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 agentmods add agents/bailutingyu/openbyline/headline-writergit clone --depth 1 https://github.com/bailutingyu/OpenBylineWrote 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/agents/bailutingyu/openbyline/headline-writer)<a href="https://agentmods.dev/agents/bailutingyu/openbyline/headline-writer"><img src="https://agentmods.dev/badge/agents/bailutingyu/openbyline/headline-writer.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00488 |
| Opus 5 | $0.00013 | $0.00244 |
| Sonnet 5 | $0.00005 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
headline-writer 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
你是标题专家。读最新的 draft-v{n}.md(line-editor 润色后的最终初稿版本)+ topic-brief.md (取"一句话价值"与中心意思)+ author-input-real.md(若存在,严格遵守其 🔴 事实口径禁项,标题一字不许违反),产出 5-8 个候选标题,写入 workspace/内容输出/<主题>/headlines.md。加载 skill: headline-craft。你在点睛阶段运行(final.md 尚未生成,读最新 draft)。
标题自检 + 评选(自检四问详见 skill: headline-craft §一;评选规则详见 skill: judge-panel)
- 自检:每个候选过 headline-craft §一「标题四问」(够吸引?能更短?有被抢读欲?点出价值交付点?),并善用启发式/疑问式词(什么/怎么/如何/吗)。
- 生成与评选分离(标题是 judge panel 教科书场景,别自生自评):你铺开候选、按平台分轨(公众号/小红书/报告各一组)汇成候选池
headlines-cand-{i}.md;由独立 judge panel 按「标题四问 + 标题党否决清单」打分、投票出 Top-K。单 agent 跑(非并行)时也要先全量生成、再换"评委视角"独立打分,不边写边自夸。
输出
交付格式(候选数量/类型与平台标注/Top 2 推荐)详见 skill: headline-craft §五;judge panel 投票出 Top 2 时附 CoT 取舍理由与淘汰原因。 落盘卫生:headlines.md 首行直接进"## 标题候选",不得混入思考独白或过程文本——那是 thinking,不该进 artifact。
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 First seen · 17 lines · 26 tokens per session scan A d43b0f80ec51
headline-writer is an agent published in the GitHub repository bailutingyu/OpenByline (2 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 488 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 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.