docs(readme): list the new release map among the analyzers

The 28th deterministic map (release_map: version, scheme, changelog and
release automation) shipped but the README still said 27 and left it out
of the module rundown. Sync both the EN and CN copies.

Author: he-yufeng

README.md

@@ -194,7 +194,7 @@ CodeABC/
 │   │   ├── cache.py          # SQLite cache + on-disk project library
 │   │   ├── codemap_export.py # Stitch every map into one offline codemap.md
 │   │   ├── report_export.py  # Self-contained offline HTML report
-│   │   └── …                 # + 27 deterministic, no-API-key analyzers (one per map)
+│   │   └── …                 # + 28 deterministic, no-API-key analyzers (one per map)
 │   └── prompts/
 │       ├── overview.py      # Project overview prompt
 │       ├── annotate.py      # Line-by-line annotation prompt
@@ -211,13 +211,13 @@ CodeABC/
 └── README.md
 ```
 
-The `services/` analyzers are one module per deterministic map: `coverage`, `symbols`, `datamodels`, `settings_map`, `schedules`, `ci_checks`, `entrypoints`, `commands`, `envscan`, `dependencies`, `integrations`, `error_handling`, `techdebt`, `docs`, `complexity`, `churn`, `activity`, `ownership`, `licenses`, `security`, `risk`, `health_score`, `apimap`, `glossary`, `filenames`, `package_purposes`, and `action_plan`.
+The `services/` analyzers are one module per deterministic map: `coverage`, `symbols`, `datamodels`, `settings_map`, `schedules`, `ci_checks`, `release_map`, `entrypoints`, `commands`, `envscan`, `dependencies`, `integrations`, `error_handling`, `techdebt`, `docs`, `complexity`, `churn`, `activity`, `ownership`, `licenses`, `security`, `risk`, `health_score`, `apimap`, `glossary`, `filenames`, `package_purposes`, and `action_plan`.
 
 ## Roadmap
 
 ### Shipped
 
-The reading experience is already complete end to end: a plain-language project manual, hover annotations, a terminology dictionary, natural-language editing, and snippet Q&A, all in a bilingual UI you launch with one command (or as a native Tauri desktop app). On top of that sit a dozen deterministic, no-API-key maps — reading map, core-module ranking, a project-wide definition index with find-all-references (look up any name to jump to where it's declared and list every place it's used), test coverage, git-history hotspots and ownership, tech-debt markers, env-var surface, entry points, CLI commands, the data-model shapes a project declares (dataclasses, pydantic models, TypedDicts and NamedTuples, with their fields and types), the tunable settings hard-coded as UPPER_SNAKE constants (retry counts, timeouts, default model, feature flags — the values you might change without reading the code), the scheduled and automated tasks a project runs on its own (cron jobs, APScheduler/Celery beat timers, GitHub Actions schedules and JS timers — what fires without you pressing anything, with common cron expressions glossed into plain language), the CI quality gates a change has to pass on push or pull request (the lint, formatting, type-check, test, coverage, security and build steps wired up in GitHub Actions, pre-commit, GitLab CI, CircleCI, Jenkins and friends, each labelled in plain language so a red check stops being scary), external integrations, silent-failure spots, under-documented files, and logic complexity. It all exports offline too: every map stitches into a single `codemap.md`, or a self-contained HTML report you can email to a non-technical stakeholder — no server, no API key, nothing fetched from the network. Analyses also persist to a small on-disk library (`GET /api/projects`), so you can list past projects and reopen one without remembering its id or re-scanning.
+The reading experience is already complete end to end: a plain-language project manual, hover annotations, a terminology dictionary, natural-language editing, and snippet Q&A, all in a bilingual UI you launch with one command (or as a native Tauri desktop app). On top of that sit a dozen deterministic, no-API-key maps — reading map, core-module ranking, a project-wide definition index with find-all-references (look up any name to jump to where it's declared and list every place it's used), test coverage, git-history hotspots and ownership, tech-debt markers, env-var surface, entry points, CLI commands, the data-model shapes a project declares (dataclasses, pydantic models, TypedDicts and NamedTuples, with their fields and types), the tunable settings hard-coded as UPPER_SNAKE constants (retry counts, timeouts, default model, feature flags — the values you might change without reading the code), the scheduled and automated tasks a project runs on its own (cron jobs, APScheduler/Celery beat timers, GitHub Actions schedules and JS timers — what fires without you pressing anything, with common cron expressions glossed into plain language), the CI quality gates a change has to pass on push or pull request (the lint, formatting, type-check, test, coverage, security and build steps wired up in GitHub Actions, pre-commit, GitLab CI, CircleCI, Jenkins and friends, each labelled in plain language so a red check stops being scary), how the project ships releases (where the current version lives, which versioning scheme it follows, whether there's a changelog, and whether pushing a tag or cutting a release auto-publishes to PyPI / npm / GitHub Release), external integrations, silent-failure spots, under-documented files, and logic complexity. It all exports offline too: every map stitches into a single `codemap.md`, or a self-contained HTML report you can email to a non-technical stakeholder — no server, no API key, nothing fetched from the network. Analyses also persist to a small on-disk library (`GET /api/projects`), so you can list past projects and reopen one without remembering its id or re-scanning.
 
 ### Planned
 

README_CN.md

@@ -190,7 +190,7 @@ npm run tauri:dev
 
 ### 已交付
 
-阅读体验已经完整跑通：大白话项目说明书、悬停批注、术语词典、自然语言编辑、片段问答，全部在双语界面里，一条命令就能启动（也可以打包成 Tauri 原生桌面应用）。在这之上是十几张无需 API Key 的确定性图谱：阅读路线、核心模块排序、全项目定义索引（查任何名字，跳到它的定义处、并列出所有用到它的地方）、测试覆盖、Git 历史热点与代码归属、技术债标记、环境变量清单、程序入口、命令行命令、数据模型形状（dataclass / pydantic / TypedDict / NamedTuple 及其字段类型）、写死成全大写常量的可调设置（重试次数、超时、默认模型、开关——不读代码也能改的那些值）、会自己定时跑的自动化任务（cron 定时、APScheduler / Celery beat 定时器、GitHub Actions 定时与 JS 定时器——不用你按按钮就会发生的那些，常见 cron 表达式还翻成大白话）、提交代码后会自动跑的检查（push 或开 PR 时，GitHub Actions、pre-commit、GitLab CI、CircleCI、Jenkins 等里配的代码规范、格式、类型、测试、覆盖率、安全、构建这些关卡，每一道都翻成大白话，红叉不再吓人）、外部依赖、错误被吞点、最缺文档的文件，还有逻辑复杂度。这些还能离线导出：所有图谱可以拼成一份 `codemap.md`，或者一份自包含的 HTML 报告，直接发给不懂技术的同事或老板——不用起服务、不用 API Key、不从网上拉任何东西。分析结果还会存进一个小的本地项目库（`GET /api/projects`），可以列出以前分析过的项目、重开其中一个，不用记住它的 id、也不用再扫一遍。
+阅读体验已经完整跑通：大白话项目说明书、悬停批注、术语词典、自然语言编辑、片段问答，全部在双语界面里，一条命令就能启动（也可以打包成 Tauri 原生桌面应用）。在这之上是十几张无需 API Key 的确定性图谱：阅读路线、核心模块排序、全项目定义索引（查任何名字，跳到它的定义处、并列出所有用到它的地方）、测试覆盖、Git 历史热点与代码归属、技术债标记、环境变量清单、程序入口、命令行命令、数据模型形状（dataclass / pydantic / TypedDict / NamedTuple 及其字段类型）、写死成全大写常量的可调设置（重试次数、超时、默认模型、开关——不读代码也能改的那些值）、会自己定时跑的自动化任务（cron 定时、APScheduler / Celery beat 定时器、GitHub Actions 定时与 JS 定时器——不用你按按钮就会发生的那些，常见 cron 表达式还翻成大白话）、提交代码后会自动跑的检查（push 或开 PR 时，GitHub Actions、pre-commit、GitLab CI、CircleCI、Jenkins 等里配的代码规范、格式、类型、测试、覆盖率、安全、构建这些关卡，每一道都翻成大白话，红叉不再吓人）、这个项目是怎么发版本的（当前版本号写在哪、用的哪种版本号规则、有没有更新日志、一推 tag 或发 release 时会不会自动发布到 PyPI / npm / GitHub Release）、外部依赖、错误被吞点、最缺文档的文件，还有逻辑复杂度。这些还能离线导出：所有图谱可以拼成一份 `codemap.md`，或者一份自包含的 HTML 报告，直接发给不懂技术的同事或老板——不用起服务、不用 API Key、不从网上拉任何东西。分析结果还会存进一个小的本地项目库（`GET /api/projects`），可以列出以前分析过的项目、重开其中一个，不用记住它的 id、也不用再扫一遍。
 
 ### 后续规划