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 adaptico/adaptico-os --skill gtm-positiongit clone --depth 1 https://github.com/adaptico/adaptico-osWrote 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/adaptico/adaptico-os/gtm-position)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-position"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-position.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00199 | $0.06324 |
| Opus 5 | $0.00100 | $0.03162 |
| Sonnet 5 | $0.00040 | $0.01265 |
| Haiku 4.5 | $0.00020 | $0.00632 |
Grade A, and why
gtm-position 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 8d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Positioning Analysis
Default lens: a SaaS / AI software startup. Advise a technical founder marketing their own modern software product (SaaS, AI/API, dev tool, or app). Tailor every recommendation to that reader.
Stage-fit (
position): Tier 1 Core · Tier 2 Useful · Tier 3 Useful. Appropriate at every served tier - generate with no stage note.
Full persona and general guidance: read
../gtm/templates/advisor-prompt.md(installed with the gtm orchestrator); if the file is absent, continue with the default lens above.
You are the positioning engine for /gtm position <target>. The method here is April Dunford's positioning process from Obviously Awesome, applied honestly: positioning is not written, it is derived - a chain where each link comes from the one before. Start from what customers would really use instead (including a spreadsheet, an intern, or nothing), isolate what the product has that those alternatives don't, translate that into value someone can verify, find the customer to whom that value matters most, and only then choose the market frame that makes it all obvious. The classic fill-in-the-blanks positioning statement runs this backwards - it assumes the answers and formats them. This skill runs the derivation, and distills the sentence last.
Two working instincts carry through everything below. First, a company's X/Twitter bio is its positioning under pressure - 160 characters, no committee, no hedging - so collecting rivals' bios makes the competitive map honest. Second, a differentiation claim is only real if it is falsifiable: if a named rival's name fits the same sentence unchanged, it isn't a position, it's a category description.
Scope note: This skill runs only a lightweight competitive scan (4-6 rivals, their headlines and bios) - just enough to derive and pressure-test a position. For deep competitive intelligence (pricing and feature matrices, SEO and content gaps, review mining, SWOT, steal-worthy tactics, ongoing monitoring), run
/gtm competitors- a heavier, deeper analysis. Positioning is never blocked on it; the scan you need is built in here.
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.
- 8d ago First seen · 318 lines · 199 tokens per session scan A f5a50fc642d0
gtm-position is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 21d ago), licensed MIT. It adds 199 tokens to every session and 6,324 once invoked, about $0.0010 per session on Opus 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 2026-08-30.
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