implement

What this skill does

# Implement Feature

Parallel subagent execution for feature implementation with scope control and reflection.

## Quick Start

```bash
/ork:implement user authentication
/ork:implement --model=opus real-time notifications
/ork:implement dashboard analytics
```

---

## Argument Resolution

```python
FEATURE_DESC = "$ARGUMENTS"  # Full argument string, e.g., "user authentication"
# $ARGUMENTS[0] is the first token, $ARGUMENTS[1] second, etc. (CC 2.1.59)

# Model override detection (CC 2.1.72)
MODEL_OVERRIDE = None
for token in "$ARGUMENTS".split():
    if token.startswith("--model="):
        MODEL_OVERRIDE = token.split("=", 1)[1]  # "opus", "sonnet", "haiku"
        FEATURE_DESC = FEATURE_DESC.replace(token, "").strip()
```

Pass `MODEL_OVERRIDE` to all Agent() calls via `model=MODEL_OVERRIDE` when set. Accepts symbolic names (`opus`, `sonnet`, `haiku`) or full IDs (`claude-opus-4-8`) per CC 2.1.74.

---

## Step -1: MCP Probe + Resume Check

**Run BEFORE any other step.** Detect available MCP servers and check for resumable state.

```python
# Probe MCPs (parallel — all in ONE message):
# memory is alwaysLoad in .mcp.json (CC 2.1.121+, #1541) — probe below kept as fallback for older CC:
ToolSearch(query="select:mcp__memory__search_nodes")
ToolSearch(query="select:mcp__context7__resolve-library-id")

Write(".claude/chain/capabilities.json", JSON.stringify({
  "memory": <true if found>,
  "context7": <true if found>,
  "timestamp": now()
}))

# Resume check:
Read(".claude/chain/state.json")
# If exists and skill == "implement":
#   Read last handoff (e.g., 04-architecture.json)
#   Skip to current_phase
#   "Resuming from Phase {N} — architecture decided in previous session"
# If not: write initial state
Write(".claude/chain/state.json", JSON.stringify({
  "skill": "implement", "feature": FEATURE_DESC,
  "current_phase": 1, "completed_phases": [],
  "capabilities": capabilities,
  "budget_remaining_pct": 100  // advisory; see Budget Awareness below
}))
```

### Batch Size Governance (large refactors)

For implementations touching **>10 files**, enforce max 5 files per agent batch, run tests between batches, commit green batches immediately, stop on red. Override via `--batch-size N`. Full rule: `Read("${CLAUDE_SKILL_DIR}/rules/batch-governance.md")`.

### Budget Awareness (Opus 4.8 task budgets, public beta)

Opus 4.8 exposes per-task token budgets. Until the CC side is GA, OrchestKit tracks an advisory `budget_remaining_pct` in `state.json` so long runs self-throttle. Update after each phase:

```python
# At end of every phase, estimate remaining budget:
pct = tokensAsContextPct(tokensUsedSoFar)  # from lib/context-window.ts
remaining = max(0, 100 - pct)
state["budget_remaining_pct"] = remaining
Write(".claude/chain/state.json", JSON.stringify(state))
```

Thresholds influence behavior:

| Remaining | Behavior |
|---|---|
| `> 50%` | Normal — all optional depth (devil's advocate, visual capture, deep exploration). |
| `20-50%` | Efficient — skip optional depth; keep core phases. Warn user once. |
| `< 20%` | Conservation — finish current phase, emit a handoff with next steps, do not start new work. |

When CC's native task-budget API ships GA, replace the estimate with the real signal; the thresholds and behavior stay the same.

> Load: `Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/checkpoint-resume.md")`

---

## Step 0: Effort-Aware Phase Scaling (CC 2.1.76; `xhigh` added in 2.1.111)

Read the `/effort` setting to scale implementation depth. The effort-aware context budgeting hook detects effort level automatically — adapt the phase plan accordingly:

| Effort Level | Phases Run | Agents | Token Budget |
|-------------|------------|--------|--------------|
| **low** | 1 (Discovery) → 5 (Implement) → 10 (Reflect) | 2 max | ~50K |
| **medium** | 1 → 2 → 5 → 7 (Scope Creep) → 10 | 3 max | ~150K |
| **high** (default) | All 10 phases | 4-7 | ~400K |
| **xhigh** (Opus 4.8, CC 2.1.111+) | All 10 phases + one additional healing iteration on test failures before escalating | 4-7 | ~550K |

> **Override:** Explicit user selection in Step 0 (e.g., "Plan first" or "Worktree") overrides `/effort` downscaling. If user requests full exploration, respect that regardless of effort level.

## Step 0a: Project Context Discovery

**BEFORE any work**, detect the project tier. This becomes the complexity ceiling for all patterns.

Scan codebase signals and classify into tiers 1-6 (Interview through Open Source). Each tier sets an architecture ceiling and determines which phases/agents to use.

Load tier details, workflow mapping, and orchestration mode: `Read("${CLAUDE_SKILL_DIR}/references/tier-classification.md")`

### Worktree Isolation (CC 2.1.49)

For features touching 5+ files, offer worktree isolation to prevent conflicts with the main working tree:

```python
AskUserQuestion(questions=[{
  "question": "Isolate this feature in a git worktree?",
  "header": "Isolation",
  "options": [
    {"label": "Yes — worktree (Recommended)", "description": "Creates isolated branch via EnterWorktree, merges back on completion"},
    {"label": "No — work in-place", "description": "Edit files directly in current branch"},
    {"label": "Plan first", "description": "Research and design in plan mode before writing code"}
  ],
  "multiSelect": false
}])
```

**If 'Plan first' selected:**

```python
# 1. Enter read-only plan mode
EnterPlanMode("Research and design: $ARGUMENTS")

# 2. Research phase — Read/Grep/Glob ONLY, no Write/Edit
#    - Read existing code in the target area
#    - Grep for related patterns, imports, dependencies
#    - Check tests, configs, and integration points
#    - If context7 available: query library docs

# 3. Design the plan — produce:
#    - File map: which files to create/modify
#    - Architecture decisions with rationale
#    - Task breakdown with acceptance criteria
#    - Risk assessment and edge cases

# 4. Exit plan mode — returns plan to user for approval
ExitPlanMode()

# 5. User reviews plan. If approved → continue to Phase 1 (Discovery)
#    with the plan as input. If rejected → revise or stop.
```

If worktree selected:
1. Call `EnterWorktree(name: "feat-{slug}")` to create isolated branch
2. All agents work in the worktree directory
3. On completion, merge back: `git checkout {original-branch} && git merge feat-{slug}`
4. If merge conflicts arise, present diff to user via `AskUserQuestion`

Load worktree details: `Read("${CLAUDE_SKILL_DIR}/references/worktree-isolation-mode.md")`

---

## Task Management (MANDATORY)

**BEFORE doing ANYTHING else, create tasks to track progress:**

```python
# 1. Create main task IMMEDIATELY
TaskCreate(
  subject="Implement: {feature}",
  description="Feature implementation with parallel subagents",
  activeForm="Implementing {feature}"
)

# 2. Create subtasks for each phase
TaskCreate(subject="Research best practices and docs", activeForm="Researching best practices")  # id=2
TaskCreate(subject="Micro-plan: scope, files, criteria", activeForm="Micro-planning")            # id=3
TaskCreate(subject="Architecture design (parallel agents)", activeForm="Designing architecture") # id=4
TaskCreate(subject="Implement and write tests", activeForm="Implementing code")                  # id=5
TaskCreate(subject="Integration verification", activeForm="Verifying integration")               # id=6
TaskCreate(subject="Scope creep check", activeForm="Checking scope creep")                       # id=7
TaskCreate(subject="E2E verification", activeForm="Running E2E verification")                    # id=8
TaskCreate(subject="Document and reflect", activeForm="Documenting decisions")                   # id=9

# 3. Set dependencies for sequential phases
TaskUpdate(taskId="3", addBlockedBy=["2"])  # Plan needs research
TaskUpdate(taskId="4", addBlockedBy=["3"])  # Architecture needs plan
TaskUpdate(taskId="5", addBlockedBy=["4"])  # Implementation needs architecture
TaskUpdate(taskId="6", addBlockedBy=["5