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 varunk130/ai-gtm-skill-library --skill launch-commandgit clone --depth 1 https://github.com/varunk130/ai-gtm-skill-libraryWrote 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/varunk130/ai-gtm-skill-library/launch-command)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/launch-command"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/launch-command.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.02513 |
| Opus 5 | $0.00024 | $0.01256 |
| Sonnet 5 | $0.00010 | $0.00503 |
| Haiku 4.5 | $0.00005 | $0.00251 |
Grade A, and why
launch-command 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 7d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Launch Command (IGNITE Protocol)
A comprehensive launch orchestration engine that coordinates eight cross-functional workstreams through four progressive gates, producing a quantified readiness dashboard and executable launch day runbook. IGNITE ensures nothing ships without verified readiness across every dimension that determines launch success.
When to Use
- Preparing for a product launch and need structured readiness tracking
- Running a go/no-go decision meeting and need objective scoring
- Coordinating multiple teams toward a shared launch date
- Building a launch day runbook with hour-by-hour execution plan
- Assessing whether a launch is ready to proceed or needs to slip
- Post-gate review to identify workstreams that are falling behind
- Transitioning from build phase to market-facing execution
What You'll Need
Critical inputs (ask if not provided):
- Product name, target launch date, and launch type (GA, beta, feature, major release)
- Target audience and market segment definitions
- Positioning and messaging framework (from position-lock)
- Sales enablement status and materials inventory
- Marketing campaign plan and channel strategy (from demand-engine)
- Analytics and measurement framework (from launch-pulse)
Nice-to-have:
- Competitive landscape analysis (from battle-scanner)
- Partner readiness status (from partner-blueprint)
- Community/PLG strategy (from community-catalyst)
- Budget allocation plan (from budget-allocator)
- Customer journey maps (from journey-architect)
- Previous launch debriefs and lessons learned
Process
Step 1: Define the Eight Launch Workstreams
Each workstream represents a critical dimension of launch readiness. Assign an owner and define 5-10 criteria per workstream.
| # | Workstream | Owner Role | Weight | Description |
|---|---|---|---|---|
| 1 | Product | Product/Engineering | 20% | Feature completeness, stability, performance, documentation |
| 2 | Positioning | Product Marketing | 15% | Messaging locked, value props validated, differentiation clear |
| 3 | Sales Enablement | Sales/Revenue | 15% | Battle cards, talk tracks, demo environments, pricing approved |
| 4 | Marketing | Marketing/Demand Gen | 15% | Campaigns built, content ready, channels activated, PR queued |
| 5 | Partners | Partnerships | 10% | Partner communications, co-marketing assets, integration tested |
| 6 | Community/PLG | Growth/Community | 10% | Self-serve flow tested, community seeded, PLG hooks live |
| 7 | Operations | Ops/Support | 10% | Support trained, SLAs defined, escalation paths, billing ready |
| 8 | Analytics | Data/Analytics | 5% | Dashboards live, tracking verified, baselines captured, alerts set |
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.
- 7d ago First seen · 183 lines · 48 tokens per session scan A 6560909b34fd
launch-command is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (5 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 2,513 once invoked, about $0.0002 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 2026-08-31.
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