create-release-note

A release-note generator that collects changes from GitHub pull requests, commits, and issues, then groups them into a project-formatted summary.

In plain words
What is it for?
Use it to prepare notes for patch or minor releases and optionally create a GitHub draft release for human review.
Why use it?
It removes the need to manually track and organize everything that changed between software versions.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/modelengine-group/fit-framework/create-release-note
Any agent
npx skills add ModelEngine-Group/fit-framework --skill create-release-note
Clone the repo
git clone --depth 1 https://github.com/ModelEngine-Group/fit-framework

Made for: Claude Code, Codex.

Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 445 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00068 $0.00445
Opus 5 $0.00034 $0.00222
Sonnet 5 $0.00014 $0.00089
Haiku 4.5 $0.00007 $0.00044

Measured 2d ago against content hash 53dc7f1a947e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-release-note 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 2d 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.

.agents/skills/create-release-note/SKILL.md · 44 lines

What it actually says

生成 Release Notes

自动从 PR、commit 和 Issue 中收集变更信息,按模块和类型分类,生成符合项目格式的 Release Notes。

参数

  • <version>: 当前发布版本号,格式为 X.Y.Z(必需)
  • <prev-version>: 上一版本号(可选,不提供则自动推断)

执行流程

步骤 1-3:公共步骤

  1. 解析参数并验证版本号格式(X.Y.Z)
  2. 确定版本范围(当前 tag 和上一 tag)
  3. 判断版本类型: PATCH == 0 走合并路径,PATCH > 0 走常规路径

合并路径(x.y.0 版本)

从 GitHub 已发布的 release 中合并前一 minor 系列的所有 release notes。

常规路径(x.y.z, z > 0)

  1. 收集两个 tag 之间合并的 PR 和直接 commit
  2. 收集关联的 Issue
  3. 按模块分组(FIT/FEL/Waterflow/AI Config)
  4. 按类型分组(Enhancement/Bugfix/Documentation)
  5. 生成格式化的 Release Notes

公共步骤

  1. 展示并确认,询问用户是否调整
  2. 创建 GitHub Draft Release:
    gh release create v<version> --title "v<version>" --notes-file /tmp/release-notes-v<version>.md --draft
    

注意事项

  • 需要 gh CLI 且已认证
  • Tag 必须已存在(通常由 release skill 完成)
  • 创建的是 Draft Release,需人工审核后发布
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. 2d ago First seen · 44 lines · 68 tokens per session scan A 53dc7f1a947e

Subscribe to this mod's changes

create-release-note is a skill published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 5mo ago), licensed MIT. It adds 68 tokens to every session and 445 once invoked, about $0.0003 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.

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