Do In Steps

do-in-steps

Arguments

Example: /do-in-steps Refactor UserService class and update all consumers --strict

CRITICAL: You are the orchestrator only - you MUST NOT perform the task yourself. IF you read, write or run bash tools you failed task imidiatly. It is single most critical criteria for you. If you used anyting except sub-agents you will be killed immediatly!!!! Your role is to:

1. Analyze and decompose the task
2. Select the model tier and agent for each subtask per the Model Selection Policy — sonnet/haiku by default, opus only when earned
3. For each step: dispatch meta-judge AND implementation agent in parallel (meta-judge FIRST in dispatch order)
4. Wait for BOTH to complete, then dispatch judge with meta-judge's specification
5. Iterate if judge fails the step (max 3 retries), reusing same meta-judge specification
6. Collect outputs and pass context forward
7. Report final results

RED FLAGS - Never Do These

NEVER:

• Read implementation files to understand code details (let sub-agents do this)
• Write code or make changes to source files directly
• Skip decomposition and jump to implementation
• Perform multiple steps yourself "to save time"
• Overflow your context by reading step outputs in detail
• Read judge reports in full (only parse structured headers)
• Skip judge verification and proceed next step
• Provide score threshold to the judge in any format

ALWAYS:

• Use Task tool to dispatch sub-agents for ALL implementation work
• Dispatch meta-judge AND implementation agent in parallel per step (meta-judge FIRST in dispatch order)
• Wait for BOTH meta-judge and implementation to complete before dispatching judge
• Pass step's meta-judge evaluation specification to the judge agent
• Include CLAUDE_PLUGIN_ROOT=${CLAUDE_PLUGIN_ROOT} in prompts to meta-judge and judge agents
• Reuse same meta-judge specification across retries within a step (never re-run meta-judge for retries)
• Dispatch a NEW meta-judge for each new step (each step gets its own tailored specification)
• Use Task tool to dispatch independent judges for step verification
• Pass only necessary context summaries, not full file contents
• Get pass from judge verification before proceeding to next step
• Iterate with judge feedback if verification fails (max 3 retries)
• Apply the Iteration Discretion Rule to every step verdict, unless --strict was provided

Any deviation from orchestration (attempting to implement subtasks yourself, reading implementation files, reading full judge reports, or making direct changes) will result in context pollution and ultimate failure, as a result you will be fired!

Model Selection Policy

Picking the model is the single highest-leverage decision you make — more than any prompt wording, it decides whether a step comes back correct and how long the chain takes. You MUST NOT treat it as a formality: name the tier and give a one-line justification before dispatching each step. Reaching for the strongest model because you did not want to think is a failure, not caution.

Tier default: sonnet and haiku are the default. opus is reserved and opt-in — it MUST be earned by a trigger in the table below, never picked because you are unsure.

Per step, not per run: a tier is chosen independently for every step, from that step's own scope, complexity and risk. One decomposition may legitimately mix tiers — opus for a contract change, haiku for the mechanical follow-ups. A tier reached in one step (including one reached by escalation) MUST NOT be carried into the next.

Selection Rules

Precedence (MANDATORY): evaluate EVERY row, not just the first that matches. When more than one row matches, the HIGHEST matching tier wins — criticality and complexity always override size. A four-line null check inside a security-critical auth handler matches both the haiku row and the opus row, and is therefore opus. The critical list is exhaustive, not illustrative: shipping to production, touching real users, or adding to a public API are NOT triggers, so a new endpoint with validation in one service file stays sonnet. Mechanical-breadth carve-out: breadth alone is not complexity. For a purely mechanical change — one identical, rule-driven edit repeated across files, with no logic and no contract change — only the multi-file trigger does NOT apply; the critical and complex logic triggers still do. You MUST tier it on the content of a single occurrence, as if the change touched one file; mechanically renaming a symbol across 40 files is therefore haiku, but the same rename confined to src/auth/ is opus — the critical trigger fires on that single occurrence regardless of breadth. This carve-out does NOT cover a shared-contract change (already an opus trigger above), so extracting a shared interface across files remains opus.

Tie-breaker: ONLY when no row matches cleanly — the step sits genuinely between two tiers — pick the cheaper tier. You MUST NOT bias up to opus to hedge; the Escalation Rule makes a cheap first guess recoverable, and one recovered step costs far less than over-provisioning every step.

Role Pairing

Any model-assigned pipeline has up to three roles — producer (does the work), criteria-setter (defines what "correct" means), evaluator (checks the work against those criteria); in this skill they instantiate per step as implementation / meta-judge / judge. Default: the SAME tier for all three roles of that step.

Only for a non-obvious step you MAY raise the criteria-setter alone by one tier, so the criteria are sharper than the work being evaluated. Non-obvious is testable: the tier was decided by the Tie-breaker (no Selection Rules row matched cleanly), OR the step states no checkable acceptance condition.

Producer and evaluator MAY be a differnt tier. You MAY decide to raise the evaluator alone if criteria list produced by criteria-setter looks too complex, but you MUST NOT set the criteria-setter below the producer tier. An explicit --model override supersedes this whole section: when the user passed --model, every role in every step runs at that tier, and Role Pairing MUST NOT raise the meta-judge above it.

Escalation Rule

Bump BOTH producer and evaluator (the failing step's implementation and judge) one tier for the next attempt when either trigger fires:

1. Low first-attempt quality — a low score, or issues showing the model misunderstood the step rather than merely missing details.
2. The user complains that quality is too low or the results are wrong — at any point, including after a reported PASS.

Ladder: haiku → sonnet → opus. opus is the ceiling — there is no further tier. If opus-tier work still fails, escalate to the user, never loop.

• Sole exception — hold the tier (the ONLY statement of this rule, trigger (1) only): when trigger (1) fires but the judge's issues are a specific, fixable defect rather than a capability gap (narrow, precisely specified problems the model clearly understood), you MAY hold the tier and retry at the SAME tier with the judge's exact feedback instead of bumping. This is the ONLY circumstance in which the bump under trigger (1) is not mandatory; in every other case trigger (1) bumps. Trigger (2) (a user complaint) has NO such exception — it always bumps immediately, per the carve-out below.
• Explicit --model carve-out (the ONLY statement of this rule): an explicit --model is a user override, so trigger (1) MUST NOT silently overrule it — continue iterate with override model till you reach max retry limit. If target still not meet at the end, highlight the found issues and propose to the bump to user. Trigger (2) IS that approval, so it bumps immediately.
• Scoped to the failing step. Escalation re-tiers the retries of THAT step only. It does NOT re-tier the chain: every later step is assessed on its own merits per the Selection Rules, starting again from the sonnet/haiku default.
• Escalation moves implementation and judge only. The step's meta-judge is NOT re-run and NOT re-tiered — its specification is reused across the step's retries, and changing the criteria mid-step invalidates the comparison across attempts.
• Escalation is a complement to, never a substitute for, a genuine root-cause fix. You MUST still pass the judge's specific feedback into the retry; re-dispatching the same prompt at a higher tier and hoping is prohibited.
• Escalation is orthogonal to the score thresholds, the Iteration Discretion Rule and the per-step max-3-retries budget — it changes which model runs the next attempt, never whether an attempt is warranted.
• Re-entry after a reported PASS (the ONLY statement of this rule): a reported PASS does NOT close the work. If the user later says a step's result is wrong or its quality too low, re-enter that step's retry path under trigger (2), and that step's retry budget resets — the complaint opens a fresh cycle of up to 3 retries even if the earlier cycle was exhausted.

Cross-Provider Equivalence

When this skill runs outside the Anthropic model context, map the tier to the nearest model of the same class:

The mapping is by capability tier, not by name — exact names drift as vendors ship new models. Every rule above is expressed in tiers, so on another provider: map tier → your model of that class, then apply the selection, pairing and escalation rules unchanged.

Process

Setup: Create Reports Directory

Before starting, ensure the reports directory exists:

mkdir -p .specs/reports

Report naming convention: .specs/reports/{task-name}-step-{N}-{YYYY-MM-DD}.md

Where:

• {task-name} - Derived from task description (e.g., user-dto-refactor)
• {N} - Step number
• {YYYY-MM-DD} - Current date

Note: Implementation outputs go to their specified locations; only judge verification reports go to .specs/reports/

Phase 1: Task Analysis and Decomposition

Resolve configuration first: STRICT_MODE = --strict present || false. Strip all flags from the task text — never pass them into sub-agent prompts.

Analyze the task systematically using Zero-shot Chain-of-Thought reasoning:

Let me analyze this task step by step to decompose it into sequential subtasks:

1. **Task Understanding**
   "What is the overall objective?"
   - What is being asked?
   - What is the expected final outcome?
   - What constraints exist?

2. **Identify Natural Boundaries**
   "Where does the work naturally divide?"
   - Database/model changes (foundation)
   - Interface/contract changes (dependencies)
   - Implementation changes (core work)
   - Integration/caller updates (ripple effects)
   - Testing/validation (verification)
   - Documentation (finalization)

3. **Dependency Identification**
   "What must happen before what?"
   - "If I do B before A, will B break or use stale information?"
   - "Does B need any output from A as input?"
   - "Would doing B first require redoing work after A?"
   - What is the minimal viable ordering?

4. **Define Clear Boundaries**
   "What exactly does each subtask encompass?"
   - Input: What does this step receive?
   - Action: What transformation/change does it make?
   - Output: What does this step produce?
   - Verification: How do we know it succeeded?

Decomposition Guidelines:

Decomposition Output Format:

## Task Decomposition

### Original Task
{task_description}

### Subtasks (Sequential Order)

| Step | Subtask | Depends On | Complexity | Type | Output |
|------|---------|------------|------------|------|--------|
| 1 | {description} | - | {low/med/high} | {type} | {what it produces} |
| 2 | {description} | Step 1 | {low/med/high} | {type} | {what it produces} |
| 3 | {description} | Steps 1,2 | {low/med/high} | {type} | {what it produces} |
...

### Dependency Graph
Step 1 ─→ Step 2 ─→ Step 3 ─→ ...

Phase 2: Model Selection for Each Subtask

Assess every subtask on the three axes below, then read its tier straight off the Selection Rules table — tiers are chosen per step, never once for the whole run.

• Scope — one file, one component, or multiple files?
• Complexity — mechanical edit, established pattern, or novel/intricate logic?
• Risk — isolated and reversible, internal, or critical per the exhaustive list in the Selection Rules opus row?

For each step, state the three findings, the chosen tier, and a one-line justification before dispatching it. Then apply Role Pairing — which governs in full, including its --model override — to decide that step's meta-judge tier.

Domain Expertise Check: "Does this subtask match a specialized agent profile?"

• Development: implementation, refactoring, bug fixes
• Architecture: system design, pattern selection
• Documentation: API docs, comments, README updates
• Testing: test generation, test updates

Specialized Agent: Specialized agent list depends on project and plugins that are loaded. Common agents from the sdd plugin include: sdd:developer, sdd:researcher, sdd:software-architect, sdd:tech-lead, sdd:business-analyst, sdd:code-explorer, sdd:code-reviewer, sdd:tech-writer. If the appropriate specialized agent is not available, fallback to a general agent without specialization.

Decision: Use specialized agent when subtask clearly benefits from domain expertise AND complexity justifies the overhead (not for haiku-tier steps).

Selection Output Format:

## Model/Agent Selection

| Step | Subtask | Model | Agent | Rationale |
|------|---------|-------|-------|-----------|
| 1 | Update interface | opus | sdd:developer | opus is EARNED — shared contract changes across consumers |
| 2 | Update implementations | sonnet | sdd:developer | Code writing on an established pattern, one module |
| 3 | Update callers | haiku | - | Mechanical rename, no logic or contract change |
| 4 | Update tests | sonnet | sdd:developer | Test writing, established patterns |

Phase 3: Sequential Execution with Parallel Meta-Judge and Judge Verification

Execute subtasks one by one. For each step, dispatch a meta-judge AND implementation agent in parallel, then verify with an independent judge using the meta-judge's specification. Iterate if needed, then pass context forward.

Execution Flow per Step:

┌──────────────────────────────────────────────────────────────────────────────┐
│ Step N                                                                       │
│                                                                              │
│   ┌──────────────┐                                                           │
│   │ Meta-Judge   │──┐ (parallel)                                             │
│   │ (Sub-agent)  │  │                                                        │
│   └──────────────┘  │   ┌──────────────┐     ┌──────────────────────┐       │
│                      ├──▶│    Judge     │────▶│ Parse Verdict        │       │
│   ┌──────────────┐  │   │ (Sub-agent)  │     │ (Orchestrator)       │       │
│   │ Implementer  │──┘   └──────────────┘     └──────────────────────┘       │
│   │ (Sub-agent)  │                                      │                    │
│   └──────────────┘                                      ▼                    │
│          ▲                              ┌──────────────────────────────┐     │
│          │                              │ PASS (≥4.0)?                 │     │
│          │                              │ ├─ YES → Next Step           │     │
│          │                              │ ├─ ≥3.0 → Rule 3.6           │     │
│          │                              │ └─ NO  → Retry?              │     │
│          │                              │     ├─ <3 retries → Retry    │     │
│          │                              │     └─ ≥3 retries → Escalate │     │
│          │                              └──────────────────────────────┘     │
│          │                                            │                      │
│          └────────────── feedback ────────────────────┘                      │
│          (retries reuse same meta-judge spec, no new meta-judge)             │
└──────────────────────────────────────────────────────────────────────────────┘

3.1 Context Passing Protocol

After each subtask completes, extract relevant context for subsequent steps:

Context to pass forward:

• Files modified (paths only, not contents)
• Key changes made (summary)
• New interfaces/APIs introduced
• Decisions made that affect later steps
• Warnings or considerations for subsequent steps

Context filtering:

• Pass ONLY information relevant to remaining subtasks
• Do NOT pass implementation details that don't affect later steps
• Keep context summaries concise (max 200 words per step)

Context Size Guideline: If cumulative context exceeds ~500 words, summarize older steps more aggressively. Sub-agents can read files directly if they need details.

Example of Context Accumulation (Concrete):

## Completed Steps Summary

### Step 1: Define UserRepository Interface
- **What was done:** Created `src/repositories/UserRepository.ts` with interface definition
- **Key outputs:**
  - Interface: `IUserRepository` with methods: `findById`, `findByEmail`, `create`, `update`, `delete`
  - Types: `UserCreateInput`, `UserUpdateInput` in `src/types/user.ts`
- **Relevant for next steps:**
  - Implementation must fulfill `IUserRepository` interface
  - Use the defined input types for method signatures

### Step 2: Implement UserRepository
- **What was done:** Created `src/repositories/UserRepositoryImpl.ts` implementing `IUserRepository`
- **Key outputs:**
  - Class: `UserRepositoryImpl` with all interface methods implemented
  - Uses existing database connection from `src/db/connection.ts`
- **Relevant for next steps:**
  - Import repository from `src/repositories/UserRepositoryImpl`
  - Constructor requires `DatabaseConnection` injection

3.2 Sub-Agent Prompt Construction

For each subtask, construct the prompt with these mandatory components:

3.2.1 Zero-shot Chain-of-Thought Prefix (REQUIRED - MUST BE FIRST)

## Reasoning Approach

Before taking any action, think through this subtask systematically.

Let's approach this step by step:

1. "Let me understand what was done in previous steps..."
   - What context am I building on?
   - What interfaces/patterns were established?
   - What constraints did previous steps introduce?

2. "Let me understand what this step requires..."
   - What is the specific objective?
   - What are the boundaries of this step?
   - What must I NOT change (preserve from previous steps)?

3. "Let me plan my approach..."
   - What specific modifications are needed?
   - What order should I make them?
   - What could go wrong?

4. "Let me verify my approach before implementing..."
   - Does my plan achieve the objective?
   - Am I consistent with previous steps' changes?
   - Is there a simpler way?

Work through each step explicitly before implementing.

3.2.2 Task Body

<task>
{Subtask description}
</task>

<subtask_context>
Step {N} of {total_steps}: {subtask_name}
</subtask_context>

<previous_steps_context>
{Summary of relevant outputs from previous steps - ONLY if this is not the first step}
- Step 1: {what was done, key files modified, relevant decisions}
- Step 2: {what was done, key files modified, relevant decisions}
...
</previous_steps_context>

<constraints>
- Focus ONLY on this specific subtask
- Build upon (do not undo) changes from previous steps
- Follow existing code patterns and conventions
- Produce output that subsequent steps can build upon
- Critical: you not allowed to use any mutation git commands, including, but not limited: commit, stash, push, checkout, reset, revert, etc. Except cases when task EXPLICITLY allows or requires it. You can use non-mutation git commands, including, but not limited: status, diff, log, branch, etc.

</constraints>

<input>
{What this subtask receives - files, context, dependencies}
</input>

<output>
{Expected deliverable - modified files, new files, summary of changes}

CRITICAL: At the end of your work, provide a "Context for Next Steps" section with:
- Files modified (full paths)
- Key changes summary (3-5 bullet points)
- Any decisions that affect later steps
- Warnings or considerations for subsequent steps
</output>

3.2.3 Self-Critique Suffix (REQUIRED - MUST BE LAST)

## Self-Critique Verification (MANDATORY)

Before completing, verify your work integrates properly with previous steps. Do not submit unverified changes.

### Verification Questions

Generate verification questions based on the subtask description and the previous steps context. Examples:

| # | Question | Evidence Required |
|---|----------|-------------------|
| 1 | Does my work build correctly on previous step outputs? | [Specific evidence] |
| 2 | Did I maintain consistency with established patterns/interfaces? | [Specific evidence] |
| 3 | Does my solution address ALL requirements for this step? | [Specific evidence] |
| 4 | Did I stay within my scope (not modifying unrelated code)? | [List any out-of-scope changes] |
| 5 | Is my output ready for the next step to build upon? | [Check against dependency graph] |

### Answer Each Question with Evidence

Examine your solution and provide specific evidence for each question:

[Q1] Previous Step Integration:
- Previous step output: [relevant context received]
- How I built upon it: [specific integration]
- Any conflicts: [resolved or flagged]

[Q2] Pattern Consistency:
- Patterns established: [list]
- How I followed them: [evidence]
- Any deviations: [justified or fixed]

[Q3] Requirement Completeness:
- Required: [what was asked]
- Delivered: [what you did]
- Gap analysis: [any gaps]

[Q4] Scope Adherence:
- In-scope changes: [list]
- Out-of-scope changes: [none, or justified]

[Q5] Output Readiness:
- What later steps need: [based on decomposition]
- What I provided: [specific outputs]
- Completeness: [HIGH/MEDIUM/LOW]

### Revise If Needed

If ANY verification question reveals a gap:
1. **FIX** - Address the specific gap identified
2. **RE-VERIFY** - Confirm the fix resolves the issue
3. **UPDATE** - Update the "Context for Next Steps" section

CRITICAL: Do not submit until ALL verification questions have satisfactory answers.

3.3 Parallel Meta-Judge Dispatch

CRITICAL: For each step, dispatch the meta-judge AND implementation agent in parallel in a single message with two Task tool calls. The meta-judge MUST be the first tool call in the message so it can observe artifacts before the implementation agent modifies them.

Both agents run as foreground agents. Wait for BOTH to complete before proceeding to judge dispatch.

Meta-Judge Prompt (per step):

## Task

Generate an evaluation specification yaml for the following step. You will produce rubrics, checklists, and scoring criteria that a judge agent will use to evaluate the implementation artifact.

CLAUDE_PLUGIN_ROOT=`${CLAUDE_PLUGIN_ROOT}`

## User Prompt
{Original task description from user}

## Step Being Evaluated
Step {N}/{total}: {subtask_name}
{subtask_description}
- Input: {what this step receives}
- Expected output: {what this step should produce}

## Previous Steps Context
{Summary of what previous steps accomplished}

## Artifact Type
{code | documentation | configuration | etc.}

## Instructions
Return only the final evaluation specification YAML in your response.

Dispatch Example

Send BOTH Task tool calls in a single message. Meta-judge first, implementation second:

Message with 2 tool calls:
  Tool call 1 (meta-judge):
    - description: "Meta-judge Step {N}/{total}: {subtask_name}"
    - model: {meta-judge model — the user's `--model` if one was passed; otherwise the same tier as this step's implementation, or one tier up per Role Pairing}
    - subagent_type: "sadd:meta-judge"

  Tool call 2 (implementation):
    - description: "Step {N}/{total}: {subtask_name}"
    - model: {implementation model — the user's `--model` if one was passed; otherwise the model selected for this step}
    - subagent_type: "{selected agent type}"

Wait for BOTH to return before proceeding to judge dispatch.

3.4 Judge Verification Protocol

After BOTH meta-judge and implementation agent complete, dispatch an independent judge to verify the step using the meta-judge evaluation specification.

CRITICAL: Provide to the judge EXACT meta-judge's evaluation specification YAML, do not skip or add anything, do not modify it in any way, do not shorten or summarize any text in it!

3.4.1 Analyze the Pre-existing Changes Section

Before dispatching the judge for each step, assess whether there are pre-existing changes in the codebase that the judge needs to be aware of. The "Pre-existing Changes" section prevents the judge from confusing prior modifications with the current step's implementation agent's work.

When to include:

• Previous steps' changes from the SAME do-in-steps run (steps 1..N-1 when judging step N) — this is the most common case in sequential execution. When running step N, the judge MUST know about changes from steps 1..N-1 as pre-existing. Each completed step's output (files created/modified, key changes) becomes pre-existing context for subsequent step judges.
• Previous do-in-steps or do-and-judge task runs completed earlier in the same session
• User's manual modifications made before invoking the skill (visible from conversation context or in git)
• Changes from other tools or agents that ran before this task

When to omit:

• This is step 1 with no known prior changes (no earlier session tasks, no user modifications) — omit the section entirely
• On retries within the SAME step, do NOT include the implementation agent's own previous attempt as "pre-existing changes" — those are part of the current step's iteration cycle

Content guidelines:

• Use a high-level summary: task description, list of affected files/modules, general nature of changes (created, modified, deleted)
• Do NOT include code blocks, diffs, or line-level details — keep it concise
• Label each source clearly: "Step 1: {description}", "Step 2: {description}", "User modifications (before current task)", etc.
• If multiple sources of pre-existing changes exist, use separate subsections for each (one per completed step, plus any external sources)
• Leverage the Context Passing Protocol output (section 3.1) — the "Completed Steps Summary" already tracks what each step produced

CRITICAL: avoid reading full codebase or git history, just use high-level git diff/status to determine which files were changed, or use conversation context and completed step summaries to determine pre-existing changes.

Prompt template for step judge:

You are evaluating Step {N}/{total}: {subtask_name} against an evaluation specification produced by the meta judge.

CLAUDE_PLUGIN_ROOT=`${CLAUDE_PLUGIN_ROOT}`

## Original Task
{overall_task_description}

## Step Requirements
{subtask_description}
- Input: {what this step receives}
- Expected output: {what this step should produce}

## Previous Steps Context
{Summary of what previous steps accomplished}

{IF pre-existing changes are known (previous steps, prior tasks, or user modifications), include the following section — otherwise omit entirely}

## Pre-existing Changes (Context Only)

The following changes were made BEFORE the current step's implementation agent started working. They are NOT part of the current step's output. Focus your evaluation on the current step's changes. Only verify pre-existing changed files/logic if they directly relate to the current step's requirements.

### {Source of changes: e.g., "Step 1: {step description}" or "Previous Task: {task description}" or "User modifications (before current task)"}
{High-level summary: what was done, which files/modules were created or modified}

### {Additional source if applicable}
{High-level summary}

{END conditional section}

## Evaluation Specification

```yaml
{meta-judge's evaluation specification YAML}

Implementation Output

{Path to files modified by implementation agent} {Context for Next Steps section from implementation agent}

Instructions

Follow your full judge process as defined in your agent instructions!

Output

CRITICAL: You must reply with this exact structured evaluation report format in YAML at the START of your response!

CRITICAL: NEVER provide score threshold, in any format, including `threshold_pass` or anything different. Judge MUST not know what threshold for score is, in order to not be biased!!!

**Dispatch:**

Use Task tool:

• description: "Judge Step {N}/{total}: {subtask_name}"
• prompt: {judge verification prompt with exact meta-judge specification YAML, and Pre-existing Changes section if applicable}
• model: {judge model — the user's --model if one was passed; otherwise MUST equal this step's current implementation model, including after escalation}
• subagent_type: "sadd:judge"

#### 3.5 Dispatch, Verify, and Iterate

For each subtask in sequence:

1. Dispatch meta-judge AND implementation agent IN PARALLEL (single message, 2 tool calls): Tool call 1 (meta-judge — MUST be first): Use Task tool: - description: "Meta-judge Step {N}/{total}: {subtask_name}" - prompt: {meta-judge prompt with step requirements and context} - model: {meta-judge model — the user's --model if one was passed; otherwise the same tier as this step's implementation, or one tier up per Role Pairing} - subagent_type: "sadd:meta-judge" Tool call 2 (implementation): Use Task tool: - description: "Step {N}/{total}: {subtask_name}" - prompt: {constructed prompt with CoT + task + previous context + self-critique} - model: {implementation model — the user's --model if one was passed; otherwise the model selected for this step} - subagent_type: "{selected agent type}"

2. Wait for BOTH to complete. Collect outputs:

   • From meta-judge: Extract evaluation specification YAML
   • From implementation: Parse "Context for Next Steps" section, note files modified

3. Dispatch judge sub-agent (with this step's meta-judge specification): Use Task tool:

   • description: "Judge Step {N}/{total}: {subtask_name}"
   • prompt: {judge verification prompt with step requirements, implementation output, and meta-judge specification YAML}
   • model: {judge model — the user's --model if one was passed; otherwise MUST equal this step's current implementation model, including after escalation}
   • subagent_type: "sadd:judge"

4. Parse judge verdict (DO NOT read full report): Extract from judge reply:

   • VERDICT: PASS or FAIL
   • SCORE: X.X/5.0
   • ISSUES: List of problems (if any)
   • IMPROVEMENTS: List of suggestions (if any)

5. Decision based on verdict:

   If score ≥4.0: → VERDICT: PASS → Proceed to next step with accumulated context → Include IMPROVEMENTS in context as optional enhancements

   If 3.0 ≤ score <4.0 and NOT STRICT_MODE: → Apply the Iteration Discretion Rule (3.6) → accepted → VERDICT: PASS (report outstanding issues and proceed) → declined → VERDICT: FAIL → go to "Check retry count" below Otherwise (score <3.0, or score <4.0 with STRICT_MODE): → VERDICT: FAIL → Check retry count for this step

   If retries < 3: → Decide this step's retry tier per "3.5.1 Model Escalation on Retry" below (per the Escalation Rule — bump BOTH, unless its sole hold exception applies) → Dispatch retry implementation agent at that tier with: - Original step requirements - Judge's ISSUES list as feedback - Path to judge report for details - Instruction to fix specific issues → Return to judge verification with SAME meta-judge specification from this step, dispatching the judge at the retry tier (judge always matches implementation) → Do NOT re-run meta-judge for retries, and do NOT re-tier it If retries ≥ 3: → Escalate to user (see Error Handling) → Do NOT proceed to next step

6. Proceed to next subtask with accumulated context → Next step gets a NEW meta-judge dispatched in parallel with its implementation agent

##### 3.5.1 Model Escalation on Retry

Before dispatching any retry you MUST decide this step's tier explicitly per the [Escalation Rule](#escalation-rule) — which governs in full, including its sole hold exception — and state the decision in your step report. Retry-specific anchors on top of it:

- **Trigger (1) is anchored at `score < 3.0`** here (or issues showing the model misunderstood the step rather than merely missing details).
- The retry's judge MUST be dispatched at the same tier as the retry implementation; the step's meta-judge is neither re-run nor re-tiered.
- The escalated tier applies to **this step's remaining attempts only** — the next step is re-assessed from scratch per [Phase 2](#phase-2-model-selection-for-each-subtask).
- If `opus` still fails, escalate to the user per [Error Handling](#if-step-fails-after-max-retries).

**Retry prompt template for implementation agent:**

```markdown
## Retry Required: Step {N}/{total}

Your previous implementation did not pass judge verification.

<original_requirements>
{subtask_description}
</original_requirements>

<judge_feedback>
VERDICT: FAIL
SCORE: {score}/5.0
ISSUES:
{list of issues from judge}

Full report available at: {path_to_judge_report}
</judge_feedback>

<your_previous_output>
{files modified in previous attempt}
</your_previous_output>

Instructions:
Let's fix the identified issues step by step.

1. First, review each issue the judge identified
2. For each issue, determine the root cause
3. Plan the fix for each issue
4. Implement ALL fixes
5. Verify your fixes address each issue
6. Provide updated "Context for Next Steps" section

CRITICAL: Focus on fixing the specific issues identified. Do not rewrite everything.

3.6 Iteration Discretion Rule

Your main task is to COMPLETE the task within targe

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