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 agent-first-pagesgit 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/agent-first-pages)<a href="https://agentmods.dev/skills/calliope-editor/writing-skills/agent-first-pages"><img src="https://agentmods.dev/badge/skills/calliope-editor/writing-skills/agent-first-pages/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/agent-first-pages"><img src="https://agentmods.dev/badge/skills/calliope-editor/writing-skills/agent-first-pages.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 | $0.00079 | $0.02945 |
| Opus 5 | $0.00039 | $0.01473 |
| Sonnet 5 | $0.00016 | $0.00589 |
| Haiku 4.5 | $0.00008 | $0.00295 |
Grade A, and why
agent-first-pages 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 12d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Put the opening in front of a simulated literary agent reading cold from the slush pile — and get the verdict, request or pass, with the real reason behind it.
The one rule
This skill reads and judges. It never writes or rewrites the author's prose. It tells the writer where the agent's attention dropped and why the pass came; it does not rewrite the hook or punch up the first line. The honest read is the value — a fixed page would just hide the problem the writer needs to see.
Intake — you don't need a polished query
You don't have to arrive with a logline, comps, or any query-letter polish. Open however you like — paste the first pages and ask "would an agent keep reading?", say "here's my opening, be brutal," or just drop the chapter in. Framing the market read is the skill's job, not yours.
Its first reply orients you in two quick moves: a one-line map of what's about to happen (a cold slush read → a page-by-page reaction → a verdict with the honest why), then a light intake it needs to put the pages on the right desk:
- Genre and category — thriller, literary, upmarket, romance, MG, YA, adult. This decides whose desk it lands on: a literary agent and a thriller agent request and pass on different things, so the read is only fair if it's calibrated to the market you're actually querying. If you're unsure, it will infer a best guess from the pages and name it, so you can correct it.
- How much to read — the classic agent unit is the first five pages (~1,250 words) or the first chapter. Hand it whatever you'd paste into a query form; it reads only as far as the writing earns.
Then it reads. You set the market; you never have to diagnose the problem — that's what the read is for.
The desk it lands on
A query doesn't go to "an agent" in the abstract. It goes to one specific desk, and agent taste is narrow and personal — the skill simulates a single agent who actually represents your genre and category, reading with that market's norms and that list's appetite. This matters two ways:
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.
- 12d ago First seen · 115 lines · 79 tokens per session scan A 9bad5f8b0672
agent-first-pages is a skill published in the GitHub repository Calliope-Editor/writing-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 2,945 once invoked, about $0.0004 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.
Other skills, from other repositories
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story-deslop
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A novel-cover generator that creates a cover with the book title and author name. It chooses a visual style from the book information and can use Codex's image-generation tool.