sadd:launch-sub-agent

sadd:launch-sub-agent — an installable skill for AI agents, published by neolabhq/context-engineering-kit.

INSTALLATION
npx skills add https://github.com/neolabhq/context-engineering-kit --skill sadd:launch-sub-agent
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

launch-sub-agent

Process

Phase 1: Task Analysis with Zero-shot CoT

Before dispatching, analyze the task systematically. Think through step by step:

Let me analyze this task step by step to determine the optimal configuration:

-

Task Type Identification

"What type of work is being requested?"

  • Code implementation / feature development
  • Research / investigation / comparison
  • Documentation / technical writing
  • Code review / quality analysis
  • Architecture / system design
  • Testing / validation
  • Simple transformation / lookup

-

Complexity Assessment

"How complex is the reasoning required?"

  • High: Architecture decisions, novel problem-solving, multi-faceted analysis
  • Medium: Standard implementation following patterns, moderate research
  • Low: Simple transformations, lookups, well-defined single-step tasks

-

Output Size Estimation

"How extensive is the expected output?"

  • Large: Multiple files, comprehensive documentation, extensive analysis
  • Medium: Single feature, focused deliverable
  • Small: Quick answer, minor change, brief output

-

Domain Expertise Check

"Does this task match a specialized agent profile?"

  • Development: code, implement, feature, endpoint, TDD, tests
  • Research: investigate, compare, evaluate, options, library
  • Documentation: document, README, guide, explain, tutorial
  • Architecture: design, system, structure, scalability
  • Exploration: understand, navigate, find, codebase patterns
### Phase 2: Model Selection

Select the optimal model based on task analysis:

| Task Profile | Recommended Model | Rationale |

|--------------|-------------------|-----------|

| **Complex reasoning** (architecture, design, critical decisions) | `opus` | Maximum reasoning capability |

| **Specialized domain** (matches agent profile) | Opus + Specialized Agent | Domain expertise + reasoning power |

| **Non-complex but long** (extensive docs, verbose output) | `sonnet[1m]` | Good capability, cost-efficient for length |

| **Simple and short** (trivial tasks, quick lookups) | `haiku` | Fast, cost-effective for easy tasks |

| **Default** (when uncertain) | `opus` | Optimize for quality over cost |

**Decision Tree:**

Is task COMPLEX (architecture, design, novel problem, critical decision)?

|

+-- YES --> Use Opus (highest capability)

| |

| +-- Does it match a specialized domain?

| +-- YES --> Include specialized agent prompt

| +-- NO --> Use Opus alone

|

+-- NO --> Is task SIMPLE and SHORT?

|

+-- YES --> Use Haiku (fast, cheap)

|

+-- NO --> Is output LONG but task not complex?

|

+-- YES --> Use Sonnet (balanced)

|

+-- NO --> Use Opus (default)

### Phase 3: Specialized Agent Matching

If the task matches a specialized domain, incorporate the relevant agent prompt. Specialized agents provide domain-specific best practices, quality standards, and structured approaches that improve output quality.

**Decision:** Use specialized agent when task clearly benefits from domain expertise. Skip for trivial tasks where specialization adds unnecessary overhead.

**Agents:** Available specialized agents depends on project and plugins installed. Common agents from the `sdd` plugin include: `sdd:developer`, `sdd:researcher`, `sdd:software-architect`, `sdd:tech-lead`, `sdd:team-lead`, `sdd:qa-engineer`, `sdd:code-explorer`, `sdd:business-analyst`. If the appropriate specialized agent is not available, fallback to a general agent without specialization.

**Integration with Model Selection:**

- Specialized agents are combined WITH model selection, not instead of

- Complex task + specialized domain = Opus + Specialized Agent

- Simple task matching domain = Haiku without specialization (overhead not justified)

**Usage:**

1. Read the agent definition

2. Include the agent's instructions in the sub-agent prompt AFTER the CoT prefix

3. Combine with Zero-shot CoT prefix and Critique suffix

### Phase 4: Construct Sub-Agent Prompt

Build the sub-agent prompt with these mandatory components:

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

Reasoning Approach

Before taking any action, you MUST think through the problem systematically.

Let's approach this step by step:

  1. "Let me first understand what is being asked..."

- What is the core objective?

- What are the explicit requirements?

- What constraints must I respect?

  1. "Let me break this down into concrete steps..."

- What are the major components of this task?

- What order should I tackle them?

- What dependencies exist between steps?

  1. "Let me consider what could go wrong..."

- What assumptions am I making?

- What edge cases might exist?

- What could cause this to fail?

  1. "Let me verify my approach before proceeding..."

- Does my plan address all requirements?

- Is there a simpler approach?

- Am I following existing patterns?

Work through each step explicitly before implementing.


#### 4.2 Task Body

<task>

{Task description from $ARGUMENTS}

</task>

<constraints>

{Any constraints inferred from the task or conversation context}

</constraints>

<context>

{Relevant context: files, patterns, requirements, codebase information}

</context>

<output>

{Expected deliverable: format, location, structure}

</output>


#### 4.3 Self-Critique Suffix (REQUIRED - MUST BE LAST)

Self-Critique Loop (MANDATORY)

Before completing, you MUST verify your work. Submitting unverified work is UNACCEPTABLE.

1. Generate 5 Verification Questions

Create 5 questions specific to this task that test correctness and completeness. There example questions:

#Verification QuestionWhy This Matters
1Does my solution fully address ALL stated requirements?Partial solutions = failed task
2Have I verified every assumption against available evidence?Unverified assumptions = potential failures
3Are there edge cases or error scenarios I haven't handled?Edge cases cause production issues
4Does my solution follow existing patterns in the codebase?Pattern violations create maintenance debt
5Is my solution clear enough for someone else to understand and use?Unclear output reduces value

2. Answer Each Question with Evidence

For each question, examine your solution and provide specific evidence:

[Q1] Requirements Coverage:

  • Requirement 1: [COVERED/MISSING] - [specific evidence from solution]
  • Requirement 2: [COVERED/MISSING] - [specific evidence from solution]
  • Gap analysis: [any gaps identified]

[Q2] Assumption Verification:

  • Assumption 1: [assumption made] - [VERIFIED/UNVERIFIED] - [evidence]
  • Assumption 2: [assumption made] - [VERIFIED/UNVERIFIED] - [evidence]

[Q3] Edge Case Analysis:

  • Edge case 1: [scenario] - [HANDLED/UNHANDLED] - [how]
  • Edge case 2: [scenario] - [HANDLED/UNHANDLED] - [how]

[Q4] Pattern Adherence:

  • Pattern 1: [pattern name] - [FOLLOWED/DEVIATED] - [evidence]
  • Pattern 2: [pattern name] - [FOLLOWED/DEVIATED] - [evidence]

[Q5] Clarity Assessment:

  • Is the solution well-organized? [YES/NO]
  • Are complex parts explained? [YES/NO]
  • Could someone else use this immediately? [YES/NO]

3. Revise If Needed

If ANY verification question reveals a gap:

  1. STOP - Do not submit incomplete work
  1. FIX - Address the specific gap identified
  1. RE-VERIFY - Confirm the fix resolves the issue
  1. DOCUMENT - Note what was changed and why

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


### Phase 5: Dispatch Sub-Agent

Use the Task tool to dispatch with the selected configuration:

Use Task tool:

  • description: "Sub-agent: {brief task summary}"
  • prompt: {constructed prompt with CoT prefix + task + critique suffix}
  • model: {selected model - opus/sonnet/haiku}
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