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 human-avatar/skills-for-humanity --skill s4h-writing-executive-summarygit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-writing-executive-summary)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-writing-executive-summary"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-writing-executive-summary/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/human-avatar/skills-for-humanity/s4h-writing-executive-summary"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-writing-executive-summary.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 | $0.00102 | $0.01715 |
| Opus 5 | $0.00051 | $0.00857 |
| Sonnet 5 | $0.00020 | $0.00343 |
| Haiku 4.5 | $0.00010 | $0.00171 |
Grade A, and why
s4h-writing-executive-summary 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing: Executive Summary
Executive summaries fail when they summarise the document rather than answering the reader's question. A summary of a 40-page analysis is not what an executive needs. They need: what is the situation, what are the three things most important to know, what does it mean for their decision, and what should happen next. In that order. In one page.
The fundamental principle: the executive is not the end reader of your analysis — they are a decision-maker who needs the output of your analysis in a form that enables action. The detail, the methodology, the full data — that stays in the main document. The executive summary gives them what they need to act without reading the full document.
Four common failures:
- Summarising the process, not the answer: "We conducted a comprehensive analysis of three market segments, reviewing 47 data sources over 8 weeks." The executive doesn't need to know how long it took — they need to know what it found.
- Findings without implications: Stating what happened without stating what it means for the decision at hand.
- False balance: Including minor findings to be thorough, diluting the signal with noise. Three things that matter are better than twelve things that range from critical to marginal.
- Passive language on the recommendation: "It may be worth considering..." — the executive summary is where the recommendation is made, not hedged.
Your Process
Step 1: Reader's Role and Actual Decision Who exactly is reading this? What is the specific decision they need to make? Not "the board should be informed" but "the board is deciding whether to approve the $2M market expansion budget." This decision frames everything: what gets included, what gets cut, and how the recommendation is framed.
Framing check: Confirm the reader and their decision before continuing. State what you've identified — the specific audience, their role, and the exact decision they are making — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of who the reader is and what decision they need to make]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different situation than read; incorporate the correction before proceeding
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 · 117 lines · 102 tokens per session scan A 292fa181d5c5
s4h-writing-executive-summary is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 102 tokens to every session and 1,715 once invoked, about $0.0005 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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