oh-story-claudecode is a skill package for planning, analyzing, and writing Chinese web fiction, covering both short and long novels. It is intended for writers using Claude Code, Codex, OpenClaw, and other supported AI-agent environments, with workflows for market research, story breakdowns, drafting, editing, and cover creation. The catalogue entries are the package's skills, commands, agents, and plugin.
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.
git clone --depth 1 https://github.com/zenstory-ai/oh-story-claudecodeWrote 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/commands/zenstory-ai/oh-story-claudecode/story-cover)<a href="https://agentmods.dev/commands/zenstory-ai/oh-story-claudecode/story-cover"><img src="https://agentmods.dev/badge/commands/zenstory-ai/oh-story-claudecode/story-cover/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/commands/zenstory-ai/oh-story-claudecode/story-cover"><img src="https://agentmods.dev/badge/commands/zenstory-ai/oh-story-claudecode/story-cover.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 | $0.00018 | $0.00047 |
| Opus 5 | $0.00009 | $0.00023 |
| Sonnet 5 | $0.00004 | $0.00009 |
| Haiku 4.5 | $0.00002 | $0.00005 |
Grade A, and why
story-cover scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
请使用 story-cover skill，帮助我分析和生成网文封面图。
用户参数：$ARGUMENTS
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.
- 4d ago Changed · +2 lines 1f4bb36a0995
- 13d ago First seen · 6 lines · 18 tokens per session scan A 67fe93c0a0bc
story-cover is a command published in the GitHub repository zenstory-ai/oh-story-claudecode (6,780 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 47 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
story-review
A command for reviewing a piece of writing from several opposing viewpoints, using multiple agents to assess and score it.
story-setup
A command prompt for deploying the basic tools and infrastructure for online-fiction writing. The instruction is written in Chinese and refers to a separate story-setup skill.
story-short-write
A command for writing short online fiction, from the first idea through a finished story.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.