FIT is an enterprise AI development framework with a multilingual function engine, a flow orchestration engine, and Java tools for connecting language models, knowledge bases, and external tools. It is for Java-oriented teams building AI applications that can run locally or in distributed deployments with plugins. The catalogue add-ons provide commands, skills, instructions, and settings for working with FIT.
Borrowing it
Nothing to install: this file belongs to ModelEngine-Group/fit-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ModelEngine-Group/fit-framework/main/.agents/skills/release/SKILL.mdgit clone --depth 1 https://github.com/ModelEngine-Group/fit-frameworkWrote 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/modelengine-group/fit-framework/release)<a href="https://agentmods.dev/skills/modelengine-group/fit-framework/release"><img src="https://agentmods.dev/badge/skills/modelengine-group/fit-framework/release/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/modelengine-group/fit-framework/release"><img src="https://agentmods.dev/badge/skills/modelengine-group/fit-framework/release.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 | $0.00057 | $0.00427 |
| Opus 5.5 | $0.00023 | $0.00171 |
| Sonnet 5.5 | $0.00011 | $0.00085 |
| Haiku 4.5 | $0.00006 | $0.00043 |
Grade A, and why
release 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 2mo 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
版本发布
执行标准化的版本发布流程。不含构建验证，不含自动推送。
参数
<version>: 发布版本号，格式为 X.Y.Z（必需）
执行步骤
-
解析并验证参数: 版本号必须匹配 X.Y.Z 格式，确认 SNAPSHOT 存在。
-
确认工作区状态: 工作区必须干净（无未提交更改）。
-
全局替换 SNAPSHOT -> Release: 将
X.Y.Z-SNAPSHOT替换为X.Y.Z。 排除目录:.agents/,.ai-workspace/,.claude/,.codex/,.gemini/,.opencode/ -
创建 Release commit:
git add -A && git commit -m "Release X.Y.Z" -
创建轻量标签:
git tag vX.Y.Z -
创建发布分支:
git branch release-X.Y.Z -
回退当前分支:
git reset --hard HEAD~1 -
替换为下一 SNAPSHOT:
X.Y.Z-SNAPSHOT->X.Y.(Z+1)-SNAPSHOT -
创建 SNAPSHOT commit:
git add -A && git commit -m "Prepare the next SNAPSHOT version" -
输出总结: 包含发布信息和后续手动操作指引。
注意事项
- 工作区必须干净
- 不会自动推送，所有操作仅在本地
- 建议发布前已完成
mvn clean install验证
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.
- 2mo ago First seen · 42 lines · 57 tokens per session scan A c2a96680cf97
release is a skill published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 7mo ago), licensed MIT. It adds 57 tokens to every session and 427 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
finish
Completing a development branch for merge readiness. Use when implementation and tests pass and the branch needs formal preparation for review and merge.
rebase
Focused rebase against a target branch. Use when you need to update a feature branch with upstream changes. Stops on conflicts — does not auto-resolve. Extended mode adds autonomous conflict resolution and test-fix loop.
checkpoint
Save a checkpoint — bump version, commit, push. Use when work is complete and ready to ship without the full finish protocol.
bump
Bumping project version and updating changelog atomically. Use when releasing a new version — patch, minor, or major.
worktree
Managing git worktrees for isolated parallel development. Use when creating branches, setting up agent worktrees, or cleaning up after merges.
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.