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-dialoguegit 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-dialogue)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-writing-dialogue"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-writing-dialogue/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-dialogue"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-writing-dialogue.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 | $0.00091 | $0.01665 |
| Opus 5 | $0.00046 | $0.00833 |
| Sonnet 5 | $0.00018 | $0.00333 |
| Haiku 4.5 | $0.00009 | $0.00167 |
Grade A, and why
s4h-writing-dialogue 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing: Dialogue
Dialogue fails in two primary ways: it says exactly what it means (no subtext), or it explains things the characters already know (exposition dressed as conversation). Both failures produce the same effect on the reader — a sense of flatness, of the author's hand visible, of characters becoming mouthpieces rather than people.
Real conversation is oblique. People in conflict rarely say "I'm angry with you." They talk about something else. The anger is present in what they say about the dishes, the schedule, the way someone looks. The subtext is the scene — the surface conversation is the vehicle for it. When dialogue is on the nose, the subtext and the surface are the same thing, which means there is no scene — only information delivery.
Voice differentiation is the second major failure point. Every character has a distinct rhythm of thought, a vocabulary range shaped by their history, evasion patterns specific to their wound, and a relationship to silence. When characters sound interchangeable, the dialogue's only differentiator is the attribution ("he said / she said") — which means the characters, on the page, don't exist yet.
Your Process
Step 1: Speaker Goals — Surface vs. Subtext For each speaker in the exchange, identify:
Framing check: Confirm the specific dialogue before continuing. State what you've identified — the exchange being analysed, the speakers involved, and the apparent dramatic situation — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the dialogue, its speakers, and the situation it takes place in]. 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
- Surface goal: What they appear to be talking about
- Subtext goal: What they actually want from this exchange (what they won't say directly)
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 · 125 lines · 91 tokens per session scan A 75af2f2625a7
s4h-writing-dialogue is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 1,665 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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