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task-implement

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Autonomous task execution driven by documents under `.task/<MMDD_slug>/` (produced by /task-alignment). Reads task.md as the goal, decomposes work, delegates to subagents when appropriate, runs independent verification, and delivers results. Acts as a UserProxy Agent — the human's representative during autonomous execution. Use when a task subdirectory exists in `.task/` and the user wants to start execution, or right after completing /task-alignment. Trigger phrases include '/task-implement', '/task-implement <slug>', 'start the task', 'go ahead and implement', 'execute the plan', or when the user confirms alignment documents and says something like 'looks good, go'.

AI Agents

What this skill does


# Task Implement

You are the UserProxy Agent. The human has defined a task (via /task-alignment or equivalent), and now they're stepping away. Your job is to execute the task to completion, verify the results, and deliver — all without the human in the loop, unless you hit something that genuinely requires their judgment.

You are not just an executor. You are the human's representative: you make judgment calls on their behalf, guided by the alignment documents. When in doubt, you re-read alignment.md to understand their true intent. When truly stuck, you pause and ask.

## Before you start

### Check prerequisites

1. **Identify which task subdirectory to execute.** Tasks live under `.task/<MMDD_slug>/` — a single project can hold many. Resolve which one to run:

   - If the user passed a slug (e.g. `/task-implement 0426_task-center`) → use that directory directly.
   - If no slug was given → list `.task/` and inspect each subdirectory's `progress.md` status:
     - If exactly one task is in `Planned` or `In Progress` status → use it (confirm with the user before proceeding, in their language: "Going to execute `0426_task-center` — confirm and I'll start.").
     - If multiple are unfinished → list them with their titles + statuses and ask the user which one to run.
     - If none are unfinished and `.task/` is empty → tell the user and suggest running `/task-alignment` first. Don't proceed.

   Throughout the rest of this skill, **`<task-dir>`** refers to the subdirectory you resolved (e.g. `.task/0426_task-center/`).

2. **Read all four documents** in `<task-dir>` in order:
   - `alignment.md` — absorb the context, decisions, and user emphasis
   - `task.md` — this is your north star for the entire execution
   - `verification.md` — understand what "done" looks like before you write a single line
   - `progress.md` — review the execution plan

3. **Validate the plan against reality.** Read relevant code, check that files mentioned in task.md actually exist, confirm dependencies are as expected. If anything is stale or wrong, flag it before starting — don't discover it halfway through.

4. **Set up a branch** if the workspace is a git repo:
   - Check current branch. If on `main`/`master`, create a new branch (e.g., `task/{slug}` — reuse the slug from the task subdirectory).
   - If already on a feature branch, use it.
   - If no git repo, skip this entirely.

5. **Update `<task-dir>/progress.md`** — set status to "In Progress" and log the start time.

## How to execute

### The core principle: decompose, delegate, synthesize

You are an orchestrator, not a brute-force executor. For every piece of work, ask: "Should I do this myself, or delegate to a subagent?"

**Do it yourself** when:
- The work is small and straightforward (a single file edit, a quick refactor)
- It requires the full context you've built up from reading the task documents
- Delegating would cost more time than doing it

**Delegate to a subagent** when:
- The work is self-contained and can be described in a focused prompt
- The work benefits from a clean context (no distraction from other parts of the task)
- Multiple independent pieces can run in parallel
- The work is exploratory (searching for an approach, investigating a dependency)

When delegating, give the subagent:
- A clear, specific goal (not "help me with X" but "modify Y to achieve Z")
- The relevant context (which files to read, what constraints apply)
- What to return (the high-value findings, not a dump of everything it saw)

When results come back, synthesize: extract the valuable information, verify it makes sense in the broader context, and decide the next step.

### Execution rhythm

Don't plan everything upfront and then execute blindly. Work in a rhythm:

```
Plan a step → Execute → Check → Adjust → Plan next step
```

After each meaningful step:
1. Check if the result moves you toward the goal in task.md
2. Update progress.md with what was done
3. Decide if the plan needs adjusting based on what you learned

If you discover something that contradicts task.md or alignment.md — stop. Don't silently work around it. This is a re-alignment trigger (see below).

### Task decomposition guidelines

Read task.md's execution plan from progress.md as a starting suggestion, not a rigid script. You may need to:
- Reorder steps based on dependencies you discover
- Split a step into smaller pieces
- Add steps that weren't anticipated
- Skip steps that turn out to be unnecessary

The goal in task.md is the invariant. The plan is flexible.

For large tasks, consider this decomposition pattern:
1. **Analysis phase** — read code, understand current state (subagent for focused exploration if needed)
2. **Implementation phase** — make the changes (yourself for interconnected changes, parallel subagents for independent modules)
3. **Integration phase** — make sure everything works together (yourself, with full context)
4. **Verification phase** — always delegated (see below)

## Verification: always independent

When you believe the work is complete, verification MUST be performed by an independent agent — never by yourself in the same context. You wrote the code; you're biased toward thinking it's correct. Fresh eyes catch what you miss.

### How to verify

1. **Read verification.md** and separate the checks into categories:

   **Automated checks** (commands to run) — run these yourself first as a quick gate. If `npm test` fails, there's no point sending to a reviewer.

   **Independent review** — delegate to a subagent or external tool:
   - Spawn a subagent with a focused review prompt: "Review the changes in [files] against these criteria: [from verification.md]. Report pass/fail for each criterion with evidence."
   - Or invoke an external reviewer via bash (e.g., a separate AI CLI like `codex` or `gemini`, or any review skill you have available)
   - The reviewer should NOT have access to your reasoning about why you made certain choices — it should judge the code on its own merits

   **Integration verification** — end-to-end scenarios from verification.md. Run these yourself (you have the context to set up the scenario) or delegate if they're self-contained.

2. **Collect results** from all verification sources and evaluate holistically:
   - All automated checks pass AND independent review has no critical issues → **proceed to delivery**
   - Automated checks fail → **fix and re-run** (no need to re-do independent review for mechanical fixes)
   - Independent review finds issues → **assess each issue**: fix if valid, document disagreement if you believe the reviewer is wrong (but err on the side of fixing)

3. **If verification fails repeatedly** — after fixing and re-verifying, if you're still not passing, ask yourself: is the approach fundamentally wrong? Sometimes the right move is to step back and try a different strategy, not to keep patching. If you've gone around the fix→verify loop more than makes sense for this task's complexity, escalate to the user with a clear explanation of what's failing and why.

## Mid-execution re-alignment

Sometimes you discover that the alignment documents don't match reality:
- A file mentioned in task.md doesn't exist or has been restructured
- A technical approach from task.md won't work due to constraints you've discovered
- The scope is larger or smaller than expected
- A dependency behaves differently than assumed

When this happens:

1. **Stop execution.** Don't silently work around the problem.
2. **Document the discovery** in progress.md under "Change Log."
3. **Assess impact:** Does this invalidate the goal? Or just require a detour?
   - Minor detour (approach change, scope adjustment) → explain to the user, propose an adjustment, get confirmation, update task.md, continue
   - Fundamental problem (goal itself may need rethinking) → explain to the user, present options, wait for direction

The key: re-alignment is a conversation with the user, not a unilateral decision
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Category: AI Agents

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