task-forest

1# Task Forest
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3## Purpose
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5Maintain the current workspace's task structure, proposals, history, and progress. Produce one standalone HTML deliverable that a first-time reader can understand without opening another task list or internal file.
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7Use the user's language for task content, proposals, reports, and HTML. Default to Chinese when unknown.
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9## Portability
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11This skill is agent-agnostic. Install the whole `task-forest` directory in any host-supported skill location, then resolve scripts, references, and assets from the directory containing this `SKILL.md`. Do not assume a specific agent name, skill root, home-directory layout, shell, path separator, or operating system.
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13Use an available Python 3 launcher on the host (`python3`, `python`, or `py -3`). The scripts use the Python standard library and support macOS, Linux, and Windows. To label task history with the calling agent, set `COMPASS_AGENT_NAME` or `AGENT_NAME`, or pass `--actor`; otherwise the neutral value `agent` is used.
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15## Core Rules
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171. Read and write task-forest data only through `scripts/task_forest.py`; never hand-edit `.agent-workbench/task-forest/` canonical files.
182. Use one primary `child_of` parent per node, `contributes_to` for secondary ownership, and `depends_on` for prerequisites.
193. Save graph changes as a proposal and wait for user confirmation before `proposal-apply --yes`.
204. Keep low-confidence inference in a question or proposal. Record material execution drift as a deviation.
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