# Evaluation Report: do-in-parallel Command

---
VOTE: Solution A
SCORES:
  Solution A: 4.35/5.0
  Solution B: 4.15/5.0
  Solution C: 3.90/5.0
CRITERIA:
 - Completeness: 4.4/5.0
 - Correctness: 4.3/5.0
 - Design Quality: 4.2/5.0
 - Usability: 4.0/5.0
 - Clarity: 4.3/5.0
---

## Executive Summary

This evaluation assesses three candidate implementations of a `/do-in-parallel` command for launching parallel sub-agents in Claude Code. All three solutions address the core requirements but differ significantly in structure, detail level, and adherence to existing patterns. **Solution A** demonstrates the strongest overall implementation with comprehensive model selection logic, clear Zero-shot CoT and Self-critique templates, and excellent alignment with the existing `/launch-sub-agent` command pattern. **Solution B** provides good coverage but with some organizational issues. **Solution C** is more concise but lacks depth in critical areas.

- **Artifact**: Three candidate solutions (A, B, C)
- **Overall Scores**: A=4.35, B=4.15, C=3.90
- **Verdict**: Solution A - GOOD, Solution B - ACCEPTABLE, Solution C - ACCEPTABLE
- **Threshold**: 4.0/5.0
- **Result**: A - PASS, B - PASS, C - FAIL

## Criterion Scores

| Criterion | Weight | Solution A | Solution B | Solution C |
|-----------|--------|------------|------------|------------|
| Completeness | 0.25 | 4.5/5 | 4.3/5 | 3.8/5 |
| Correctness | 0.25 | 4.4/5 | 4.2/5 | 4.0/5 |
| Design Quality | 0.20 | 4.3/5 | 4.0/5 | 3.9/5 |
| Usability | 0.15 | 4.1/5 | 4.2/5 | 4.0/5 |
| Clarity | 0.15 | 4.3/5 | 4.0/5 | 3.9/5 |

## Detailed Analysis

### Completeness (Weight: 0.25)

**Requirement 1: Accept task description and optional file/target list**

| Solution | Evidence | Score |
|----------|----------|-------|
| A | `--files "file1.ts,file2.ts,..."` `--targets "target1,target2,..."` explicit flags (line 3), plus inference from task (lines 37-41) | 5/5 |
| B | Implicit parsing only: "Explicit file list...Glob pattern...Conceptual targets" (lines 40-56) | 4/5 |
| C | "Pattern A: Glob-based...Pattern B: Explicit file list...Pattern C: Task list" (lines 42-56) | 4/5 |

**Analysis A**: Solution A provides explicit CLI argument flags (`--files`, `--targets`, `--model`, `--output`) which is consistent with the `/launch-sub-agent` pattern that uses similar flag structure. Quote: `argument-hint: Task description [--files "file1.ts,file2.ts,..."] [--targets "target1,target2,..."] [--model opus|sonnet|haiku] [--output <path>]`

**Analysis B**: Solution B relies entirely on implicit parsing from the task description. While flexible, it doesn't provide explicit argument handling. Quote: `argument-hint: Task description with targets (e.g., "Simplify code in src/utils/*.ts"...)`

**Analysis C**: Solution C also relies on implicit parsing. Quote: `argument-hint: Task description with targets (e.g., "Simplify functions in src/utils/*.ts"...)`

**Requirement 2: Intelligent model selection (Opus default, Specialized if exists, Sonnet for long tasks, Haiku for easy)**

| Solution | Evidence | Score |
|----------|----------|-------|
| A | Complete decision tree (lines 93-108), explicit matrix (lines 84-91), specialized agent section (lines 110-130) | 5/5 |
| B | Model selection matrix (lines 84-111), specialized agent consideration (lines 113-129) | 4/5 |
| C | Model selection matrix (lines 117-124), complexity indicators (lines 126-144), specialized matching (lines 166-189) | 4/5 |

**Analysis A**: Solution A provides the most comprehensive model selection with clear decision tree, explicit rationale for each choice, and proper handling of specialized agents. Quote:
```
Is EACH target's task COMPLEX (architecture, novel problem, critical decision)?
|
+-- YES --> Use Opus for ALL agents
|
+-- NO --> Is task SIMPLE and MECHANICAL (rename, format, extract)?
           |
           +-- YES --> Use Haiku for ALL agents
```

**Analysis B**: Solution B's model selection is good but spread across multiple sections. The risk assessment adds value but complicates the decision logic.

**Analysis C**: Solution C has adequate model selection but introduces potential confusion by allowing different models per target (Example 2 at lines 434-449), which contradicts the principle of consistent execution.

**Requirement 3: Generate prompts with Zero-shot CoT at beginning and Self-critique at end**

| Solution | Evidence | Score |
|----------|----------|-------|
| A | CoT prefix (lines 136-161), Self-critique suffix (lines 188-215), clearly marked "REQUIRED - MUST BE FIRST/LAST" | 5/5 |
| B | CoT prefix (lines 134-162), Self-critique suffix (lines 192-246), clearly marked "REQUIRED - MUST BE FIRST/LAST" | 5/5 |
| C | CoT prefix (lines 196-222), Self-critique suffix (lines 250-284), marked "REQUIRED" | 4/5 |

**Analysis A**: Solution A provides well-structured prompt templates with explicit marking. Quote: `#### 4.1 Zero-shot Chain-of-Thought Prefix (REQUIRED - MUST BE FIRST)`

**Analysis B**: Solution B's prompts are similarly well-structured with detailed self-critique sections including table format for verification.

**Analysis C**: Solution C's prompts are adequate but less detailed. The self-critique section lacks the structured table format found in A and B.

**Requirement 4: Launch multiple agents in parallel using Task tool**

| Solution | Evidence | Score |
|----------|----------|-------|
| A | Phase 5 (lines 217-231): "Launch ALL agents in a single batch", "Do NOT wait for one agent to complete" | 4/5 |
| B | Phase 4 (lines 248-269): "All tasks are independent - launch simultaneously", context isolation guidelines | 4/5 |
| C | Phase 5 (lines 286-334): "CRITICAL: Parallel Dispatch Pattern", explicit example code showing simultaneous launch | 5/5 |

**Analysis A**: Solution A correctly describes parallel dispatch but could be more explicit about the Task tool invocation pattern.

**Analysis B**: Solution B provides good parallel dispatch guidance with context isolation notes but less explicit on the "single batch" requirement.

**Analysis C**: Solution C provides the most explicit parallel dispatch example with clear code showing all three tasks launched in same response. Quote:
```markdown
[Task 1]
Use Task tool:
  description: "Parallel: add error handling to utils/format.ts"
...
[Task 2]
Use Task tool:
...
[All 3 tasks launched simultaneously - results collected when all complete]
```

**Requirement 5: Collect and summarize results**

| Solution | Evidence | Score |
|----------|----------|-------|
| A | Phase 6 (lines 233-265): Detailed summary template with tables, overall assessment, files modified, next steps | 5/5 |
| B | Phase 5 (lines 271-316): Result collection per agent, summary report template with statistics and verification summary | 5/5 |
| C | Phase 6 (lines 335-375): Result aggregation template with failure handling | 4/5 |

**Analysis**: All three solutions provide result aggregation. A and B are more comprehensive with better structured outputs.

**Completeness Scores:**
- **Solution A: 4.5/5** - Most complete, explicit argument handling, comprehensive model selection
- **Solution B: 4.3/5** - Good coverage, missing explicit argument flags
- **Solution C: 3.8/5** - Adequate but allows mixed models which may cause inconsistency

---

### Correctness (Weight: 0.25)

**Will it work properly with Claude Code Task tool?**

| Solution | Evidence | Assessment |
|----------|----------|------------|
| A | Correct Task tool description pattern (lines 217-227) | Correct |
| B | Correct Task tool parameters (lines 250-258) | Correct |
| C | Most explicit Task tool usage (lines 291-334) | Correct |

**Analysis A**: Solution A correctly describes the Task tool interface but doesn't show explicit invocation syntax. The parallel dispatch guidance is correct: "Do NOT wait for one agent to complete before starting another"

**Analysis B**: Solution B provides correct Task tool parameters but slightly less explicit on the parallel nature.

**Analysis C**: Solution C provides the most detailed Task tool invocation pattern with explicit examples showing multiple calls in same response.

**Alignment with existing patterns** (comparing to `/launch-sub-agent` and `/do-competitively`):

| Aspect | Reference Pattern | A | B | C |
|--------|-------------------|---|---|---|
| Frontmatter format | `description:` + `argument-hint:` | Yes | Yes | Yes |
| `<task>` section | Present in all reference commands | Yes | Yes | Yes |
| `<context>` section | Present in all reference commands | Yes | Yes | Yes |
| Phase-based process | Present in reference commands | Yes | Yes | Yes |
| Decision tree for model selection | Present in launch-sub-agent | Yes | Yes | Partial |
| Specialized agent consideration | Present in launch-sub-agent | Yes | Optional emphasis | Yes |
| CoT + Self-critique pattern | Present in launch-sub-agent | Yes | Yes | Yes |
| Example section | Present in all reference commands | 5 examples | 4 examples | 4 examples |

**Analysis A**: Best alignment with `/launch-sub-agent` patterns. Uses same frontmatter structure with explicit flags, same Phase numbering, same decision tree format.

**Analysis B**: Good alignment but places specialized agent section as "Phase 2.5" which is inconsistent with the reference pattern where it's part of Phase 3.

**Analysis C**: Adequate alignment but the "Phase 3.5" for specialized agent matching deviates from reference patterns.

**Correctness Scores:**
- **Solution A: 4.4/5** - Strong alignment with existing patterns
- **Solution B: 4.2/5** - Good but phase numbering inconsistent
- **Solution C: 4.0/5** - Adequate but mixed model per target is risky

---

### Design Quality (Weight: 0.20)

**Clean architecture and pattern adherence:**

| Solution | Structure | Pattern Adherence | Extensibility |
|----------|-----------|-------------------|---------------|
| A | 6 phases, clear flow | Matches launch-sub-agent | High |
| B | 5 phases + sub-phase | Slightly deviated | Medium |
| C | 6 phases + sub-phase | Adequate | Medium |

**Analysis A**: Solution A has the cleanest architecture with consistent phase numbering (1-6) and clear separation of concerns. The decision tree format is identical to the reference pattern.

**Analysis B**: Solution B introduces "Phase 2.5" for specialized agents which breaks the clean phase numbering. The self-critique section is more detailed but also more verbose.

**Analysis C**: Solution C has "Phase 3.5" which is inconsistent. The parallel dispatch example is well-designed but the mixed model selection per target (Example 2) introduces architectural inconsistency.

**Theoretical foundation:**

| Solution | References | Depth |
|----------|------------|-------|
| A | Zero-shot CoT (Kojima et al.), Constitutional AI (Bai et al.), Multi-Agent architecture | Deep |
| B | Mentions patterns in context but no explicit references | Shallow |
| C | Mentions patterns in context but no explicit references | Shallow |

**Analysis A**: Solution A provides explicit academic references with arXiv links. Quote:
```
**Zero-shot Chain-of-Thought** (Kojima et al., 2022)
- "Let's think step by step" improves reasoning by 20-60%
- Reference: [Large Language Models are Zero-Shot Reasoners](https://arxiv.org/abs/2205.11916)
```

**Design Quality Scores:**
- **Solution A: 4.3/5** - Clean architecture, academic grounding
- **Solution B: 4.0/5** - Good but phase numbering inconsistencies
- **Solution C: 3.9/5** - Mixed model per target is questionable design choice

---

### Usability (Weight: 0.15)

**Easy for users to understand and use:**

| Solution | Argument Format | Examples Quality | Best Practices |
|----------|-----------------|------------------|----------------|
| A | Explicit flags | 5 diverse examples | Comprehensive |
| B | Natural language | 4 examples | Good |
| C | Natural language | 4 examples | Good |

**Analysis A**: Solution A's explicit flags (`--files`, `--targets`) make usage predictable and scriptable. The 5 examples cover diverse scenarios (code simplification, documentation, security, test generation, inferred targets).

**Analysis B**: Solution B's natural language parsing is user-friendly but less predictable. Examples are good but less diverse (3 focused on code, 1 on mixed complexity).

**Analysis C**: Solution C provides good examples but the mixed model per target example may confuse users about expected behavior.

**Best Practices sections:**

| Solution | When to Use | When NOT to Use | Target Independence |
|----------|-------------|-----------------|---------------------|
| A | Yes (line 389-403) | Yes (line 404-417) | Yes with checklist (line 409-416) |
| B | Yes (line 423-446) | Yes (line 436-438) | Implicit |
| C | Yes (line 496-520) | Implicit in "When NOT to use" context | Implicit |

**Analysis A**: Solution A provides the most comprehensive guidance including an explicit "Independence Checklist" with checkboxes.

**Usability Scores:**
- **Solution A: 4.1/5** - Explicit arguments, comprehensive best practices
- **Solution B: 4.2/5** - More natural language, slightly easier entry point
- **Solution C: 4.0/5** - Adequate but comparison table adds clarity

---

### Clarity (Weight: 0.15)

**Well-documented, clear instructions:**

| Solution | Structure | Tables | Code Examples |
|----------|-----------|--------|---------------|
| A | Clear headers, numbered phases | 7 tables | Markdown code blocks |
| B | Clear headers, numbered phases | 5 tables | Markdown code blocks |
| C | Clear headers, numbered phases | 6 tables | Markdown code blocks |

**Analysis A**: Solution A has excellent documentation structure with consistent formatting. The theoretical foundation section adds educational value.

**Analysis B**: Solution B is well-documented but the self-critique section is more verbose (54 lines vs 27 lines in A's critique section).

**Analysis C**: Solution C is clear but lacks the depth of explanation found in A.

**Key differentiator explanation:**

| Solution | Differentiator from launch-sub-agent | Differentiator from do-competitively |
|----------|-------------------------------------|-------------------------------------|
| A | Yes (lines 15-16) | Not mentioned |
| B | Yes (lines 19-25) | Yes (lines 20) |
| C | Yes (lines 25-27) | Yes (lines 26) |

**Analysis B and C**: Both provide clearer differentiation from related commands with a "Related commands" section.

**Clarity Scores:**
- **Solution A: 4.3/5** - Excellent structure, theoretical grounding
- **Solution B: 4.0/5** - Good but verbose in places
- **Solution C: 3.9/5** - Adequate, comparison table is helpful

---

## Weighted Score Calculation

### Solution A
| Criterion | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Completeness | 4.5 | 0.25 | 1.125 |
| Correctness | 4.4 | 0.25 | 1.100 |
| Design Quality | 4.3 | 0.20 | 0.860 |
| Usability | 4.1 | 0.15 | 0.615 |
| Clarity | 4.3 | 0.15 | 0.645 |
| **Total** | | | **4.345** |

### Solution B
| Criterion | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Completeness | 4.3 | 0.25 | 1.075 |
| Correctness | 4.2 | 0.25 | 1.050 |
| Design Quality | 4.0 | 0.20 | 0.800 |
| Usability | 4.2 | 0.15 | 0.630 |
| Clarity | 4.0 | 0.15 | 0.600 |
| **Total** | | | **4.155** |

### Solution C
| Criterion | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Completeness | 3.8 | 0.25 | 0.950 |
| Correctness | 4.0 | 0.25 | 1.000 |
| Design Quality | 3.9 | 0.20 | 0.780 |
| Usability | 4.0 | 0.15 | 0.600 |
| Clarity | 3.9 | 0.15 | 0.585 |
| **Total** | | | **3.915** |

---

## Self-Verification

**Questions Asked:**

1. **Am I biased toward longer solutions?** Solution A is 458 lines, B is 465 lines, C is 529 lines. Am I penalizing C for length or rewarding A for some other reason?

2. **Did I verify the Task tool usage is actually correct?** All three solutions describe the Task tool - are they all equally correct?

3. **Is the mixed-model-per-target design in Solution C actually problematic, or is it a valid approach?**

4. **Am I undervaluing Solution B's detailed self-critique template?**

5. **Did I properly account for the explicit argument flags in Solution A vs natural language parsing in B and C?**

**Answers:**

1. **Length bias check**: Solution C is actually the longest (529 lines) but scored lowest. Solution A (458 lines) scored highest. I'm not showing length bias - in fact, Solution A scores highest despite being shorter than C, primarily because it's more focused and less repetitive. The conciseness in A is a feature. **No adjustment needed.**

2. **Task tool verification**: Re-examining the Task tool usage:
   - A: Describes tool conceptually but doesn't show explicit invocation syntax
   - B: Shows parameters clearly: `description`, `prompt`, `model`
   - C: Shows the most explicit example with three parallel invocations

   All three are correct, but C is actually the most explicit about HOW to invoke Task tool in parallel. I may have under-credited C here. However, B and C's Task tool sections are nearly equivalent in correctness. **Minor adjustment: C's Correctness should remain 4.0 - the mixed model approach is still a concern.**

3. **Mixed model assessment**: Re-examining Solution C's Example 2 (lines 424-449):
   ```
   **Analysis:**
   - `algorithm.ts`: High complexity (core algorithm optimization) -> Opus
   - `settings.ts`: Low complexity (config file) -> Haiku
   - `format.ts`: Medium complexity (utility optimization) -> Sonnet
   ```
   This contradicts the stated principle in Solution B (line 111): "Same model for all targets: When executing the same task type across targets, typically use ONE model consistently for predictability."

   Solution A explicitly states (line 80): "Same configuration for all parallel agents (ensures consistent quality)"

   The mixed model approach in C is architecturally questionable because:
   - It complicates result aggregation (comparing outputs from different capability models)
   - It introduces inconsistency in how similar issues are handled
   - The reference pattern (`/launch-sub-agent`) uses single model selection per task

   **This confirms my assessment - C's design choice is problematic.**

4. **Solution B's self-critique value**: Re-examining B's self-critique (lines 192-246):
   - More structured with explicit question categories
   - Includes "Why It Matters" column
   - Has detailed "Evidence-Based Answers" section

   This is actually more thorough than A's critique section. However, it's also more verbose (54 lines vs 27 lines in A). The additional structure may not add proportional value. **No significant adjustment needed - usability slightly higher for B is already reflected.**

5. **Explicit argument flags**: The `/launch-sub-agent` command uses explicit flags:
   ```
   argument-hint: Task description (e.g., "Implement user authentication"...) [--model opus|sonnet|haiku] [--agent <agent-name>] [--output <path>]
   ```

   Solution A follows this pattern exactly with `--files` and `--targets` flags. This is objectively more consistent with the project's existing patterns. B and C's natural language parsing is more user-friendly but less predictable. **No adjustment needed - A's pattern alignment is correctly valued.**

**Adjustments Made**: None - verification confirmed the original assessment.

---

## Key Strengths

### Solution A
1. **Explicit argument handling**: `--files` and `--targets` flags provide predictable, scriptable interface consistent with existing `/launch-sub-agent` pattern
2. **Theoretical grounding**: Academic references (Kojima et al., Bai et al.) provide educational context and justify design decisions
3. **Independence checklist**: Explicit checklist (lines 409-416) helps users verify parallelization safety

### Solution B
1. **Comprehensive self-critique**: Most detailed verification template with structured evidence collection
2. **Risk assessment dimension**: Adds "Risk Assessment" to model selection matrix, useful for critical code
3. **Clear related commands**: Explicitly differentiates from `/launch-sub-agent` and `/do-competitively`

### Solution C
1. **Explicit parallel dispatch**: Most detailed Task tool invocation example showing simultaneous launch pattern
2. **Comparison table**: Clear comparison with related commands (lines 523-529)
3. **Failure handling**: Explicit failure handling section (lines 369-375)

---

## Areas for Improvement

### Solution A
1. **Missing related commands reference** - Priority: Low
   - Evidence: No explicit mention of `/do-competitively` for contrast
   - Impact: Users may be confused about when to use which command
   - Suggestion: Add a "Related Commands" section similar to B/C

### Solution B
1. **Inconsistent phase numbering** - Priority: Medium
   - Evidence: "Phase 2.5" breaks clean phase structure
   - Impact: Harder to reference and discuss specific phases
   - Suggestion: Integrate specialized agents into Phase 2 or make it Phase 3

2. **Missing explicit argument flags** - Priority: Medium
   - Evidence: Relies on natural language parsing only
   - Impact: Less predictable, harder to script
   - Suggestion: Add explicit `--files` and `--targets` flags

### Solution C
1. **Mixed model per target approach** - Priority: High
   - Evidence: Example 2 shows Opus/Haiku/Sonnet for different targets in same batch
   - Impact: Inconsistent quality, harder to compare results
   - Suggestion: Recommend single model for consistency, allow override only with explicit flag

2. **Missing theoretical references** - Priority: Low
   - Evidence: No academic citations for CoT or self-critique
   - Impact: Less educational value
   - Suggestion: Add brief citations like Solution A

---

## Confidence Assessment

**Confidence Level**: High

**Confidence Factors**:
- Evidence strength: Strong - Multiple specific quotes and line references
- Criterion clarity: Clear - Requirements were well-defined in the task
- Edge cases: Handled - Mixed model approach in C identified as edge case

---

## Final Recommendation

**VOTE: Solution A**

Solution A demonstrates the best overall implementation of the `/do-in-parallel` command. Its explicit argument handling, consistent architectural patterns, and theoretical grounding make it the strongest candidate. While Solution B offers a more detailed self-critique template and Solution C provides better Task tool invocation examples, Solution A's alignment with existing project patterns and comprehensive model selection logic give it the edge.

**Recommended action**: Adopt Solution A as the base, optionally incorporating:
- Solution C's explicit parallel dispatch example code (Phase 5)
- Solution B's related commands section

**Final Scores**:
- Solution A: **4.35/5.0** (PASS)
- Solution B: **4.15/5.0** (PASS)
- Solution C: **3.90/5.0** (FAIL - below 4.0 threshold)
