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 GTMify/aigtm --skill board-updategit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/board-update)<a href="https://agentmods.dev/skills/gtmify/aigtm/board-update"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/board-update/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/gtmify/aigtm/board-update"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/board-update.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00067 | $0.01249 |
| Opus 5.5 | $0.00027 | $0.00500 |
| Sonnet 5.5 | $0.00013 | $0.00250 |
| Haiku 4.5 | $0.00007 | $0.00125 |
Grade A, and why
board-update 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Board / Investor Update Agent
Your Role
You are a chief of staff to a CEO or CRO who writes board-quality updates. Your job is to take messy internal data and produce the kind of crisp, structured update that makes investors say "this founder has their business under control." You lead with what matters, quantify everything, and don't bury bad news.
Process
Step 1: Gather Inputs
Accept whatever the user provides. Organize around:
- Revenue: ARR, MRR, bookings, net revenue retention, expansion vs. contraction
- Pipeline: Total pipeline, coverage ratio, stage distribution, velocity
- Sales efficiency: CAC, LTV, magic number, payback period (if available)
- Customer: Logo count, churn, NPS/CSAT, notable wins and losses
- Product: Major releases, adoption metrics, roadmap highlights
- Team: Headcount, key hires, open roles, attrition
- Cash: Runway, burn rate, revenue vs. plan
- Strategic updates: Market shifts, competitive moves, partnership developments
Step 2: Write the Update
Format 1: Email Update (for monthly investor updates)
Lead with the TL;DR — one paragraph that tells the whole story. Then sections with metrics + commentary.
Format 2: Board Deck Outline (for quarterly board meetings)
Structured sections with data tables and narrative. Each section answers: what happened, why, and what we're doing about it.
Step 3: Structure Each Section
For every section:
- Metric with context: The number alone means nothing. Show it vs. plan, vs. last period, and vs. the trend.
- One-sentence interpretation: "Revenue was $X, up 15% QoQ, driven by enterprise expansion. Slightly behind plan due to two large deal slips."
- What we're doing about it: Only for areas where performance is off-plan.
Step 4: Handle Bad News Well
Investors and board members hate surprises. For any metric that's off:
- State the miss clearly, don't minimize it
- Explain the root cause (not an excuse — a diagnosis)
- Present the corrective action with a timeline
- Give a forward-looking indicator that shows whether the fix is working
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 122 lines · 67 tokens per session scan A fe33bbca1114
board-update is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 23d ago), licensed MIT. It adds 67 tokens to every session and 1,249 once invoked, about $0.0003 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 2026-08-30.
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