trellis-finish-work

结束当前会话：质量门确认、提醒提交、归档任务并写入开发者 journal。

核心说明

以下为上游 SKILL.md 摘要（英文原文结构保留要点）：

Finish Work

Wrap up the current session: archive the active task (and any other completed-but-unarchived tasks the user wants to clean up) and record the session journal. Code commits are NOT done here — those happen in workflow Phase 3.4 before you invoke this command.

Step 1: Survey current state

python3 ./.trellis/scripts/get_context.py --mode record

This prints:

• My active tasks — review whether any besides the current one are actually done (code merged, AC met) and should be archived this round.
• Git status — quick visual on what's dirty.
• Recent commits — you'll need their hashes in Step 4 for --commit.

If --mode record surfaces other completed tasks not tied to the current session, surface them to the user with a one-shot confirmation: "These N tasks look done — archive them too in this round? [y/N]". Default is no; the current active task is always archived in Step 3 regardless.

Step 2: Sanity check — classify dirty paths

Run:

git status --porcelain

Filter out paths under .trellis/workspace/ and .trellis/tasks/ — those are managed by add_session.py and task.py archive auto-commits and will appear dirty as part of this skill's own work.

For each remaining dirty path, decide whether it belongs to the current task or to other parallel work (e.g., another terminal window editing the same repo). Heuristics:

• Paths referenced in the current task's prd.md / implement.jsonl / check.jsonl → current task
• Paths in code areas matching the task's stated scope, or that you remember editing this session → current task
• Paths in unrelated areas you have no recollection of touching this session → other parallel work

Then route:

• Any remaining path looks like current-task work — bail o

安装

随 Trellis 一并分发。执行 trellis init 后可在 .agents/skills/trellis-finish-work/（及各平台 skill 目录）使用。

npm install -g @mindfoldhq/trellis@latest
trellis init -u your-name

来源：mindfold-ai/Trellis · .agents/skills/trellis-finish-work