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 gy910210/hermes-research-skills --skill methodology-sample-flow-extractor-zhgit clone --depth 1 https://github.com/gy910210/hermes-research-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/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh)<a href="https://agentmods.dev/skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh"><img src="https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh/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/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh"><img src="https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh.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 | $0.00097 | $0.01002 |
| Opus 5 | $0.00048 | $0.00501 |
| Sonnet 5 | $0.00019 | $0.00200 |
| Haiku 4.5 | $0.00010 | $0.00100 |
Grade A, and why
methodology-sample-flow-extractor-zh 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hermes 适配说明
- 本 skill 现面向 Hermes 使用,优先依赖 Hermes 原生工具:
search_files、read_file、write_file、patch、session_search、delegate_task、cronjob、browser、web/search、vision。 - 若正文提到
references/...或scripts/...,优先读取当前 skill 目录下对应文件,不再依赖 Claude 专属目录结构。 - 原始 Claude
agents/openai.yaml不作为执行前提;需要并行研究、分工精读或角色评审时,改用 Hermes 的delegate_task。 - 保留原有研究方法论与产物契约,但执行层统一按 Hermes 工具体系落地。
Methodology Sample Flow Extractor(中文)
这个 skill 负责抽取“方法怎么做”,尤其是:
- 训练样本怎么构造;
- 分几个阶段;
- 哪些是公开 prompt / template;
- 哪些比例和规则公开了,哪些没有。
它不是普通 paper-reader-zh 的替代,而是一个更偏“实验与实现结构”的专用抽取器。
何时使用
- 你要做“训练方式 / 样本流”专题。
- 你想把多篇论文的 methodology 放到统一模板里比较。
- 你想知道论文有没有公开 prompt、appendix template、task mixture、sample ratio。
- 你想产出方法例子集、实验设计模板、样本构造路线图。
输入
sources[]- 论文、PDF、appendix、官方技术页
focussample_flowpublic_prompt_evidenceloss_stackstagewise_trainingindustrial_result_mapping
granularitypaper_cardcomparison_tableexecution_template
输出
methodology_packettask_and_sceneraw_data_objectstoken_objectsstagewise_sample_flowtraining_targetsloss_stackpublic_prompt_evidencedisclosed_ratiosundisclosed_gapsindustrial_results
method_comparison_rows[]illustrative_examples[]
工作流
- 先判断论文属于哪一类:
- tokenizer / SID
- generative retrieval/search
- recommendation backbone
- reranking / control
- training system / serving
- 优先抽“对象定义”,再抽“怎么训练”:
- raw tables / raw logs
- sample object
- token object
- list object
- 再按阶段抽取:
Stage Atokenizer / SIDStage Bbackbone supervisionStage Calignment / preferenceStage Donline refresh / serving coupling
- 识别是否存在公开 prompt / template:
- 正文里的 instruction 示例
- appendix 表格里的 prompt template
- figure / pseudo-template
- 把没有公开的地方显式记成:
未披露摘要级可知appendix 可知
- 如果用户要求例子集,可在论文支持范围外补
illustrative example,但必须明确标注为示意,不得冒充论文原文。
守护
- 不把“方法直觉”写成“论文披露的实现细节”。
- 对 prompt/template 尤其保守:只有公开正文/附录稳定可见时,才记为公开证据。
- 对 ratio、filtering threshold、sampling policy,只要没看到原文,就写
未披露。 - 对工业收益,不做跨论文强行横比;只记录论文公开写出的结果。
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 · 95 lines · 97 tokens per session scan A 5645e8626dd5
methodology-sample-flow-extractor-zh is a skill published in the GitHub repository gy910210/hermes-research-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 97 tokens to every session and 1,002 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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