Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brainbytes-dev/everything-claude-marketing --skill product-positioninggit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/product-positioning)<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/product-positioning"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/product-positioning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/product-positioning"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/product-positioning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.02796 |
| Opus 5.5 | $0.00010 | $0.01118 |
| Sonnet 5.5 | $0.00005 | $0.00559 |
| Haiku 4.5 | $0.00002 | $0.00280 |
Grade A, and why
product-positioning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Positioning
When to Activate
- Launching a new product and need to define how it fits in the market
- Existing product positioning isn't resonating (sales struggles to explain value, customers are confused)
- Entering a new market or segment
- Repositioning after competitive landscape changes
- Preparing a go-to-market strategy and need the positioning foundation
- Sales team asks "how do we explain what we do?" and nobody gives the same answer
- Competitor launches a product that changes the category conversation
First Questions
- What do your best customers say when they describe your product to others?
- Who is your ideal customer? (Be specific — title, company size, situation)
- What were they doing before they found your product? (The real competitive alternative)
- What can you do that no alternative can? (Your unique capabilities)
- What is the measurable value customers get? (Time saved, revenue gained, cost reduced)
- What market category do customers put you in?
- Why do you win deals? Why do you lose them?
Geoffrey Moore's Positioning Statement
The Classic Framework
For [target customer]
who [statement of need or opportunity],
[product name] is a [product category]
that [key benefit / reason to buy].
Unlike [competitive alternative],
our product [primary differentiation].
Example
For mid-market SaaS companies
who struggle to predict customer churn before it happens,
RetainIQ is a customer intelligence platform
that identifies at-risk accounts 30 days before they cancel.
Unlike generic analytics tools,
our product uses behavioral AI trained specifically on
SaaS engagement patterns to deliver 89% prediction accuracy.
When to Use Moore's Framework
- Quick internal alignment on positioning basics.
- Starting point before deeper positioning work.
- Useful for early-stage companies with a clear product-market fit.
- Not sufficient for complex positioning decisions — use Dunford's framework for depth.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 281 lines · 24 tokens per session scan A 4def7a9f6315
product-positioning is a skill published in the GitHub repository brainbytes-dev/everything-claude-marketing (10 stars, last pushed 7mo ago), licensed MIT. It adds 24 tokens to every session and 2,796 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
product-positioning compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| product-positioningbrainbytes-dev/everything-claude-marketing | Skill | 10 | 7mo ago | MIT | A | 24 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |