1 created (template: scout-fast)
[10:30:01] scout_1 commanded: "Analyze auth module"
[10:30:05] scout_1 Read: src/auth/login.ts
[10:30:08] scout_1 Grep: "password" in src/auth/
[10:30:15] scout_1 completed (duration: 14s)
[10:30:16] scout_1 deleted

Event types:

  • Agent lifecycle (create, delete)
  • Commands sent
  • Tool calls
  • Status changes
  • Errors

3. Cost Tracking

Track spend per agent and total:

Cost Summary
────────────────────────────────────
scout_1 (haiku)      $0.05
scout_2 (haiku)      $0.04
builder_1 (sonnet)   $0.35
reviewer_1 (sonnet)  $0.12
────────────────────────────────────
Total                $0.56
Budget remaining     $4.44 (89%)

Cost components:

  • Input tokens
  • Output tokens
  • Per-agent breakdown
  • Running total
  • Budget tracking

4. Result Inspector

View consumed and produced assets:

Agent: builder_1

Consumed Assets:
├── Scout report (summary)
├── src/auth/middleware.ts
└── package.json

Produced Assets:
├── src/auth/rate-limit.ts (created)
├── src/auth/middleware.ts (modified)
└── tests/rate-limit.test.ts (created)

Summary: "Implemented rate limiting middleware"
Status: completed

5. Log Viewer

Filterable activity history:

Filters: [agent: all] [level: all] [tool: all]

10:30:00 INFO  scout_1   Created from template
10:30:01 INFO  scout_1   Received command
10:30:05 DEBUG scout_1   Read: src/auth/login.ts (1,200 tokens)
10:30:08 DEBUG scout_1   Grep: found 5 matches
10:30:12 WARN  scout_1   Context at 80% capacity
10:30:15 INFO  scout_1   Completed successfully

Implementation Patterns

Logging Architecture

# Event types
class AgentEvent:
    timestamp: datetime
    agent_id: str
    event_type: str  # create, command, tool, status, error
    details: dict

# Log collector
def log_event(event: AgentEvent):
    # Store to database
    db.events.insert(event)
    # Emit to WebSocket
    ws.broadcast(event)
    # Update metrics
    metrics.update(event)

Real-Time Updates

# WebSocket for live updates
async def agent_status_stream(agent_id):
    while agent_active(agent_id):
        status = get_agent_status(agent_id)
        yield status
        await asyncio.sleep(1)

Cost Calculation

def calculate_cost(usage):
    input_cost = usage.input_tokens * MODEL_INPUT_PRICE
    output_cost = usage.output_tokens * MODEL_OUTPUT_PRICE
    return input_cost + output_cost

UI Components

Minimal CLI View

Orchestration: Add rate limiting
────────────────────────────────────
Agents: 3 active | 2 complete | 0 error
Cost: $0.56 / $5.00 budget
Progress: ████████░░ 80%

[scout_1] ✓ complete (14s)
[scout_2] ✓ complete (12s)
[builder] ⚡ executing (45s)

Rich Dashboard View

┌─────────────────────────────────────────────────────────────┐
│                    Orchestration Dashboard                    │
├─────────────────────────────────────────────────────────────┤
│ Task: Add rate limiting to authentication                    │
│ Started: 10:30:00 | Duration: 2m 15s | Cost: $0.56          │
├─────────────────────────────────────────────────────────────┤
│ Agent Fleet                          │ Event Stream          │
│ ┌─────────────────────────────────┐  │ [10:32:15] builder   │
│ │ scout_1        [✓ complete]    │  │   Write: rate-limit  │
│ │ scout_2        [✓ complete]    │  │ [10:32:10] builder   │
│ │ builder        [⚡ executing]   │  │   Read: middleware   │
│ │ reviewer       [○ pending]     │  │ [10:30:15] scout_2   │
│ └─────────────────────────────────┘  │   completed          │
├─────────────────────────────────────────────────────────────┤
│ Cost Breakdown     │ Results Summary                         │
│ haiku:  $0.09     │ Files read: 8                           │
│ sonnet: $0.47     │ Files written: 3                        │
│ Total:  $0.56     │ Tests: 5/5 passing                      │
└─────────────────────────────────────────────────────────────┘

Design Checklist

  • Per-agent metrics defined
  • Aggregate metrics calculated
  • Event logging implemented
  • Real-time updates via WebSocket
  • Cost tracking per agent
  • Result inspection available
  • Log filtering supported
  • UI components designed

Output Format

When designing observability, provide:

## Observability Design

### Metrics

**Per-Agent:**
[List with tracking method]

**Aggregate:**
[List with calculation]

### Components

**Agent Cards:** [fields and update frequency]
**Event Stream:** [event types and storage]
**Cost Tracking:** [breakdown and budgets]
**Result Inspector:** [consumed/produced format]
**Log Viewer:** [filters and retention]

### Implementation

**Logging:** [architecture]
**Real-Time:** [WebSocket design]
**Storage:** [database schema]
**UI:** [component specifications]

Anti-Patterns

Anti-PatternProblemSolution
No metricsFlying blindTrack everything
Delayed updatesStale statusReal-time WebSocket
No cost trackingBudget overrunsPer-agent costs
Missing logsCan't debugLog all events
No aggregationCan't summarizeCalculate totals

Cross-References

  • @three-pillars-orchestration.md - Observability pillar
  • @results-oriented-engineering.md - Result patterns
  • @agent-lifecycle-crud.md - Agent state tracking
  • @orchestrator-design skill - System architecture

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101

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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

Codex

39.19%
按下载量换算25

Claude

29.25%
按下载量换算19

Cursor

17.92%
按下载量换算12

Gemini CLI

10.75%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

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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。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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