chore: migrate from opencode to trellis 0.5.0-rc.6
- Remove legacy .opencode/ directory and configuration - Update .trellis/ to v0.5.0-rc.6 structure - Refactor scripts: modularize common/, remove multi_agent/ - Add new common modules: git.py, io.py, log.py, types.py, etc. - Update workflow.md and AGENTS.md - Archive completed migration tasks
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# Local Workflow System
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`.trellis/workflow.md` is the Trellis workflow source of truth inside the user project. An AI does not need Trellis source code to understand how the current project should move tasks forward; this file is enough.
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## File Responsibilities
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`.trellis/workflow.md` has three responsibilities:
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1. **Explain workflow phases**: Plan, Execute, Finish.
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2. **Define skill routing**: which skill or agent the AI should use when the user expresses a certain intent.
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3. **Provide workflow-state prompt blocks**: hooks can inject the prompt block for the current state into the conversation.
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## Current Phase Model
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```text
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Phase 1: Plan -> clarify what to build, produce prd.md and required research
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Phase 2: Execute -> implement against the PRD and specs, then check
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Phase 3: Finish -> final verification, preserve lessons, and wrap up
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```
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Each phase contains numbered steps, such as `1.3 Configure context`. These numbers are not runtime fields in `task.json`; they are workflow structure for AI and humans to read.
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## Skill Routing
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`workflow.md` separates routing by platform capability:
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- Platforms with sub-agent support: dispatch `trellis-implement` by default for implementation and `trellis-check` for checking.
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- Platforms without sub-agent support: the main session reads skills such as `trellis-before-dev`, then executes directly.
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When changing local AI behavior, update the routing descriptions in `workflow.md` first, then check whether the corresponding platform skill, command, or agent files need to stay in sync.
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## Workflow-State Prompt Blocks
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The bottom of `workflow.md` can contain state blocks like this:
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```text
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[workflow-state:no_task]
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...
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[/workflow-state:no_task]
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```
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Hooks choose the right block based on current task status and inject it into the conversation. Common states include:
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| State | Meaning |
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| --- | --- |
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| `no_task` | The current session has no active task. |
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| `planning` | The task is still in requirements, research, or context configuration. |
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| `in_progress` | The task has entered implementation and checking. |
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| `completed` | The task is complete and waiting for wrap-up or archive. |
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If the user wants to change policies such as "whether to create a task when there is no task," "when task creation may be skipped," or "whether sub-agents are required," edit these state blocks and the routing table above them.
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## Local Modification Patterns
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Common changes:
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| Goal | Edit point |
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| --- | --- |
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| Add a phase | Update the Phase Index, phase body, routing, and state blocks. |
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| Change task creation policy | Update the `no_task` state block and Phase 1 description. |
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| Change the default implementation/check path | Update Phase 2 and skill routing. |
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| Change the wrap-up flow | Update Phase 3 and `finish-work` related descriptions. Note the current split: Phase 3.4 = AI-driven code commits (batched, user-confirmed), Phase 3.5 = `/finish-work` (archive + record session). `/finish-work` refuses to run if the working tree is dirty. |
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| Change platform differences | Update routing descriptions grouped by platform. |
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After editing, make the AI reread `.trellis/workflow.md`; do not assume the flow from the old conversation is still valid.
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## Relationship To Platform Files
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`workflow.md` is the semantic center of the local workflow, but each platform can also have its own entry files:
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- skills, such as `trellis-brainstorm` and `trellis-check`.
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- commands/prompts/workflows, such as continue and finish-work.
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- hooks, such as session-start or workflow-state injection.
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If only `workflow.md` changes, platform entry files may still contain old language. When the user wants to change "what the AI actually does," also inspect the relevant platform directory.
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