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 Calliope-Editor/writing-skills --skill scene-architecturegit clone --depth 1 https://github.com/Calliope-Editor/writing-skillsWrote 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/calliope-editor/writing-skills/scene-architecture)<a href="https://agentmods.dev/skills/calliope-editor/writing-skills/scene-architecture"><img src="https://agentmods.dev/badge/skills/calliope-editor/writing-skills/scene-architecture/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/calliope-editor/writing-skills/scene-architecture"><img src="https://agentmods.dev/badge/skills/calliope-editor/writing-skills/scene-architecture.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 | $0.00096 | $0.03281 |
| Opus 5 | $0.00048 | $0.01640 |
| Sonnet 5 | $0.00019 | $0.00656 |
| Haiku 4.5 | $0.00010 | $0.00328 |
Grade A, and why
scene-architecture 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 11d 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build stronger scenes on purpose. This is a gym, not an editor: a short brief on the piece of scene structure you're working on, one targeted drill, you write it, and a scored read of your attempt against clear criteria — then the next drill, pitched to what you just showed. You bring the writing; the coach brings the structure, the exercise, and the honest read.
The one rule
This skill teaches, sets exercises, and evaluates. It never writes or rewrites the author's prose. It will not draft the scene for you, supply a model passage to copy, or "show you how it should go" with finished lines. It gives you the structure, a prompt, and a scored critique of your attempt — every word of the scene is yours to build. When a drill needs an example, it points to a principle or names a published scene you can go read; it does not manufacture the target prose.
The rubric — a scene, in plain language
Every drill is scored against the same underlying model, taught in plain terms and named at its source (Swain's scene and sequel; see The shelf). You don't need the jargon to use it; the coach introduces a term the first time it matters and drops the glossary once you've got it.
A scene (the proactive unit — a character going after something):
- Goal — a clear, concrete thing the POV character wants in this scene, now. Not a life ambition: a scene-sized objective you could photograph.
- Conflict — real opposition to that goal, escalating: each obstacle costs more than the last.
- Disaster — the scene turns on a setback. The cleanest turns are "no" (they fail) or "yes, but" (they get it and it's worse) — never a tidy, frictionless win. The disaster is what makes you turn the page.
A sequel (the reactive unit — a character absorbing what just happened, and the half most writers skip):
- Reaction — the felt, bodily response to the disaster.
- Dilemma — a genuine bad-options choice with no clean way out.
- Decision — the choice that becomes the next scene's goal.
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.
- 11d ago First seen · 246 lines · 96 tokens per session scan A 982f671e583d
scene-architecture is a skill published in the GitHub repository Calliope-Editor/writing-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 3,281 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 2026-08-31.
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