Token导航 LogoToken导航TokenDH.com
研究检索执行命令github未标认证来源可访问许可证需确认审计通过

investigate调查

Agent Skill

investigate 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。

总安装

524

周安装

21

GitHub Stars

292

下载量

170
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:investigate(调查)
来源仓库:https://github.com/tobihagemann/turbo
仓库路径:skills/investigate
安装命令:
npx skills add https://github.com/tobihagemann/turbo --skill investigate
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/tobihagemann/turbo --skill investigate

简介

investigate 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Investigate

Systematic methodology for finding the root cause of bugs, failures, and unexpected behavior. Cycle through characterize-isolate-hypothesize-test steps, with oracle escalation for hard problems. Diagnose the root cause — do not apply fixes.

Optional: $ARGUMENTS contains the problem description or error message.

Step 1: Characterize

Gather the symptom and establish what is actually happening:

  1. Collect evidence — error message, stack trace, test output, log entries, or user description of unexpected behavior
  2. Classify the problem type:
SignalType
Stack trace / exceptionRuntime error
Test assertion failureTest failure
Compilation / bundler / build errorBuild failure
Type checker error (tsc, mypy, pyright)Type error
Slow response / high CPU / memory growthPerformance
"It does X instead of Y" / no errorUnexpected behavior
  1. Establish reproduction — run the failing command, test, or operation. If the problem cannot be reproduced (intermittent, environment-specific), document the constraints and proceed with historical evidence.

Record the exact reproduction command and its output for verification. For intermittent or long-running reproductions, use the Monitor tool to tail logs filtered for relevant signals (errors, stack traces, specific identifiers) so failures surface live while you work.

Step 2: Isolate

Narrow from "something is wrong" to "the problem is in this area." Read references/problem-type-playbooks.md for type-specific first moves and tool sequences.

Git Archeology

For all problem types, check what changed recently near the failure point:

git log --oneline -20 -- <file>
git blame -L <start>,<end> <file>

If a known-good state exists (e.g., "this worked yesterday"), consider git bisect to pinpoint the breaking commit.

Scope Narrowing

  • Stack traces: Read the throwing function and its callers — full functions, not just the flagged line
  • Test failures: Read both the test and the system under test
  • Build errors: Read the config file and the referenced source
  • Unexpected behavior: Trace the data flow from input to the unexpected output

Step 3: Hypothesize

Generate 2-4 hypotheses ranked by likelihood. Each hypothesis must be falsifiable — specify what evidence would confirm or refute it.

Format:

H1 (most likely): [description] — confirmed if [X], refuted if [Y]
H2: [description] — confirmed if [X], refuted if [Y]
H3: [description] — confirmed if [X], refuted if [Y]

Parallel Investigation

For complex problems with 3+ hypotheses and a non-obvious root cause, spawn parallel investigators simultaneously.

Spawn condition: 3+ hypotheses AND the problem is not a simple typo, missing import, or syntax error.

Skip when 1-2 hypotheses are obvious (e.g., stack trace points directly to the bug).

Use the Agent tool to launch all agents below in a single assistant message so they run concurrently. Each Agent call uses model: "opus" and does not set run_in_background. Expect (one Agent per hypothesis + one Codex Agent) total. State the count explicitly when emitting the calls.

  • Hypothesis Agent (one per hypothesis): Each receives the hypothesis, relevant file paths, what evidence to look for, and instructions to report confirmed / refuted / inconclusive with evidence. Budget: max 5 tool calls per subagent.
  • Codex Agent: Launch one Agent whose prompt instructs the subagent to invoke /consult-codex via the Skill tool with a focused prompt describing the problem, reproduction, and files examined. The multi-turn conversation allows it to dig deeper into patterns the hypothesis-driven subagents miss. Run the /evaluate-findings skill on its output after the Agent returns.

After all investigators complete, merge results. Codex findings that overlap with a subagent's confirmed hypothesis reinforce confidence. Novel codex findings become additional hypotheses to test in Step 4.

Step 4: Test

Verify each hypothesis with minimal, targeted actions:

Action TypeTool
Find usage or patternGrep
Read surrounding codeRead
Check recent changesBash (git log, git blame, git diff)
Run isolated testBash (specific test command)
Check dependency versionBash (npm ls, pip3 show, etc.)
Inspect runtime stateBash (add temporary logging, run, check output)

Record each result:

HypothesisVerdictEvidence
H1confirmed / refuted / inconclusive[what was found]
H2confirmed / refuted / inconclusive[what was found]

Iteration

If all hypotheses are refuted or inconclusive:

  1. Document what was learned — each refuted hypothesis eliminates a possibility and narrows the search
  2. Return to Step 2 with the new information to re-isolate
  3. Generate new hypotheses in Step 3 based on updated understanding

Cycle budget: maximum 2 full cycles (hypothesize → test → learn → repeat) before escalating.

Escalation

After 2 failed hypothesis cycles, offer escalation to /consult-oracle via AskUserQuestion:

Investigation stalled after [N] hypothesis cycles.

Tested: [summary of hypotheses and evidence]
Remaining unknowns: [what is still unclear]

Escalate to Oracle? (consults external model with full context)

Proceed only if the user approves.

Investigation Report

Output results as text:

Investigation Report:

Problem: [one-line description]
Type: [runtime error | test failure | build failure | type error | performance | unexpected behavior]
Root cause: [confirmed cause, or "unresolved" with best hypothesis]

Evidence:
- [what confirmed the root cause]

Suggested fix: [description of what to change, or "needs further investigation"]
Reproduction command: [command to verify the fix once applied]

Hypotheses tested:
1. [hypothesis] — [confirmed/refuted/inconclusive] — [evidence]
2. [hypothesis] — [confirmed/refuted/inconclusive] — [evidence]

Escalation: [none | oracle]

Then use the TaskList tool and proceed to any remaining task.

Rules

  • If the problem turns out to be environmental (wrong Node version, missing dependency, OS-specific), report that clearly — it may not require a code fix.
  • If the problem is in a dependency (not the project's code), document the dependency issue and suggest workaround options rather than patching the dependency.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

37.98%
按下载量换算65

Claude

31.36%
按下载量换算53

Cursor

16.63%
按下载量换算28

Gemini CLI

8.85%
按下载量换算15

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/tobihagemann/turbo --skill investigate 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。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。

来源信息

继续浏览同类 Skills