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Agent Skill · 研究检索

premortem(premortem 搜索)

premortem 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

premortem 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 15,427。

总安装 7,858周安装 321GitHub Stars 3,682下载 2,517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
MIT

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:premortem(premortem 搜索)
来源仓库:https://github.com/parcadei/continuous-claude-v3
仓库路径:skills/premortem
安装命令:
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill premortem
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill premortem

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

premortem 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。适用于研究检索类任务,支持基于关键词或上下文进行信息聚合与过滤。

通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和联网能力。建议结合原始 README 核验具体用法,注意维护状态及是否触发文件读写或命令执行。premortem 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/premortem

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/parcadei/continuous-claude-v3 --skill premorte…;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

    它需要执行命令,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

premortem 怎么安装?

在终端执行 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill premortem。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

premortem 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。

premortem 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill premortem;npx skills add parcadei/continuous-claude-v3 --skill "premortem" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

premortem 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

premortem 用的人多吗?

公开数据是累计安装 7,858 次,近一周安装 321 次,下载 2,517 次,GitHub 3,682 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。

premortem 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
premortem

premortem 搜索 · 本页

7,8583,682执行命令MIT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

Pre-Mortem

Identify failure modes before they occur by systematically questioning plans, designs, and implementations. Based on Gary Klein's technique, popularized by Shreyas Doshi (Stripe).

Usage

/premortem              # Auto-detect context, choose depth
/premortem quick        # Force quick analysis (plans, PRs)
/premortem deep         # Force deep analysis (before implementation)
/premortem <file>       # Analyze specific plan or code

Core Concept

"Imagine it's 3 months from now and this project has failed spectacularly. Why did it fail?"

Risk Categories (Shreyas Framework)

CategorySymbolMeaning
Tiger[TIGER]Clear threat that will hurt us if not addressed
Paper Tiger[PAPER]Looks threatening but probably fine
Elephant[ELEPHANT]Thing nobody wants to talk about

CRITICAL: Verify Before Flagging

Do NOT flag risks based on pattern-matching alone. Every potential tiger MUST go through verification.

The False Positive Problem

Common mistakes that create false tigers:

  • Seeing a hardcoded path without checking for if exists(): fallback
  • Finding missing feature X without asking "is X in scope?"
  • Flagging code at line N without reading lines N±20 for context
  • Assuming error case isn't handled without tracing the code

Verification Checklist (REQUIRED)

Before flagging ANY tiger, verify:

potential_finding:
  what: "Hardcoded path at line 42"

verification:
  context_read: true    # Did I read ±20 lines around the finding?
  fallback_check: true  # Is there try/except, if exists(), or else branch?
  scope_check: true     # Is this even in scope for this code?
  dev_only_check: true  # Is this in __main__, tests/, or dev-only code?

result: tiger | paper_tiger | false_alarm

If ANY verification check is "no" or "unknown", DO NOT flag as tiger.

Required Evidence Format

Every tiger MUST include:

tiger:
  risk: "<description>"
  location: "file.py:42"
  severity: high|medium
  # REQUIRED - what mitigation was checked and NOT found:
  mitigation_checked: "No exists() check, no try/except, no fallback branch"

If you cannot fill in mitigation_checked with specific evidence, it's not a verified tiger.

Workflow

Step 1: Detect Context & Depth

# Auto-detect based on context
if in_plan_creation:
    depth = "quick"   # Localized scope
elif before_implementation:
    depth = "deep"    # Global scope
elif pr_review:
    depth = "quick"   # Localized scope
else:
    # Ask user
    AskUserQuestion(
        question="What depth of pre-mortem analysis?",
        header="Depth",
        options=[
            {"label": "Quick (2-3 min)", "description": "Plans, PRs, localized changes"},
            {"label": "Deep (5-10 min)", "description": "Before implementation, global scope"}
        ]
    )

Step 2: Run Appropriate Checklist

Quick Checklist (Plans, PRs)

Run through these mentally, note any that apply:

Core Questions:

  1. What's the single biggest thing that could go wrong?
  2. Any external dependencies that could fail?
  3. Is rollback possible if this breaks?
  4. Edge cases not covered in tests?
  5. Unclear requirements that could cause rework?

Output Format:

premortem:
  mode: quick
  context: "<plan/PR being analyzed>"

  # Two-pass process: first gather potential risks, then verify each one
  potential_risks:  # Pass 1: Pattern-matching findings
    - "hardcoded path at line 42"
    - "missing error handling for X"

  # Pass 2: After verification
  tigers:
    - risk: "<description>"
      location: "file.py:42"
      severity: high|medium
      category: dependency|integration|requirements|testing
      mitigation_checked: "<what was NOT found>"  # REQUIRED

  elephants:
    - risk: "<unspoken concern>"
      severity: medium

  paper_tigers:
    - risk: "<looks scary but ok>"
      reason: "<why it's fine - what mitigation EXISTS>"
      location: "file.py:42-48"  # Show the mitigation location

  false_alarms:  # Findings that turned out to be nothing
    - finding: "<what was initially flagged>"
      reason: "<why it's not a risk>"
Deep Checklist (Before Implementation)

Work through each category systematically:

Technical Risks:

  • Scalability: Works at 10x/100x current load?
  • Dependencies: External services + fallbacks defined?
  • Data: Availability, consistency, migrations clear?
  • Latency: SLA requirements will be met?
  • Security: Auth, injection, OWASP considered?
  • Error handling: All failure modes covered?

Integration Risks:

  • Breaking changes identified?
  • Migration path defined?
  • Rollback strategy exists?
  • Feature flags needed?

Process Risks:

  • Requirements clear and complete?
  • All stakeholder input gathered?
  • Tech debt being tracked?
  • Maintenance burden understood?

Testing Risks:

  • Coverage gaps identified?
  • Integration test plan exists?
  • Load testing needed?
  • Manual testing plan defined?

Output Format:

premortem:
  mode: deep
  context: "<implementation being analyzed>"

  # Two-pass process
  potential_risks:  # Pass 1: Initial scan findings
    - "no circuit breaker for external API"
    - "hardcoded timeout value"

  # Pass 2: After verification (read context, check for mitigations)
  tigers:
    - risk: "<description>"
      location: "file.py:42"
      severity: high|medium
      category: scalability|dependency|data|security|integration|testing
      mitigation_checked: "<what mitigations were looked for and NOT found>"
      suggested_fix: "<how to address>"

  elephants:
    - risk: "<unspoken concern>"
      severity: medium|high
      suggested_fix: "<suggested approach>"

  paper_tigers:
    - risk: "<looks scary>"
      reason: "<why it's actually ok - cite the mitigation code>"
      location: "file.py:45-52"

  false_alarms:
    - finding: "<initial concern>"
      reason: "<why verification showed it's not a risk>"

  checklist_gaps:
    - category: "<which checklist section>"
      items_failed: ["<item1>", "<item2>"]

Step 3: Present Risks via AskUserQuestion

BLOCKING: Present findings and require user decision.

# Build risk summary
risk_summary = format_risks(tigers, elephants)

AskUserQuestion(
    question=f"""Pre-Mortem identified {len(tigers)} tigers, {len(elephants)} elephants:

{risk_summary}

How would you like to proceed?""",
    header="Risks",
    options=[
        {
            "label": "Accept risks and proceed",
            "description": "Acknowledged but not blocking"
        },
        {
            "label": "Add mitigations to plan (Recommended)",
            "description": "Update plan with risk mitigations before proceeding"
        },
        {
            "label": "Research mitigation options",
            "description": "I don't know how to mitigate - help me find solutions"
        },
        {
            "label": "Discuss specific risks",
            "description": "Talk through particular concerns"
        }
    ]
)

Step 4: Handle User Response

If "Accept risks and proceed"
# Log acceptance for audit trail
print("Risks acknowledged. Proceeding with implementation.")
# Continue to next workflow step
If "Add mitigations to plan"
# User provides mitigation approach
# Update plan file with mitigations section
# Re-run quick premortem to verify mitigations address risks
If "Research mitigation options"
# Spawn parallel research for each HIGH severity tiger
for tiger in high_severity_tigers:
    # Internal: How has codebase handled this before?
    Task(
        subagent_type="scout",
        prompt=f"""
        Find how this codebase has previously handled: {tiger.category}

        Specifically looking for patterns related to: {tiger.risk}

        Return:
        - File:line references to similar solutions
        - Patterns used
        - Libraries/utilities available
        """
    )

    # External: What are best practices?
    Task(
        subagent_type="oracle",
        prompt=f"""
        Research best practices for: {tiger.risk}

        Context: {tiger.category} in a {tech_stack} codebase

        Return:
        - Recommended approaches (ranked)
        - Library options
        - Common pitfalls to avoid
        """
    )

# Wait for research to complete
# Synthesize options
# Present via AskUserQuestion with 2-4 mitigation options
If "Discuss specific risks"
# Ask which risk to discuss
AskUserQuestion(
    question="Which risk would you like to discuss?",
    header="Risk",
    options=[format_risk_option(r) for r in all_risks[:4]]
)
# Then have conversation about that specific risk

Step 5: Update Plan (if mitigations added)

If user added mitigations, append to the plan:

## Risk Mitigations (Pre-Mortem)

### Tigers Addressed:
1. **{risk}** (severity: {severity})
   - Mitigation: {user_or_researched_mitigation}
   - Added to phase: {phase_number}

### Accepted Risks:
1. **{risk}** - Accepted because: {reason}

### Pre-Mortem Run:
- Date: {timestamp}
- Mode: {quick|deep}
- Tigers: {count}
- Elephants: {count}

Integration Points

In create_plan / plan-agent

After plan structure is approved, before ExitPlanMode:

# Run quick premortem
/premortem quick

# If HIGH risks found, block until addressed
# If only MEDIUM/LOW, inform and proceed

After plan approval, before implementation

# Run deep premortem on full plan
/premortem deep thoughts/shared/plans/YYYY-MM-DD-feature.md

# Block until all HIGH tigers addressed

In PR review workflows

# Run quick premortem on diff scope
/premortem quick

# Inform of any risks found

Severity Thresholds

SeverityBlocking?Action Required
HIGHYesMust address or explicitly accept
MEDIUMNoInform user, recommend addressing
LOWNoNote for awareness

Example Session

User: /premortem deep thoughts/shared/plans/2026-01-08-api-rate-limiting.md

Claude: Running deep pre-mortem on API rate limiting plan...

[Reviews plan against deep checklist]

Pre-mortem complete. Found 2 tigers, 1 elephant:

**TIGERS:**
1. [HIGH] No circuit breaker for external payment API
   - Category: dependency
   - If payment API is slow/down, requests will pile up

2. [HIGH] No rollback strategy defined
   - Category: integration
   - If rate limiting breaks auth flow, no quick fix path

**ELEPHANTS:**
1. [MEDIUM] Team hasn't used Redis before
   - We're introducing Redis for rate limit counters
   - Learning curve could slow implementation

**PAPER TIGERS:**
1. Database migration size - Only adds one index, <1s migration

[AskUserQuestion presented]

User: Research mitigation options

Claude: Researching mitigations...

[Spawns scout + oracle in parallel]

Found 3 options for circuit breaker:

1. **Use existing retry util** (Recommended)
   - Found at src/utils/retry.ts:45
   - Already handles exponential backoff
   - Just need to add circuit breaker state

2. **Add resilience4j-lite**
   - Popular library for this pattern
   - More features but new dependency

3. **Custom implementation**
   - Full control but more code to maintain

Which approach for the circuit breaker?

User: Option 1 - use existing retry util

Claude: Added to plan:

## Risk Mitigations (Pre-Mortem)

### Tigers Addressed:
1. **No circuit breaker** (HIGH)
   - Mitigation: Extend src/utils/retry.ts with circuit breaker state
   - Added to Phase 1

Shall I also address the rollback strategy tiger?

References

平台分布

Claude Code

26.93%
按下载量换算678

OpenCode

23.78%
按下载量换算599

Gemini CLI

15.86%
按下载量换算399

Codex

10.93%
按下载量换算275

Cursor

7.3%
按下载量换算184

Antigravity

3.21%
按下载量换算81

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill premortem;npx skills add parcadei/continuous-claude-v3 --skill "premortem" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

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