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 product-announcementgit 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/product-announcement)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/product-announcement"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/product-announcement/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/varunk130/ai-gtm-skill-library/product-announcement"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/product-announcement.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 | $0.00056 | $0.01146 |
| Opus 5.5 | $0.00022 | $0.00458 |
| Sonnet 5.5 | $0.00011 | $0.00229 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
product-announcement 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 1mo 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Announcement (HERALD Protocol)
Generate coordinated, multi-channel product launch communications that tell a consistent story across every audience and platform.
When to Use
- New product launches
- Major feature announcements
- Platform/pricing changes
- Partnership announcements
- Milestone announcements
What You'll Need
Critical inputs (ask if not provided):
- What is being announced (product, feature, partnership)
- Launch date
- Target audience(s)
Nice-to-have:
- Position Lock output (messaging hierarchy)
- Battle Scanner output (competitive context)
- Approved quotes from executives/customers
Process
Step 1: HERALD Framework
Structure the announcement across 6 layers:
| Layer | What It Covers | Key Output |
|---|---|---|
| Headline | The headline story -- why this matters to the world | 1 sentence that would make someone stop scrolling |
| Echo | Persona-specific angles on the same announcement | 3-5 message variants by audience |
| Reach | All announcement materials across channels | Full asset list below |
| Align | Internal alignment and stakeholder coordination | Stakeholder sign-off checklist |
| Launch | Timed release across channels for maximum impact | Hour-by-hour launch day plan |
| Distribute | Success metrics per channel and overall | KPI dashboard |
Step 2: Big Idea Distillation
Create the announcement hierarchy:
- Internal headline (what we're really doing): 1 sentence, no jargon
- External headline (what customers care about): 1 sentence, benefit-led
- Press headline (what media would write): 1 sentence, newsworthy angle
- Social hook (what gets engagement): 1 sentence, provocative or surprising
All 4 must tell the same story from different angles.
Step 3: Multi-Channel Asset Creation
Generate content for each channel:
| Asset | Length | Tone | Key Element |
|---|---|---|---|
| Press release | 400-600 words | Formal, newsworthy | Quote from CEO + customer |
| Blog post | 800-1200 words | Educational, excited | Problem-solution narrative |
| Email to customers | 200-300 words | Direct, valuable | What it means for THEM |
| Email to prospects | 150-250 words | Compelling, CTA-driven | Why they should care NOW |
| Social posts (LinkedIn) | 150-200 words | Professional, insightful | Hot take or data point |
| Social posts (X/Twitter) | 280 chars | Punchy, shareable | The one-liner version |
| Internal announcement | 300-500 words | Celebratory, informative | What, why, and what's next |
| Sales enablement brief | 1 page | Tactical, action-oriented | Talk track + FAQ + CTA |
| Partner notification | 200-300 words | Collaborative, opportunity-focused | What it means for them |
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.
- 1mo ago First seen · 104 lines · 56 tokens per session scan A 484f805db01a
product-announcement is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 10d ago), licensed MIT. It adds 56 tokens to every session and 1,146 once invoked, about $0.0002 per session on Opus 5.5. 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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