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pm%3aexplorepm%3a 探索

Agent Skill

pm%3aexplore 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

238

周安装

10

GitHub Stars

公开资料未说明

下载量

83
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:pm%3aexplore(pm%3a 探索)
来源仓库:https://github.com/cloudvoyant/codevoyant
仓库路径:skills/pm%3Aexplore
安装命令:
npx skills add https://github.com/cloudvoyant/codevoyant --skill pm:explore
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/cloudvoyant/codevoyant --skill pm:explore

简介

用于查找、检索和筛选探索性研究相关资料。

  • 适合根据关键词快速定位新方向或技术可能性。
  • 使用时需明确探索目标和约束条件。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 安装前建议确认权限范围和维护状态。
  • pm%3aexplore 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Compatibility: AskUserQuestion falls back to numbered list on non-Claude-Code platforms.

Skill Requirements

command -v npx >/dev/null 2>&1 || echo "MISSING: npx"

Critical Rules

  • Never invent market data — every claim must come from a fetched source
  • Each research agent writes to its own isolated artifact — never combine within the agent
  • Synthesis from sub-artifacts happens only in Step 3, after all agents complete
  • One research artifact per topic slug — reuse existing slug directories when extending
  • Research artifacts feed pm:plan and pm:prd — deposit them faithfully at the specified paths
  • No markdown tables in output — use bullets and definition lists
  • Prefer Mermaid diagrams for any visual structure — timelines, competitive maps, process flows. Never use ASCII art for structured diagrams.
  • See references/web-research-standards.md for source tiers, citation format, and agent output format

Agent Index

  • internal-researcher (agents/internal-researcher.md) — scans project files for prior art, existing plans, and relevant skills
  • ideation-researcher (agents/ideation-researcher.md) — surfaces unmet needs, market gaps, and JTBD signals via web search
  • market-researcher (agents/market-researcher.md) — validates market size, growth, and existing solution landscape via web search
  • competitive-researcher (agents/competitive-researcher.md) — maps the competitive landscape with per-competitor site fetching
  • user-problems-researcher (agents/user-problems-researcher.md) — researches jobs-to-be-done and behavioral evidence via web search

Step 0: Parse arguments

TOPIC="${1:-}"
BG_FLAG=false; SILENT=false; DEEP=false
[[ "$*" =~ --bg|-b ]] && BG_FLAG=true
[[ "$*" =~ --silent ]] && SILENT=true
[[ "$*" =~ --deep ]] && DEEP=true

--deep escalates research: more searches, more URLs fetched, stricter source tier requirements.

Step 1: Mode and topic

Ask the user to select exploration mode(s):

AskUserQuestion:
  question: "What kind of exploration do you want to do?"
  header: "Explore mode"
  multiSelect: true
  options:
    - label: "Open-ended ideation"
      description: "Problem-seeking and idea generation — discover what's worth building"
    - label: "Feature/idea validation"
      description: "Validate a specific hypothesis with market research and competitive analysis"
    - label: "Competitor deep-dive"
      description: "Focused analysis of specific named competitors"
    - label: "User problem discovery"
      description: "JTBD-style research — surface jobs, pains, and gains from real sources"

If TOPIC is empty, ask for it. Derive SLUG (lowercase, hyphenated). Set:

  • OUTPUT_PATH =.codevoyant/explore/{SLUG}/summary.md
  • SUB_DIR =.codevoyant/explore/{SLUG}/research/

Ask mode-specific scoping questions (all in one AskUserQuestion call):

  • Open-ended ideation: "What space or user segment are you curious about? Any early hunches to stress-test?"
  • Feature/idea validation: "What is the hypothesis? Who is the target user? What would make this validation successful?"
  • Competitor deep-dive: "Name the competitors to analyze. Dimensions that matter most: pricing, features, positioning, or all?"
  • User problem discovery: "What job are users trying to get done? Which segments should be prioritized?"

Present a one-paragraph scope summary and confirm before launching agents.

Step 2: Launch parallel research agents

mkdir -p ".codevoyant/explore/{SLUG}/research"

Tell the user: "Starting parallel research on '{TOPIC}' (modes: {MODES}) — this will take a few minutes."

Spawn the following agents in a single message (run_in_background: true, model: claude-sonnet-4-6). Substitute all {PLACEHOLDERS} before spawning — agents receive no outer context.

Always spawn:

Agent:
  subagent_type: general-purpose
  model: claude-sonnet-4-6
  run_in_background: true
  description: 'pm-explore/internal: {SLUG}'
  prompt: |
    (full content of agents/internal-researcher.md with {TOPIC} → "{TOPIC}", {SLUG} → "{SLUG}" substituted)

Spawn based on selected modes:

ModeAgent fileOutput path
Open-ended ideationagents/ideation-researcher.md{SUB_DIR}ideation.md
Feature/idea validationagents/market-researcher.md{SUB_DIR}market.md
Feature/idea validationagents/competitive-researcher.md{SUB_DIR}competitive.md
Competitor deep-diveagents/competitive-researcher.md{SUB_DIR}competitive.md
User problem discoveryagents/user-problems-researcher.md{SUB_DIR}user-problems.md

For each agent, substitute into the agent file's prompt: {TOPIC}, {SLUG}, {DEEP}, and any mode-specific variables ({HYPOTHESIS}, {TARGET_USER}, {NAMED_COMPETITORS}, {DIMENSIONS}, {JOB_DESCRIPTION}, {USER_SEGMENTS}) gathered in Step 1. If "Competitor deep-dive" and "Feature/idea validation" are both selected, spawn competitive-researcher only once.

Do not send agent calls across separate messages — all must be in one message to run in parallel. Wait for all agents to complete before continuing.

Step 3: Synthesize and write artifact

Read all sub-artifacts in .codevoyant/explore/{SLUG}/research/. Write a unified research summary to OUTPUT_PATH:

# Research: {TOPIC}

**Modes:** {MODES}
**Date:** {DATE}

## Summary
{2–3 sentence synthesis — what do we now know that we didn't before?}

## Key Findings
{5–8 most important findings across all sub-artifacts, each cited}
- **{Finding}** — {source} [Tier N] [High/Medium/Low confidence]

## Problem Space / JTBD
{Include if ideation or user problem discovery mode — bullets from ideation.md and user-problems.md}

## Market Landscape
{Include if validation mode — bullets from market.md}

## Competitive Analysis
{Include if validation or competitor deep-dive mode — profiles from competitive.md}

## Internal Context
{bullets from internal.md — relevant prior work, plans, PRDs in this repo}

## Gaps and Open Questions
{bullets from all sub-artifacts — questions research couldn't answer}
- [UNVERIFIED] {claims attempted but not sourced}

## Suggested Next Steps
- Use this research with `/pm:plan` to inform roadmap priorities
- Use this research with `/pm:prd {SLUG}` to draft a PRD

Step 4: Notify

if [ "$SILENT" != "true" ]; then
  npx @codevoyant/agent-kit notify \
    --title "pm:explore complete" \
    --message "Research for '{TOPIC}' written to {OUTPUT_PATH}"
fi

Report: "Research summary written to {OUTPUT_PATH}. Sub-artifacts in .codevoyant/explore/{SLUG}/research/. Use /pm:prd {SLUG} or /pm:plan to continue."

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

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

34.18%
按下载量换算28

Claude

27.91%
按下载量换算23

Cursor

18.46%
按下载量换算15

Gemini CLI

10.14%
按下载量换算8

安全审计

暂无安全审计结果可展示。

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/cloudvoyant/codevoyant --skill pm:explore 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

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