> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/thiagofinch/mega-brain/llms.txt
> Use this file to discover all available pages before exploring further.

# Core Tasks

> Atomic task definitions and execution protocols

# Core Tasks

Core tasks are atomic, reusable building blocks for workflows. Each task follows the HO-TP anatomy pattern.

## Task Anatomy

Every task includes:

<ResponseField name="task_name" type="string" required>
  Human-readable task name
</ResponseField>

<ResponseField name="task_id" type="string" required>
  Unique task identifier (e.g., `TSK-020`)
</ResponseField>

<ResponseField name="execution_type" type="string" required>
  Execution mode: `Agent`, `Script`, `Manual`, `Hook`
</ResponseField>

<ResponseField name="responsible_executor" type="string" required>
  Who/what executes: `@jarvis`, `@agent:{id}`, `@human`, `@hook:{name}`
</ResponseField>

<ResponseField name="input" type="object" required>
  Required input parameters and types
</ResponseField>

<ResponseField name="output" type="object" required>
  Expected output format and location
</ResponseField>

<ResponseField name="acceptance_criteria" type="array" required>
  Checklist for task completion validation
</ResponseField>

***

## Available Tasks

### extract-dna

Extract cognitive DNA from insights and themes.

**Task ID:** `TSK-020`

**Execution:**

* **Type:** Agent
* **Executor:** `@jarvis`

**Inputs:**

<ParamField path="insights" type="json" required>
  Extracted insights from content
</ParamField>

<ParamField path="themes" type="array" required>
  Theme classifications
</ParamField>

<ParamField path="source_id" type="string" required>
  Source identifier (e.g., "CG", "JM")
</ParamField>

<ParamField path="chunks" type="array" required>
  Content chunks for reference
</ParamField>

**Outputs:**

<ResponseField name="dna_config" type="yaml">
  5-layer DNA structure saved to `agents/persons/{name}/DNA-CONFIG.yaml`
</ResponseField>

<ResponseField name="layer_counts" type="json">
  Count of items per DNA layer (L1-L5)
</ResponseField>

**Phases:**

<Expandable title="Phase 1: Philosophy Extraction (L1)">
  **Quality Gate:** QG-DNA-001

  1. Identify core beliefs and worldview statements
  2. Extract value system indicators
  3. Map to PHILOSOPHIES layer
</Expandable>

<Expandable title="Phase 2: Mental Models (L2)">
  **Quality Gate:** QG-DNA-002

  1. Identify thinking frameworks
  2. Extract decision-making patterns
  3. Map to MENTAL-MODELS layer
</Expandable>

<Expandable title="Phase 3: Heuristics (L3)">
  **Quality Gate:** QG-DNA-003

  1. Extract practical rules
  2. Identify decision shortcuts
  3. Map to HEURISTICS layer
</Expandable>

<Expandable title="Phase 4: Frameworks (L4)">
  **Quality Gate:** QG-DNA-004

  1. Identify structured methodologies
  2. Extract process definitions
  3. Map to FRAMEWORKS layer
</Expandable>

<Expandable title="Phase 5: Methodologies (L5)">
  **Quality Gate:** QG-DNA-005

  1. Extract step-by-step implementations
  2. Identify tactical procedures
  3. Map to METHODOLOGIES layer
</Expandable>

**Acceptance Criteria:**

* All 5 DNA layers populated
* Minimum 3 items per layer
* Source citations for each item (`^[chunk_id]`)
* Valid YAML structure

**Handoff:**

* **Next Task:** `trigger-agent` when `dna_complete`
* **Data Passed:** DNA-CONFIG path, layer\_counts

**Source:** `core/tasks/extract-dna.md:1-115`

***

### detect-role

Detect job roles and functions mentioned in content.

**Task ID:** `TSK-012`

**Execution:**

* **Type:** Script
* **Executor:** `@script:role_detector.py`

**Inputs:**

<ParamField path="text" type="string" required>
  Content to analyze for role mentions
</ParamField>

<ParamField path="source_id" type="string" optional>
  Source identifier for tracking
</ParamField>

**Detection Levels:**

1. **Direct (weight: 1.0)** - Role name appears explicitly
2. **Inferred (weight: 0.7)** - Activity implies role (e.g., "writing sales copy" → COPYWRITER)
3. **Emergent (weight: 0.5)** - Unknown role detected via generic patterns

**Outputs:**

<ResponseField name="roles_detected" type="array">
  List of detected roles with detection type, weight, and context
</ResponseField>

<ResponseField name="new_roles" type="array">
  Emergent roles not in vocabulary (candidates for agent creation)
</ResponseField>

<ResponseField name="triggers_activated" type="array">
  Roles that crossed threshold for agent creation
</ResponseField>

**Registry Update:**

* Increments `mention_count` in `ENTITY-REGISTRY.json`
* Updates `mention_breakdown` (direct/inferred/emergent)
* Calculates `weighted_score`
* Logs detection in `detection_history`

**Trigger Thresholds:**

* **Established:** `weighted_score >= 10` AND `sources >= 2`
* **Emerging:** `weighted_score >= 5` AND `sources >= 1`

**Source:** `core/tasks/detect-role.md:1-17`, `core/intelligence/role_detector.py:1-856`

***

### normalize-entities

Canonicalize entity names (persons, themes, roles, concepts).

**Task ID:** `TSK-008`

**Execution:**

* **Type:** Script
* **Executor:** `@script:entity_normalizer.py`

**Inputs:**

<ParamField path="name" type="string" required>
  Raw entity name to normalize
</ParamField>

<ParamField path="entity_type" type="string" required>
  Type: `person`, `theme`, `role`, `concept`
</ParamField>

<ParamField path="source_id" type="string" optional>
  Source that mentioned this entity
</ParamField>

<ParamField path="domain_hint" type="string" optional>
  Domain context for boost matching (e.g., "SALES")
</ParamField>

**Resolution Order:**

1. **Exact match** on canonical names (score: 1.0)
2. **Alias match** on known aliases (score: 1.0)
3. **Fuzzy match** via difflib (threshold: 0.85)
4. **Domain boost** for same-domain entities (+0.10 bonus)
5. **Taxonomy check** against DOMAINS-TAXONOMY.yaml
6. **New entity creation** if no match found

**Auto-Merge Rules:**

* Score ≥ 0.95: Auto-merge, add as alias
* Score 0.85-0.94: Add to review queue
* Score \< 0.85: Create new entity

**Outputs:**

<ResponseField name="canonical" type="string">
  Canonical entity name
</ResponseField>

<ResponseField name="match_type" type="string">
  Match method: `exact`, `alias`, `fuzzy`, `domain_boost`, `taxonomy`, `new`
</ResponseField>

<ResponseField name="score" type="number">
  Similarity score (0.0-1.0)
</ResponseField>

<ResponseField name="created" type="boolean">
  Whether new entity was created
</ResponseField>

**Canonical Name Formats:**

* **Person:** Title Case ("Alex Hormozi")
* **Role:** UPPER-CASE-WITH-HYPHENS ("SALES-MANAGER")
* **Theme:** lowercase-with-hyphens ("processo-vendas")
* **Concept:** Title Case ("Farm System")

**Source:** `core/tasks/normalize-entities.md:1-16`, `core/intelligence/entity_normalizer.py:1-566`

***

### analyze-themes

Detect and classify themes in content.

**Task ID:** `TSK-015`

**Execution:**

* **Type:** Script
* **Executor:** `@script:theme_analyzer.py`

**Inputs:**

<ParamField path="text" type="string" required>
  Content to analyze for themes
</ParamField>

<ParamField path="source_id" type="string" optional>
  Source identifier
</ParamField>

**Theme Categories:**

| Code | Theme               | Description               |
| ---- | ------------------- | ------------------------- |
| 01   | ESTRUTURA-TIME      | Team structure, roles     |
| 02   | PROCESSO-VENDAS     | Sales process, techniques |
| 03   | CONTRATACAO         | Hiring, onboarding        |
| 04   | COMISSIONAMENTO     | Compensation structures   |
| 05   | METRICAS            | Performance metrics       |
| 06   | FUNIL-APLICACAO     | Lead qualification        |
| 07   | PRICING             | Pricing strategy          |
| 08   | FERRAMENTAS         | Tools, tech stack         |
| 09   | GESTAO              | Management practices      |
| 10   | CULTURA-GAMIFICACAO | Culture, motivation       |
| 99   | SECUNDARIO          | Other insights            |

**Detection Logic:**

Uses keyword patterns and context analysis:

```python theme={null}
if mentions("roles", "team", "structure"):
    theme = "01-ESTRUTURA-TIME"
elif mentions("sales", "closing", "objection"):
    theme = "02-PROCESSO-VENDAS"
elif mentions("hire", "onboard", "recruit"):
    theme = "03-CONTRATACAO"
# ... etc
```

**Outputs:**

<ResponseField name="themes_detected" type="array">
  List of theme IDs with confidence scores
</ResponseField>

<ResponseField name="cross_references" type="array">
  Themes with secondary relevance
</ResponseField>

**Source:** `core/tasks/analyze-themes.md:1-17`

***

### process-batch

Process multiple files in batch with checkpointing.

**Task ID:** `TSK-025`

**Execution:**

* **Type:** Agent
* **Executor:** `@jarvis`

**Inputs:**

<ParamField path="file_list" type="array" required>
  List of file paths to process
</ParamField>

<ParamField path="workflow_id" type="string" required>
  Workflow to execute (e.g., "wf-pipeline-full")
</ParamField>

<ParamField path="checkpoint_interval" type="number" optional>
  Files per checkpoint (default: 1)
</ParamField>

**Behavior:**

* Processes files sequentially
* Creates checkpoint after each file
* Auto-resume on interruption
* Aggregates metrics across batch

**Outputs:**

<ResponseField name="batch_summary" type="object">
  Total files, success count, errors, processing time
</ResponseField>

<ResponseField name="checkpoints" type="array">
  List of checkpoint IDs created
</ResponseField>

**Source:** `core/tasks/process-batch.md:1-25`

***

### validate-cascade

Validate post-processing cascade completeness.

**Task ID:** `TSK-030`

**Execution:**

* **Type:** Script
* **Executor:** `@script:validate_cascade.py`

**Inputs:**

<ParamField path="source_id" type="string" required>
  Source identifier to validate
</ParamField>

**Validation Checks:**

1. **Agent Memories Updated** - All relevant agents have source in memory
2. **Dossiers Created** - Persons/themes have dossiers
3. **Knowledge Base Populated** - Insights written to correct categories
4. **Registry Consistency** - ENTITY-REGISTRY matches artifacts
5. **Cross-References Valid** - All links resolve correctly

**Outputs:**

<ResponseField name="validation_result" type="object">
  Pass/fail status per check with details
</ResponseField>

<ResponseField name="issues_found" type="array">
  List of issues with severity (CRITICAL, WARNING, INFO)
</ResponseField>

**Source:** `core/tasks/validate-cascade.md:1-21`

***

## Task Registry

All available tasks are indexed in `core/tasks/TASK-REGISTRY.md`:

```markdown theme={null}
| Task ID | Name | Executor | Status |
|---------|------|----------|--------|
| TSK-020 | extract-dna | @jarvis | active |
| TSK-012 | detect-role | @script | active |
| TSK-008 | normalize-entities | @script | active |
| TSK-015 | analyze-themes | @script | active |
| TSK-025 | process-batch | @jarvis | active |
| TSK-030 | validate-cascade | @script | active |
```

***

## Creating New Tasks

### Task Template

```yaml theme={null}
---
task: TSK-XXX
execution_type: Agent|Script|Manual|Hook
responsible: @jarvis|@agent:{id}|@human|@hook:{name}
---

## Task Anatomy

| Field | Value |
|-------|-------|
| task_name | Your Task Name |
| status | active|deprecated |
| responsible_executor | See above |
| execution_type | See above |
| input | {json object} |
| output | {json object} |
| action_items | {list} |
| acceptance_criteria | {checklist} |

## Inputs

[Document inputs]

## Outputs

[Document outputs]

## Execution

[Step-by-step instructions]

## Acceptance Criteria

- [ ] Criterion 1
- [ ] Criterion 2

## Handoff

| Next Task | Trigger | Data Passed |
|-----------|---------|-------------|
| task-id | condition | data |
```

### Conventions

1. **IDs:** Use `TSK-###` format (sequential)
2. **Files:** Use `kebab-case.md` in `core/tasks/`
3. **Atomicity:** One clear responsibility per task
4. **Idempotency:** Safe to re-run without side effects
5. **Testability:** Clear acceptance criteria

***

## See Also

* [Workflows](/api/core/workflows) - Task orchestration
* [Intelligence Layer](/api/core/intelligence) - Python scripts
* [Schemas](/api/core/schemas) - Data validation