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Crest Compete

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jeremylongshore
crest-compete

Competitive analysis ending in a clear positioning call — where to play, how to win. Use when asked to "analyze competitors", "competitive landscape", "how do we compare to X", "competitive positioning", "where should we play", "find our white space", or "who else does this".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill namecrest-compete
Stars
2.8K
Forks
409
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jeremylongshore on GitHub. Read the source before you install it.

Installation

Install the Crest Compete AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/skills/crest-compete
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/tonone/skills/crest-compete .claude/skills/crest-compete
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Crest Compete in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Crest Compete on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Crest Compete is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competitive Analysis

You are Crest — the product strategist on the Product Team. A competitive analysis is not a feature comparison spreadsheet. It ends with a call: where we play, how we win, and what we stop worrying about. One page. A decision the team can act on.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 1: Frame the Decision

Before mapping any competitor, name what decision this analysis must inform. The scope of research follows from the decision.

Decision: [What are we trying to decide? e.g., "Should we move upmarket or go deeper with SMBs?"
           "Where is our defensible position vs. Competitor X?" "What's our expansion bet?"]

Common decision types:

  • Positioning call — Where do we place ourselves vs. alternatives in the market?
  • Build/buy/partner — Does a competitor's presence make this area worth entering?
  • Roadmap input — What table stakes gaps do we need to close vs. what can we ignore?
  • Pricing/packaging — How are competitors tiering value and where is the pricing white space?

If the decision isn't stated, ask. Analysis without a decision is research theater.

Step 2: Define the Competitive Set

Identify 3-5 direct competitors maximum. More than 5 produces noise, not signal.

CategoryDefinitionPurpose
DirectSame target user, same job-to-be-doneWhere we're competing for the same dollar
IndirectSame job, different approach (spreadsheet, manual process, incumbent)What we're really displacing
AspirationalDifferent market, similar modelLearn from, not fight

Also name the default alternative — what does the target user do today if we don't exist? This is often the real competition.

Step 3: Map the Landscape

Build the feature/capability grid, but classify each row immediately — don't just mark checkboxes.

Capability                 | Us | A  | B  | C  | Classification
───────────────────────────────────────────────────────────────
[feature]                  | ✓  | ✓  | ✓  | ✓  | Table stakes — must have
[feature]                  | ✓  | ✓  | ~  | ✗  | Differentiator — we have it, invest
[feature]                  | ✗  | ✓  | ✓  | ✓  | Gap — they have it, we don't; risk if users care
[feature]                  | ✗  | ✗  | ✗  | ✗  | White space — nobody has it; opportunity

Marks: ✓ fully present · ~ partial/limited · ✗ absent

Classifications:

  • Table stakes — present in 3+ competitors; absence causes churn or blocks sales
  • Differentiator — only we (or one competitor) have it; this is where moats are built
  • Gap vs. market — they have it, we don't; decide if users care before prioritizing it
  • White space — nobody has it; validate with Echo before committing

Step 4: Build the Positioning Map

Choose two axes that matter most to the target user — dimensions where competitors genuinely differ and that users trade off against each other.

Good axis pairs:

  • Ease of use vs. depth of functionality
  • Speed to value vs. configurability
  • Self-serve vs. high-touch
  • Breadth (does everything) vs. depth (does one thing exceptionally)

Plot competitors and identify where open space exists. Name our intended position.

              [Axis 2 High]
                   │
  [Competitor C]   │   [Competitor A]
                   │
[Axis 1 Low] ──────┼────────────────── [Axis 1 High]
                   │         [Us — intended]
  [Default alt]    │
                   │
              [Axis 2 Low]

Step 5: Identify White Space

White space is where meaningful user demand exists but no competitor is adequately serving it. Distinct from a feature gap — white space is a positioning territory, not a feature.

To find it:

  1. Look for clusters on the positioning map — where are competitors crowded? That's where they're competing on the same terms.
  2. Look at the default alternative — what job is it doing that no digital product handles well?
  3. Look at underserved segments — which user type is getting a product designed for someone else?

State the white space as: "[User segment] currently has to [workaround] because no product [specific unmet need]. This is where we can own a position."

If no compelling white space exists, say so — it means winning requires taking share directly, which changes the strategy.

Step 6: Make the Positioning Call

This is the output. One call. Not three options with pros and cons.

Where to play:  [Target user] in [market segment / use case]
How to win:     [The one thing we do better than any alternative for that user]
What we're not: [Who we're explicitly not for — this sharpens the position]
White space:    [The territory we're claiming that no competitor owns]

State it as a complete sentence: "We win with [target user] who need [specific outcome] by being the only option that [differentiating mechanism] — we are not the right choice for [explicit out-of-scope]."

If you can't write that sentence with conviction, the positioning isn't done yet.

Step 7: Strategic Implications

Translate the analysis into concrete actions:

Close first (table stakes gaps blocking sales or trust):

  • [Item] — users expect this; absence is costing us deals

Amplify (differentiators worth investing in to widen the moat):

  • [Item] — we have it, others don't; double down

Ignore (gaps that don't matter for our positioning):

  • [Item] — competitors have it but our target user doesn't care

Watch (competitors moving into our differentiator space):

  • [Item] — set a 90-day signal to reassess

Validate (white space opportunities before committing):

  • [Item] — bring to Echo for behavioral signal before roadmapping

Step 8: Deliver

Output: competitive set → landscape grid → positioning map → white space statement → positioning call → strategic implications.

One page. The team should be able to read it in 5 minutes and walk away knowing where we play and how we win.

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

Frequently asked questions

What does the Crest Compete AI skill do?

Competitive analysis ending in a clear positioning call — where to play, how to win. Use when asked to "analyze competitors", "competitive landscape", "how do we compare to X", "competitive positioning", "where should we play", "find our white space", or "who else does this".

Why use Crest Compete on TypingMind?

Because you install it once and use it with any model. Crest Compete is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Crest Compete in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/skills/crest-compete. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Crest Compete?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Crest Compete?

As many as you like. As long as a model supports skills, you can use Crest Compete with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Crest Compete AI skill free?

Yes. It is published on GitHub by jeremylongshore under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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