Getting it into your agent
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npx skills add beingsmit/technical-product-gtm --skill positioning-strategygit clone --depth 1 https://github.com/beingsmit/technical-product-gtmWrote 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/beingsmit/technical-product-gtm/positioning-strategy)<a href="https://agentmods.dev/skills/beingsmit/technical-product-gtm/positioning-strategy"><img src="https://agentmods.dev/badge/skills/beingsmit/technical-product-gtm/positioning-strategy/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/beingsmit/technical-product-gtm/positioning-strategy"><img src="https://agentmods.dev/badge/skills/beingsmit/technical-product-gtm/positioning-strategy.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 | $0.00055 | $0.03146 |
| Opus 5 | $0.00028 | $0.01573 |
| Sonnet 5 | $0.00011 | $0.00629 |
| Haiku 4.5 | $0.00006 | $0.00315 |
Grade A, and why
positioning-strategy 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 10d 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.
This is a copy
97% identical to gtm-positioning-strategy — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Positioning Strategy
Find and own a defensible market position. Turn generic messaging into clear differentiation — or at least test whether your differentiation actually resonates before committing to it.
When to Use
Triggers:
- "Our messaging sounds exactly like competitors"
- "Brand awareness is strong but conversion is weak"
- "Sales team can't explain why we're different"
- "Buyers see us as interchangeable"
- "Should we reposition before we rebrand?"
- "How do we test positioning claims?"
Context:
- Competitive markets with similar offerings
- Messaging that isn't converting
- New product launches
- Repositioning existing products
- Sales team reports buyer confusion
Core Frameworks
1. One Word Can Change Everything (The "Autonomous" Problem)
The Pattern:
Early enterprise conversations for an autonomous AI product. Positioned as "autonomous AI agent."
Developers: "Cool, but scary." Managers: "Will this replace our team?" Deal progression: Slow. Lots of "we'll think about it."
The Change:
One word: "autonomous" → "AI teammate"
Same product. Same capabilities. Different framing.
Result:
Developers: "This helps me." Managers: "This makes my team more productive." Deal progression: Measurably faster.
Why This Matters:
Positioning isn't what you do. It's what you don't say.
We could've said "replaces developers" (technically true for some tasks). Would've killed every enterprise deal.
The Framework: Word Choice Shapes Buyer Psychology
Words that scare enterprises:
- Autonomous (implies: no control, replacing humans)
- Replaces (threatens: job security)
- Fully automated (removes: human judgment)
- AI-first (means: unclear, buzzword)
Words that convert:
- Teammate (implies: collaboration, helping)
- Augments (helps: makes humans better)
- You stay in control (reassures: human oversight)
- Handles repetitive work (specific: saves time)
How to Test Word Choice:
Don't guess. Test.
Test 1: Outbound Email A/B
- Send 100 prospects Version A ("autonomous agent")
- Send 100 prospects Version B ("AI teammate")
- Measure: Reply rate, meeting booked rate
- Signal strength: High (real buyer intent)
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.
- 10d ago First seen · 440 lines · 55 tokens per session scan A b3b522fb2db3
positioning-strategy is a skill published in the GitHub repository beingsmit/technical-product-gtm (42 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 3,146 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to gtm-positioning-strategy, differing in 5 lines, and is treated as a copy.
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