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 event4u-app/agent-config --skill gtm-launchgit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/gtm-launch)<a href="https://agentmods.dev/skills/event4u-app/agent-config/gtm-launch"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/gtm-launch/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/event4u-app/agent-config/gtm-launch"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/gtm-launch.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 | $0.00044 | $0.02079 |
| Opus 5 | $0.00022 | $0.01040 |
| Sonnet 5 | $0.00009 | $0.00416 |
| Haiku 4.5 | $0.00004 | $0.00208 |
Grade A, and why
gtm-launch 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 9d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gtm-launch
When to use
- A product, feature, or major capability is approaching ship-readiness and the team needs a wave plan (alpha → beta → GA) keyed to audience and proof, not a date on a calendar.
- A launch is being planned date-first; the team needs to invert and plan readiness-first so an unmet gate stops a wave instead of leaking past it.
- A previous launch landed soft and the retro names "no audience-by-wave logic" or "narrative beats unclear per wave" as the cause.
Do NOT use to write announcement copy (route to release-comms),
lock the message stack (route to messaging-architecture), or plan
post-launch retention loops (route to retention-loops).
Cognition cluster
- Mental model 10 — Reversible vs. irreversible decisions. A GA
wave is largely irreversible: rolling back narrative and audience
expectations after public launch costs more than re-shipping the
product. Alpha and beta are reversible; treat them as the
decision-quality buffer. See
docs/contracts/mental-models.md§ 10. - Mental model 29 — Premortem. Before the wave plan locks, write
the post-mortem of the launch as if it failed. The premortem
surfaces the gates that need to hold; the wave plan is the inverse
of that list. See
mental-models.md§ 29. - Mental model 16 — Leading vs. lagging indicators. Engineering-
readiness signals (error rate, latency, support-load) are leading;
pipeline lift is lagging. A wave plan that gates on lagging signals
ships into a soft floor. See
mental-models.md§ 16. - Context-spine — product + customer-segment + channel-stage.
Read the product slot for shippable scope, the
customer-segment slot for who hears the launch on which wave,
and the channel-stage slot for where each wave's audience lives
in the awareness → decision arc. See
context-spine.
Procedure
Step 0: Inherit the message stack
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.
- 9d ago First seen · 175 lines · 44 tokens per session scan A b9339daeeddb
gtm-launch is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 2,079 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 2026-09-03.
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