methodology-sample-flow-extractor-zh

methodology-sample-flow-extractor-zh is a skill for Claude Code, Codex from gy910210/hermes-research-skills. It costs 97 tokens per session (1,002 once invoked), scanned A, original, MIT.

A research tool that reads papers, appendices, and official technical pages to record how training data is made, how training is staged, and which prompts, templates, ratios, and losses are disclosed.

In plain words
What is it for?
Use it to compare training methods, map how samples move through training stages, collect public prompt or template examples, and build reusable experiment plans.
Why use it?
It removes the need to manually compare scattered implementation details across many sources. It also separates published facts from details that the source does not reveal.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to compare training methods, map how samples move through training stages, collect public prompt or template examples, and build reusable experiment plans.

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Install with agentmods
npx agentmods add skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh
Install

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.

Any agent
npx skills add gy910210/hermes-research-skills --skill methodology-sample-flow-extractor-zh
Clone the repo
git clone --depth 1 https://github.com/gy910210/hermes-research-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for methodology-sample-flow-extractor-zh

README.md
[![agentmods](https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh/github.svg)](https://agentmods.dev/skills/gy910210/hermes-research-skills/methodology-sample-flow-extractor-zh)
Your own site
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agentmods 80×15 button for methodology-sample-flow-extractor-zh

Your own site · 80×15
<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>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,002 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash 5645e8626dd5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/methodology-sample-flow-extractor-zh/SKILL.md · 95 lines

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_filesread_filewrite_filepatchsession_searchdelegate_taskcronjobbrowserweb/searchvision
  • 若正文提到 references/...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
  • focus
    • sample_flow
    • public_prompt_evidence
    • loss_stack
    • stagewise_training
    • industrial_result_mapping
  • granularity
    • paper_card
    • comparison_table
    • execution_template

输出

  • methodology_packet
    • task_and_scene
    • raw_data_objects
    • token_objects
    • stagewise_sample_flow
    • training_targets
    • loss_stack
    • public_prompt_evidence
    • disclosed_ratios
    • undisclosed_gaps
    • industrial_results
  • method_comparison_rows[]
  • illustrative_examples[]

工作流

  1. 先判断论文属于哪一类:
    • tokenizer / SID
    • generative retrieval/search
    • recommendation backbone
    • reranking / control
    • training system / serving
  2. 优先抽“对象定义”,再抽“怎么训练”:
    • raw tables / raw logs
    • sample object
    • token object
    • list object
  3. 再按阶段抽取:
    • Stage A tokenizer / SID
    • Stage B backbone supervision
    • Stage C alignment / preference
    • Stage D online refresh / serving coupling
  4. 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
  5. 把没有公开的地方显式记成:
    • 未披露
    • 摘要级可知
    • appendix 可知
  6. 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。

Read the full file on GitHub · 95 lines

Changes

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.

  1. 11d ago First seen · 95 lines · 97 tokens per session scan A 5645e8626dd5

Subscribe to this mod's changes

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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