Borrowing it
Nothing to install: this file belongs to ChouChiu/heya-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ChouChiu/heya-skill/v2/AGENTS.mdgit clone --depth 1 https://github.com/ChouChiu/heya-skillWrote 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/instructions/chouchiu/heya-skill/agents-md)<a href="https://agentmods.dev/instructions/chouchiu/heya-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/chouchiu/heya-skill/agents-md/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/instructions/chouchiu/heya-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/chouchiu/heya-skill/agents-md.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 | $0.01318 | $0.01318 |
| Opus 5.5 | $0.00527 | $0.00527 |
| Sonnet 5.5 | $0.00264 | $0.00264 |
| Haiku 4.5 | $0.00132 | $0.00132 |
Grade A, and why
heya-skill AGENTS.md 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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Bilibili creator "黑鸦" title style generator — CLI pipeline + AI skill output.
Runtime
- Bun only. Every command uses
bun. No npm/pnpm/yarn. bun run <script>for package.json scripts,bun testfor tests.#!/usr/bin/env bunshebang onsrc/index.ts.
Commands
bun install # install deps (bun.lock)
bun run check # biome check . && tsc --noEmit
bun run format # biome check --write .
bun test # run all tests
bun test -t <pattern> # filter by test name regex
bun run pipeline # full pipeline: fetch → analyze → generate
bun run pipeline --skip-fetch --skip-analyze --dry-run
bun run docs # typedoc → docs/ (gitignored)
Order matters: bun run check before bun test. CI enforces this.
Pipeline
3 phases: fetch (UApi Bilibili proxy) → analyze (HanLP REST + deterministic aggregation) → generate (template substitution).
Fetch uses uapi-sdk-typescript — no Bilibili cookie or WBI signing needed. HanLP REST required for analysis; skip with --skip-analyze.
SKILL.md generation
- Template:
SKILL.template.md— the canonical source. Edit this file. - Output:
skills/heya-title-style/SKILL.md— auto-generated from template + analysis, committed. This is the deployed agent skill artifact. - AUTO sections: Content between
<!-- AUTO_START:xxx -->/<!-- AUTO_END:xxx -->is replaced by pipeline for these 4 sections:core-features,title-examples,vocab-library,structure-formulas. Thecore-guidancesection has template fallback text but is NOT replaced by pipeline. Never edit AUTO sections in the output file. - Reference data:
skills/heya-title-style/references/is auto-generated.00-llm-brief.md— compact LLM-readable summary01-titles.csv— raw video titles02-style-analysis.yaml— structured analysis data02-style-analysis.md— human-readable analysis report03-title-features.json— per-title debug data; never load wholesale into LLM context
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.
- 2mo ago First seen · 110 lines · 1,318 tokens per session scan A a893dbe5410c
heya-skill AGENTS.md is an instructions file published in the GitHub repository ChouChiu/heya-skill (19 stars, last pushed yesterday), licensed MIT. It adds 1,318 tokens to every session, about $0.0053 per session on Opus 5.5. 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.
heya-skill AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| heya-skill AGENTS.mdChouChiu/heya-skill | Instructions file | 19 | yesterday | MIT | A | 1,318 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |