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Agent Skill · 待分类

war-room-checkpoint(作战室检查站)

war-room-checkpoint 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。

war-room-checkpoint 是待分类类 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,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 4,012。

总安装 832周安装 35GitHub Stars 264下载 291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:war-room-checkpoint(作战室检查站)
来源仓库:https://github.com/athola/claude-night-market
仓库路径:skills/war-room-checkpoint
安装命令:
npx skills add https://github.com/athola/claude-night-market --skill war-room-checkpoint
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 war-room-checkpoint

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

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。通过 npx skills add 命令从指定仓库安装,需结合原始 README 核验具体用法。

安装前建议确认权限范围、维护状态及是否会触发联网、命令执行或文件读写。war-room-checkpoint 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/war-room-checkpoint

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 war-room-ch…;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

war-room-checkpoint 怎么安装?

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

war-room-checkpoint 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。

war-room-checkpoint 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。

war-room-checkpoint 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。

war-room-checkpoint 用的人多吗?

公开数据是累计安装 832 次,近一周安装 35 次,下载 291 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。

war-room-checkpoint 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 需要处理待分类类任务、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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
war-room-checkpoint

作战室检查站 · 本页

832264需要联网未明确通过

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

War Room Checkpoint Skill

Lightweight inline assessment for determining whether a decision point within a command warrants War Room escalation.

Table of Contents

  1. Purpose
  2. When Commands Should Invoke This
  3. Invocation Pattern
  4. Checkpoint Flow
  5. Confidence Calculation
  6. Profile Thresholds
  7. Output Format
  8. Examples

Verification

Run make test-checkpoint to verify checkpoint logic works correctly after changes.

Purpose

This skill is not invoked directly by users. It is called by other commands (e.g., /do-issue, /pr-review) at critical decision points to:

  1. Calculate Reversibility Score (RS) for the current context
  2. Determine if full War Room deliberation is needed
  3. Return either a quick recommendation (express) or escalate to full War Room

When Commands Should Invoke This

CommandTrigger Conditions
/do-issue3+ issues, dependency conflicts, overlapping files
/pr-review>3 blocking issues, architecture changes, ADR violations
/architecture-reviewADR violations, high coupling, boundary violations
/fix-prMajor scope, conflicting reviewer feedback

Invocation Pattern

Skill(attune:war-room-checkpoint) with context:
  - source_command: "{calling_command}"
  - decision_needed: "{human_readable_question}"
  - files_affected: [{list_of_files}]
  - issues_involved: [{issue_numbers}] (if applicable)
  - blocking_items: [{type, description}] (if applicable)
  - conflict_description: "{summary}" (if applicable)
  - profile: "default" | "startup" | "regulated" | "fast" | "cautious"

Checkpoint Flow

Step 1: Context Analysis

Analyze the provided context to extract:

  • Scope of change (files, modules, services affected)
  • Stakeholders impacted
  • Conflict indicators
  • Time pressure signals

Step 2: Reversibility Assessment

Calculate RS using the 5-dimension framework:

DimensionAssessment Question
Reversal CostHow hard to undo this decision?
Time Lock-InDoes this crystallize immediately?
Blast RadiusHow many components/people affected?
Information LossDoes this close off future options?
Reputation ImpactIs this visible externally?

Score each 1-5, calculate RS = Sum / 25.

Step 3: Mode Selection

Apply profile thresholds to determine mode:

if RS <= profile.express_ceiling:
    mode = "express"
elif RS <= profile.lightweight_ceiling:
    mode = "lightweight"
elif RS <= profile.full_council_ceiling:
    mode = "full_council"
else:
    mode = "delphi"

Step 4: Response Generation

Express Mode (RS <= threshold)

Return immediately with recommendation:

response:
  should_escalate: false
  selected_mode: "express"
  reversibility_score: {rs}
  decision_type: "Type 2"
  recommendation: "{quick_recommendation}"
  rationale: "{brief_explanation}"
  confidence: 0.9
  requires_user_confirmation: false
Escalate Mode (RS > threshold)

Invoke full War Room and return results:

response:
  should_escalate: true
  selected_mode: "{lightweight|full_council|delphi}"
  reversibility_score: {rs}
  decision_type: "{Type 1B|1A|1A+}"
  war_room_session_id: "{session_id}"
  orders: ["{order_1}", "{order_2}"]
  rationale: "{war_room_rationale}"
  confidence: {calculated_confidence}
  requires_user_confirmation: {true_if_confidence_low}

Confidence Calculation

For escalated decisions, calculate confidence for auto-continue:

confidence = 1.0
- 0.10 * dissenting_view_count
- 0.20 if voting_margin < 0.3
- 0.15 if RS > 0.80
- 0.10 if novel_domain
- 0.10 if compound_decision
+ 0.20 if unanimous (cap at 1.0)

requires_user_confirmation = (confidence <= 0.8)

Profile Thresholds

ProfileExpressLightweightFull CouncilUse Case
default0.400.600.80Balanced
startup0.550.750.90Move fast
regulated0.250.450.65Compliance
fast0.500.700.90Speed priority
cautious0.300.500.70Higher stakes

Command-Specific Adjustments

CommandAdjustmentRationale
do-issue (3+ issues)-0.10Higher risk with multiple issues
pr-review (strict mode)-0.15Strict mode = higher scrutiny
architecture-review-0.05Architecture inherently consequential

Output Format

For Calling Command

Return a structured response that the calling command can act on:

## Checkpoint Response

**Source**: {source_command}
**Decision**: {decision_needed}

### Assessment
- **RS**: {reversibility_score} ({decision_type})
- **Mode**: {selected_mode}
- **Escalated**: {yes|no}

### Recommendation
{recommendation_or_orders}

### Control Flow
- **Confidence**: {confidence}
- **Auto-continue**: {yes|no}
{user_prompt_if_needed}

Integration Notes

Calling Commands Should

  1. Check checkpoint response's requires_user_confirmation
  2. If true: present confirmation prompt and wait
  3. If false: continue with orders or recommendation
  4. Log checkpoint to audit trail

Failure Handling

If checkpoint invocation fails:

  • Log warning with context
  • Continue command execution without checkpoint
  • Do NOT block the user's workflow

Audit Trail

Checkpoints are logged to:

~/.claude/memory-palace/strategeion/checkpoints/{date}/{checkpoint-id}.json

Each file contains a CheckpointEntry with: checkpoint_id, session_id, phase, action, reversibility_score, dimensions, confidence, files_affected, and requires_user_confirmation.

After a war room session completes and persist_session() is called, an audit report is written automatically to:

~/.claude/memory-palace/strategeion/war-table/{session-id}/audit-report.json

The report consolidates: all checkpoints for the session, the expert panel, voting summary with unanimity score, escalation history, final decision and rationale, and a Merkle-DAG integrity verification block. The verification recomputes every node hash against the stored values so any tampering with deliberation content is detectable.

Use AuditTrailManager from scripts.war_room.audit_trail to query checkpoints or generate reports programmatically:

from scripts.war_room.audit_trail import AuditTrailManager
manager = AuditTrailManager()
checkpoints = manager.get_checkpoints("war-room-20260303-100000")
audited = manager.list_audited_sessions()

Examples

Example 1: Low RS (Express)

Input:

source_command: "do-issue"
decision_needed: "Execution order for issues #101, #102"
issues_involved: [101, 102]
files_affected: ["src/utils/helper.py", "tests/test_helper.py"]

Assessment:

  • Reversal Cost: 1 (can revert commits)
  • Time Lock-In: 1 (no deadline)
  • Blast Radius: 1 (single utility module)
  • Information Loss: 1 (all options preserved)
  • Reputation Impact: 1 (internal)

RS: 0.20 (Type 2)

Response:

should_escalate: false
selected_mode: "express"
recommendation: "Execute in parallel - no dependencies detected"
confidence: 0.95
requires_user_confirmation: false

Example 2: High RS (Escalate)

Input:

source_command: "pr-review"
decision_needed: "Review verdict for PR #456"
blocking_items:
  - {type: "architecture", description: "New service without ADR"}
  - {type: "breaking", description: "API contract change"}
  - {type: "security", description: "Auth flow modification"}
  - {type: "scope", description: "Unrelated payment refactor"}
files_affected: ["src/auth/", "src/api/", "src/payment/", "src/services/new/"]

Assessment:

  • Reversal Cost: 4 (multi-service impact)
  • Time Lock-In: 3 (PR deadline pressure)
  • Blast Radius: 4 (cross-team impact)
  • Information Loss: 3 (some paths closing)
  • Reputation Impact: 2 (internal review)

RS: 0.64 (Type 1A)

Response:

should_escalate: true
selected_mode: "full_council"
war_room_session_id: "war-room-20260125-143025"
orders:
  - "Split PR: auth changes separate from payment refactor"
  - "Require ADR for new service before merge"
  - "API change: add migration path, not blocking"
confidence: 0.75
requires_user_confirmation: true

Related Skills

  • Skill(attune:war-room) - Full War Room deliberation
  • Skill(attune:war-room)/modules/reversibility-assessment.md - RS framework

Related Commands

  • /attune:war-room - Standalone War Room invocation
  • /do-issue - Issue implementation (uses this checkpoint)
  • /pr-review - PR review (uses this checkpoint)
  • /architecture-review - Architecture review (uses this checkpoint)
  • /fix-pr - PR fix (uses this checkpoint)

平台分布

Codex

38.02%
按下载量换算111

Claude

30.25%
按下载量换算88

Cursor

18.47%
按下载量换算54

Gemini CLI

9.24%
按下载量换算27

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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