Agent skill

Startup Positioning

by ferdinandobons in ferdinandobons/startup-skill

Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test.

MITAuto-check passedMarketing & SEO

Install Startup Positioning

skills CLI
$ npx skills add ferdinandobons/startup-skill --skill startup-positioning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ferdinandobons/startup-skill startup-positioning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ferdinandobons/startup-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/startup-positioning .claude/skills/startup-positioning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
startup-positioning
GitHub stars
1.2k
Token cost
~4.6k tokens
SKILL.md length
2,271 words
Files
9 (incl. references)
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test.

  • Works in 6 steps: Resume Check → Intake → 5: Research Depth Assessment → …
  • The user wants to define
  • SKILL.md covers How It Works, Phase 0: Resume Check, Phase 1: Intake and Phase 1.5: Research Depth…, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Startup Positioning is an agent skill from ferdinandobons/startup-skill. Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test. Produces a complete positioning document, positioning statement, competitive alternatives map, and market category analysis. Use when the user wants to define or refine their market positioning, find their unique position, differentiate from competitors, craft a positioning statement, choose a market category, or figure out "how should we position this product."…

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/frameworks.md`, `references/honesty-protocol.md` and `references/research-principles.md`).

It sits in Marketing & SEO, covering Positioning and messaging. The repository describes itself as: AI agent skills for startup validation, competitive intelligence, and planning. The licence is MIT.

When your agent uses it

  • The user wants to define
  • Refine their market positioning
  • Find their unique position
  • Differentiate from competitors

Example prompts

  • “how should we position this product.”
  • “positioning”
  • “how to position”
  • “/startup-positioning”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Resume Check
  2. Intake
  3. 5: Research Depth Assessment
  4. Research
  5. Positioning Synthesis
  6. 5: Research Verification

What it can do on your machine

Read from SKILL.md and the folder at commit a5f97c3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Startup Positioning loads about 4.6k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 243 tokens; SKILL.md has 2,271 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~243
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~19k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ferdinandobons/startup-skill at commit a5f97c3, republished under its MIT licence (© ferdinandobons). 2,271 words, ~4,636 tokens.

Download SKILL.mdSave it as .claude/skills/startup-positioning/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
startup-positioning
description
Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test. Produces a complete positioning document, positioning statement, competitive alternatives map, and market category analysis. Use when the user wants to define or refine their market positioning, find their unique position, differentiate from competitors, craft a positioning statement, choose a market category, or figure out "how should we position this product." Triggers for "positioning", "how to position", "market position", "differentiation strategy", "positioning statement", "competitive positioning", "category strategy", "where do we fit in the market", "how are we different", "unique value proposition", or any request to define, sharpen, or rethink positioning. Works standalone — no prior startup-design or startup-competitors session needed, but leverages their output if available.

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 sequential 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 0: Resume Check

Before anything else, check if a PROGRESS.md created by this skill exists in the working directory or a project subdirectory (the skill name field says startup-positioning). If it does, read it and resume from the last incomplete phase. Tell the user: "I found progress from a previous session. You completed [phases]. Picking up from [next phase]."

If no progress file exists — or the one found belongs to a different skill — start from Phase 1.


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 sequential research waves exploring competitive alternatives and market context — agents within a wave run in parallel, and Wave 2 builds on Wave 1's findings. 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.

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.

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.

Positioning is a reasoning problem, not a fill-in-the-blanks exercise. The "only" in the Onliness Test has to be true, and finding a frame where it's both true and valuable takes real thought — you're searching for the angle that makes the product's strengths matter most to the right buyer. Before committing to a frame, think hard about how each candidate category changes what the product gets compared against and whether the differentiation still holds. If the model supports extended thinking, this is where to spend it; a forced or generic position is worse than none.

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.

Show full SKILL.md (817 more words)Show less
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~419Synthesis protocol, Dunford process, validation tests, messaging implications
frameworks.mdDuring Phase 3~132Dunford/Moore/Neumeier/JTBD/Ries reference
research-scaling.mdAfter intake, before Phase 2~96Complexity scoring, tier definitions, wave configurations
verification-agent.mdAfter synthesis~128Verification protocol, universal + skill-specific checks

© ferdinandobons, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in startup-positioning of ferdinandobons/startup-skill.

  • SKILL.md
  • references/frameworks.md
  • references/honesty-protocol.md
  • references/research-principles.md
  • references/research-scaling.md
  • references/research-synthesis.md
  • references/research-wave-1-alternatives.md
  • references/research-wave-2-market-frame.md
  • references/verification-agent.md

Open the folder on GitHubat commit a5f97c3

Compare with similar skills

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Research Brandonvoyage-ai/gtm-engineer-skills1.3k—~1.3kAutomated safety check: PassMIT

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Categories

Questions about Startup Positioning

What does Startup Positioning do?

Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test. Startup Positioning is an agent skill from ferdinandobons/startup-skill. Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test.

When should I use Startup Positioning?

Startup Positioning fits situations like: the user wants to define; refine their market positioning; find their unique position; differentiate from competitors.

How do I install Startup Positioning in Claude Code?

Run `npx skills add ferdinandobons/startup-skill --skill startup-positioning -a claude-code`. Or copy the skill folder (startup-positioning in ferdinandobons/startup-skill) into .claude/skills/startup-positioning in your project. Claude Code loads it when a task matches its description.

How do I install Startup Positioning in Codex?

Run `npx skills add ferdinandobons/startup-skill --skill startup-positioning -a codex`. Or copy the skill folder (startup-positioning in ferdinandobons/startup-skill) into .agents/skills/startup-positioning in your project. Codex loads it when a task matches its description.

Can I use Startup Positioning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ferdinandobons/startup-skill --skill startup-positioning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/startup-positioning, .gemini/skills/startup-positioning, .github/skills/startup-positioning and .opencode/skills/startup-positioning in your project.

What does Startup Positioning need to run?

SKILL.md names no scripts, command-line tools or credentials: Startup Positioning is instructions for the agent only.

Does Startup Positioning access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Startup Positioning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Startup Positioning use?

Startup Positioning is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Startup Positioning use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 15k tokens, read only when the agent opens those files.

What are the alternatives to Startup Positioning?

Skills that share tags, products or a category with Startup Positioning: Marketing Os (Yuzzyuk/marketing-os, 536 stars), Revenue Centric Design (heliocosta-dev/revenue-centric-design, 740 stars), Stanley Druckenmiller Investment (tradermonty/claude-trading-skills, 3k stars) and B2b Playbook (weilun88313/B2B-Playbook, 203 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Startup Positioning?

ferdinandobons (a GitHub user) maintains it in ferdinandobons/startup-skill, which has 1,176 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on July 1, 2026.

Source: ferdinandobons/startup-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.