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 gtmagents/gtm-agents --skill land-adopt-expand-blueprintgit clone --depth 1 https://github.com/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/land-adopt-expand-blueprint)<a href="https://agentmods.dev/skills/gtmagents/gtm-agents/land-adopt-expand-blueprint"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/land-adopt-expand-blueprint/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/gtmagents/gtm-agents/land-adopt-expand-blueprint"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/land-adopt-expand-blueprint.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 | $0.00019 | $0.00267 |
| Opus 5 | $0.00010 | $0.00133 |
| Sonnet 5 | $0.00004 | $0.00053 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
land-adopt-expand-blueprint 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 12d 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.
What it actually says
Land-Adopt-Expand Blueprint Skill
When to Use
- Designing success plans for enterprise SaaS accounts.
- Aligning revenue, product, and CS teams on phased adoption metrics.
- Auditing current accounts to identify expansion triggers or risks.
Framework
- Stakeholder Matrix – map economic, technical, and champion roles per phase.
- Milestone Ladder – land (business case, pilot), adopt (activation, value proof), expand (multi-product, exec advocacy).
- Signal Library – telemetry + qualitative indicators that unlock stage gates.
- Governance Cadence – EBR/QBR schedule, exec sponsors, escalation paths.
- Action Playbook – recommended plays, assets, and enablement per milestone.
Templates
- Success plan table with phases, KPIs, owners, and timelines.
- Exec summary slide for internal standups.
- Risk/mitigation log tied to each phase.
Tips
- Tie stage gates to measurable outcomes, not just time-based milestones.
- Share blueprint with customers to co-author success plans.
- Pair with
build-land-adopt-expand-planfor account-specific automation.
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.
- 12d ago First seen · 31 lines · 19 tokens per session scan A 436832f08236
land-adopt-expand-blueprint is a skill published in the GitHub repository gtmagents/gtm-agents (399 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 19 tokens to every session and 267 once invoked, about $0.0001 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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