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Agent Skill · 研究检索

startup-positioning(启动定位)

startup-positioning 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。

startup-positioning 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;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 35,312。

总安装 2,105周安装 86GitHub Stars 261下载 681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
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unknown

安装方式

通过对话安装

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请帮我安装这个 Agent Skill:startup-positioning(启动定位)
来源仓库:https://github.com/ferdinandobons/startup-skill
仓库路径:skills/startup-positioning
安装命令:
npx skills add https://github.com/ferdinandobons/startup-skill --skill startup-positioning
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/ferdinandobons/startup-skill --skill startup-positioning

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。

startup-positioning 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。适用于初创企业在市场中定位策略的信息支持,可协助分析竞品与差异化优势。

通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 确认具体用法。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操作。当前暂无原始 SKILL.md 内容摘录,建议进一步查阅来源仓库获取详细功能说明。

来源仓库内路径:skills/startup-positioning

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/ferdinandobons/startup-skill --skill startup-p…;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

startup-positioning 怎么安装?

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

startup-positioning 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。

startup-positioning 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/ferdinandobons/startup-skill --skill startup-positioning 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。

startup-positioning 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。

startup-positioning 用的人多吗?

公开数据是累计安装 2,105 次,近一周安装 86 次,下载 681 次,GitHub 261 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。

startup-positioning 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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。

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
startup-positioning

启动定位 · 本页

2,105261执行命令未明确有提醒

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

Startup Positioning

Market positioning strategy that produces a complete positioning document, Moore + Neumeier positioning statements, competitive alternatives map, and market category analysis. Built on April Dunford's framework, enriched with JTBD discovery and stress-tested with Neumeier's Onliness Test.

How It Works

INTAKE → RESEARCH (2 parallel waves) → POSITIONING SYNTHESIS

The process: understand the product and its customers, research competitive alternatives and market context, then build positioning through Dunford's 5+1 components. Typical runtime: 10-15 minutes in Claude Code (parallel agents), 20-30 minutes in Claude.ai (sequential).

Language

Default output language is English. If the user writes in another language or explicitly requests one, use that language for all outputs instead.


Phase 1: Intake

Short and focused — 1-2 rounds of questions. The goal is enough context to research alternatives and build positioning.

Check for Prior Work

Before asking questions, check if prior sessions have been completed. Look for these files in the working directory or subdirectories:

From startup-design:

  • 00-intake/brief.md — product description and context
  • 01-discovery/competitor-landscape.md — competitor profiles
  • 01-discovery/target-audience.md — customer personas, pain points
  • 02-strategy/positioning.md — initial positioning work

From startup-competitors:

  • intake.md — product and market context
  • competitors-report.md — strategic competitive analysis
  • battle-cards/ — per-competitor profiles
  • pricing-landscape.md — pricing analysis

If these files exist, read them and use the data as a head start:

  • Extract the product description, known competitors, and customer pain points
  • Use competitor profiles and battle cards to seed the competitive alternatives map
  • Pull any existing positioning work as a starting hypothesis to test, not a conclusion to keep
  • Use customer language and pain points to inform JTBD discovery

Tell the user: "I found data from a previous session. I'll use it as a starting point for positioning analysis."

Skip redundant intake questions. Go straight to research if prior data is sufficient.

What to Ask (if no prior data exists)

Round 1 — Core context:

  • What's your product? (one sentence is fine)
  • What problem does it solve and for whom?
  • What do your customers do today instead of using you? (alternatives, workarounds, doing nothing)
  • Who are your best existing customers? (if any — describe them, not demographics)

Round 2 — Sharpening (only if needed):

  • How is your product different from the alternatives you mentioned?
  • Have you tried positioning before? What didn't work?
  • Are there competitors you're often compared to?

Don't over-interview. If the user gives a clear description upfront, move to research. The positioning process itself will surface what matters.

Output

Save to {project-name}/intake.md — a brief summary of the product, problem, alternatives, and customers. If built on prior session data, note the source files used. Project name: kebab-case (e.g., ai-email-assistant).

Create {project-name}/PROGRESS.md with: project name, skill name (startup-positioning), start date, language, research mode (Live / Knowledge-Based), and a phase checklist. Update it after each phase completes. If PROGRESS.md already exists from a previous session, resume from the last incomplete phase.


Phase 1.5: Research Depth Assessment

After intake, assess market complexity and present the Research Depth recommendation to the user.

Reference: Read references/research-scaling.md for the complexity scoring matrix, tier definitions, wave configurations, and the user communication template.

Process

  1. Score three factors from the intake: market breadth (1-3), known competitors (1-3), geographic scope (1-3)
  2. Sum the scores (range 3-9) and map to a tier: Light (3-4), Standard (5-7), Deep (8-9)
  3. Present the Research Depth table to the user (see research-scaling.md for the exact template)
  4. Wait for user response: light, deep, or ok to accept the recommendation
  5. Record the selected tier in PROGRESS.md

The selected tier determines the number of agents per wave and search rounds per agent in Phase 2. See research-scaling.md for exact wave configurations per tier.


Phase 2: Research

Two parallel research waves exploring competitive alternatives and market context. Together they provide the raw material for Dunford's 5+1 positioning components.

Environment Detection

Check if the Agent tool is available:

  • Agent tool available (Claude Code): Spawn all agents within each wave in parallel. This is faster.
  • Agent tool NOT available (Claude.ai, web): Execute research sequentially, following the same templates. Same depth, just slower.

Web Search

This skill requires WebSearch for real data. If WebSearch is unavailable or denied, fall back to Knowledge-Based Mode: use training data, mark all findings with [Knowledge-Based — verify independently], and reduce confidence ratings by one level. Note the mode in PROGRESS.md.

Reference: Read references/research-principles.md before starting any wave. It defines source quality tiers, cross-referencing rules, and how to handle data gaps.

Wave 1: Competitive Alternatives & Customer Context

Reference: Read references/research-wave-1-alternatives.md for agent templates.

Two agents (or two sequential blocks):

A1: Alternative Mapping (JTBD Lens) — Map ALL competitive alternatives, not just direct competitors. Include: direct competitors, adjacent tools competing for the same budget, manual processes, spreadsheets, hiring someone, doing nothing / status quo. For each: what job does the customer hire it for, where does it fall short, what triggers switching? The goal is the full set of things your product replaces.

A2: Customer Intelligence — Mine voice-of-customer data: reviews, forums, communities. Extract: pain points with current alternatives, exact language customers use, what "better" means to them, best-fit customer profile (who gets the most value fastest), switching triggers (what makes someone finally change). Build a language map — the words customers use to describe their problem and desired outcome.

Wave 2: Market Frame & Trends

Reference: Read references/research-wave-2-market-frame.md for agent templates.

Two agents (or two sequential blocks):

B1: Market Category Analysis — Identify 3-5 candidate market categories. For each: what do buyers expect from this category, who are the leaders, what's the competitive dynamic, how mature is it? Apply Dunford's category types: head-to-head (existing category), big fish/small pond (subcategory), or category creation. Assess which frame makes your unique strengths matter most.

B2: Trend & Timing Analysis — Identify relevant trends: technology shifts, behavioral changes, regulatory moves. For each: is it real or hype, how does it affect buyer expectations, does it make your positioning stronger or weaker? Assess timing — are you early, on-time, or late to the trend? Only include trends that genuinely change how buyers evaluate solutions.


Post-Research Checkpoint

After both waves complete, before synthesis, briefly present what the research found to the user: the competitive alternative landscape (how many direct, adjacent, status quo), the strongest customer pains, and the most promising category candidates. Ask: "Does this align with your expectations? Anything to adjust before I synthesize the positioning?"

Keep it to one message — this is a quick alignment check, not a full report.


Phase 3: Positioning Synthesis

Reference: Read references/research-synthesis.md for synthesis protocol and Dunford process details.

After the checkpoint, build positioning through Dunford's 5+1 components in order. The sequence matters — each step builds on the previous.

The 5+1 Components

  1. Competitive Alternatives — From Wave 1. What would customers use if your product didn't exist? This is the anchor — positioning is always relative.
  2. Unique Attributes — What do you have that the alternatives lack? Be specific and honest. Features, architecture, team expertise, business model, speed — anything defensible. ⏸ PAUSE — User Input Required. Present the research-derived attributes to the user. Ask them to confirm, add, or remove before proceeding to Value Themes. The founder knows capabilities that research can't surface.
  3. Value Themes — Translate each unique attribute into a customer outcome. Attribute → "so what?" → value. Group related attributes into 2-3 value themes. Use customer language from Wave 1's language map.
  4. Best-Fit Customers — From Wave 1 customer intelligence. Who cares most about your value themes? Define by characteristics that make them care, not demographics. These customers should be reachable, recognizable, and willing to pay.
  5. Market Category — From Wave 2. Choose the category frame that makes your value obvious. Present 3-5 options with trade-offs. Recommend one. The right category triggers the right buyer expectations.
  6. Trend Overlay (optional) — From Wave 2. Only include if a genuine trend makes your positioning stronger. Forced trend alignment is worse than none.

Validation

Two stress tests before finalizing:

Neumeier Onliness Test:

Basic form:

"Our [product] is the only [category] that [differentiator]."

Extended form (6 elements — WHAT/HOW/WHO/WHERE/WHY/WHEN):

"Our [product] is the only [category] that [differentiator] for [target] who [need] in [context]."

If you can't fill the basic form convincingly — if "only" feels like a stretch — the positioning is too weak. Iterate.

Ries/Trout Mental Ladder:

  • Is it simple enough to remember?
  • Does it claim one clear rung?
  • Is that rung available (not owned by a competitor)?
  • Can you explain it in one sentence?

If either test fails, revisit the 5+1 components. Don't ship weak positioning.

Output Files

Every deliverable file must start with a standardized header: # {Title}: {product} followed by *Skill: startup-positioning | Generated: {date}*. Every deliverable must end with Red Flags, Yellow Flags, and Sources sections (see templates in references/research-synthesis.md).

{project-name}/positioning-doc.md — The main deliverable:

  • Executive summary (positioning in 3 sentences)
  • The 5+1 components with supporting evidence
  • Strength assessment per component (Strong / Moderate / Needs Work)
  • Strategic recommendations and next steps
  • Data gaps & limitations

{project-name}/positioning-statement.md — Statements and messaging:

  • Moore template: "For [target] who [need], [product] is a [category] that [benefit]. Unlike [alternative], we [differentiator]."
  • Neumeier Onliness Statement (basic + extended)
  • Elevator pitch (30-second version)
  • Tagline candidates with stress-tested "Possible Misread" column
  • One-liner variants for different channels (GitHub, marketplace, social, elevator)
  • Freemium positioning (if applicable)

{project-name}/competitive-alternatives.md — Complete alternatives map:

  • All alternatives (direct, adjacent, manual, status quo)
  • Per alternative: job hired for, strengths, shortcomings, switching triggers
  • Your unique attributes vs. each alternative

{project-name}/market-category-analysis.md — Category strategy:

  • 3-5 candidate categories with buyer expectations
  • Category type assessment (head-to-head / subcategory / creation)
  • Recommendation with reasoning
  • Implementation (category label, tagline direction, buyer expectation alignment)
  • Red flags and yellow flags

{project-name}/messaging-implications.md — Bridge from positioning to copy:

  • Messaging hierarchy (what to communicate first, second, third)
  • Category label (exact phrase to use everywhere)
  • Value anchor (what to compare value to, separate from category)
  • Customer language vs. category language map (which words are customer verbs, which are category nouns)
  • Words to use / avoid
  • Social proof guidelines
  • Freemium positioning (if applicable)

Raw Data

Each agent saves its raw output to {project-name}/raw/. The synthesis phase reads these raw files and produces the polished deliverables above. Agents must NOT write directly to deliverable paths — raw and synthesized output are separate.

Raw research files:

  • alternative-mapping.md
  • customer-intelligence.md
  • market-categories.md
  • trends-timing.md

Phase 3.5: Research Verification

After all positioning deliverables are written, run a verification pass.

Reference: Read references/verification-agent.md for the full verification protocol, universal checks, and skill-specific checks.

Process

  1. Spawn agent V1: Verification — it reads all deliverable files and checks for: unlabeled claims, internal contradictions, confidence rating consistency, missing data gaps, missing flags, stale data, and duplicate-source false corroboration
  2. V1 also runs startup-positioning-specific checks: positioning statement vs. research data, JTBD vs. customer intelligence, cross-deliverable coherence, validation test integrity
  3. V1 produces {project-name}/verification-report.md
  4. If Critical issues found: Pause and present issues to the user. Ask: fix first, or proceed as-is?
  5. If only Warnings/Info: Show one-line summary

In Claude.ai or when Agent tool is unavailable, run the verification checks yourself in the main conversation following the same protocol.


Honesty Protocol

Reference: Read references/honesty-protocol.md for full protocol and anti-pattern details.

Positioning is only useful if it's honest. Core rules apply (label claims, quantify, declare gaps), plus positioning-specific additions:

  1. No aspirational positioning. Position on what you ARE, not what you hope to become. Aspirational positioning crumbles at first customer contact.
  2. Challenge "we're unique." The Onliness Test must be genuinely convincing. If it reads like marketing fluff, iterate.
  3. Research wins over narrative. When customer data contradicts internal beliefs about positioning, the data wins.
  4. Flag category creation risk. Most startups can't afford to educate a market. Default to existing categories unless the evidence is overwhelming.
Anti-PatternWhat It Looks LikeWhat to Say
"We're for everyone"No target segment defined"If you're for everyone, you're for no one. Who cares MOST?"
Feature-based positioningLeading with features not outcomes"Customers don't buy features. What outcome do they get?"
Aspirational positioning"We'll be the AI-powered...""Position on what you deliver today, not the roadmap."
Category-of-oneInventing a category to avoid comparison"New categories cost millions. Is there an existing frame?"
Copycat positioningSame message as the market leader"Find genuinely different ground — you can't out-position the leader."

See references/honesty-protocol.md for the full anti-pattern table (7 entries) and detailed protocol.


Reference Files

Read only what you need for the current phase.

FileWhen to Read~LinesPurpose
honesty-protocol.mdStart of session~73Full honesty protocol with anti-patterns
research-principles.mdBefore starting Phase 2~65Source quality, cross-referencing, data gaps
research-wave-1-alternatives.mdWhen running Wave 1~235Agent templates for alternatives + customer intel
research-wave-2-market-frame.mdWhen running Wave 2~210Agent templates for categories + trends
research-synthesis.mdAfter both waves complete~380Synthesis protocol, Dunford process, validation tests, messaging implications
frameworks.mdDuring Phase 3~133Dunford/Moore/Neumeier/JTBD/Ries reference
research-scaling.mdAfter intake, before Phase 2~75Complexity scoring, tier definitions, wave configurations
verification-agent.mdAfter synthesis~80Verification protocol, universal + skill-specific checks

平台分布

Codex

37.99%
按下载量换算259

Claude

27.6%
按下载量换算188

Cursor

18.28%
按下载量换算124

Gemini CLI

8.91%
按下载量换算61

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执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/ferdinandobons/startup-skill --skill startup-positioning 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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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