Tool Reference
Nity exposes 12 tools across 5 registered tool groups. The 5 groups (nity_analyze, nity_execute, nity_quality_gate, nity_reflect, nity_skills) are the user-facing surface; each maps to one or more of the primitives documented here.
Execution Tools
autonomous_loop
Run iterative development with self-correction. The core of Nity's autonomous capability.
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | ✅ | The task description to execute |
maxIterations | number | — | Maximum iteration count (default: 10) |
exitStrategy | "success" | "quality" | "manual" | — | When to stop iterating |
Returns: ToolResult with data: { iterations: number, outcome: string, episodes: Episode[] }
{
"tool": "nity_execute",
"params": {
"task": "Add input validation to the login form",
"maxIterations": 5,
"exitStrategy": "quality"
}
}recommend_adapter
Get the best execution approach for a task.
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | ✅ | The task to get an adapter recommendation for |
Returns: ToolResult with data: ExecutionStrategy
{
"tool": "nity_tools",
"params": {
"action": "recommend_adapter",
"task": "Refactor database layer to use connection pooling"
}
}Brain & Memory Tools
load_brain
Retrieve the current session's brain context — accumulated memories, active skills, and project summary.
| Parameter | Type | Required | Description |
|---|---|---|---|
| (none) | — | — | Uses current session context automatically |
Returns: ToolResult with data: BrainContext
{
"tool": "nity_analyze",
"params": { "action": "load_brain" }
}record_episode
Store a completed task outcome for future recall and learning.
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | ✅ | Description of the completed task |
outcome | "success" | "failure" | "partial" | ✅ | Task outcome status |
notes | string | — | Additional context or learnings |
Returns: ToolResult with data: Episode
{
"tool": "nity_reflect",
"params": {
"action": "record_episode",
"task": "Implement rate limiting middleware",
"outcome": "success",
"notes": "Used token bucket algorithm, 100 req/min default"
}
}recall_episodes
Search for similar past tasks to inform current approach.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | string | ✅ | Search query for similar episodes |
limit | number | — | Max results to return (default: 5) |
Returns: ToolResult with data: Episode[]
{
"tool": "nity_reflect",
"params": {
"action": "recall_episodes",
"query": "authentication middleware",
"limit": 3
}
}Skill Tools
skill_find
Find relevant learned skills matching a query.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | string | ✅ | Search query for skill matching |
Returns: ToolResult with data: SkillEntry[]
{
"tool": "nity_skills",
"params": {
"action": "find",
"query": "database migration"
}
}skill_create
Register a new learned skill for future reuse.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | ✅ | Human-readable skill name |
trigger | string | ✅ | Pattern that activates this skill |
prompt | string | ✅ | The skill's instruction set |
Returns: ToolResult with data: SkillEntry
Skills are only created when NityConfig.skills.autoCreate is true and
the self-reflection system determines the pattern is reusable. Direct
skill_create calls bypass this gate — use sparingly.
{
"tool": "nity_skills",
"params": {
"action": "create",
"name": "FastAPI CRUD Generator",
"trigger": "create CRUD endpoints for * model",
"prompt": "Generate FastAPI CRUD routes with Pydantic schemas..."
}
}Analysis Tools
analyze_task
Decompose a task into subtasks with complexity scoring.
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | ✅ | The task to decompose |
Returns: ToolResult with data: TaskAnalysis
{
"tool": "nity_analyze",
"params": {
"action": "analyze",
"task": "Build a real-time dashboard with WebSocket support"
}
}Response includes:
subtasks[]— ordered list with dependency graphcomplexity—simple|moderate|complexestimatedIterations— total iteration estimaterequiredCapabilities— what the task needs (e.g.,websocket,react,state-management)
validate_evidence
Check that a claim is supported by evidence. Used by quality gates.
| Parameter | Type | Required | Description |
|---|---|---|---|
claim | string | ✅ | The claim to validate |
evidence | string | ✅ | Supporting evidence to check against the claim |
Returns: ToolResult with data: { valid: boolean, confidence: number, gaps: string[] }
{
"tool": "nity_quality_gate",
"params": {
"action": "validate_evidence",
"claim": "All user inputs are sanitized before database queries",
"evidence": "Uses parameterized queries in models/user.ts lines 45-78"
}
}Quality & Reflection Tools
quality_gate
Run a quality check against a specific dimension.
| Parameter | Type | Required | Description |
|---|---|---|---|
dimension | string | ✅ | Quality dimension to check (e.g., correctness, security, performance, style) |
Returns: ToolResult with data: QualityDimension
The dimension parameter must match one of the configured dimensions in
NityConfig.quality.dimensions. Default dimensions: correctness,
security, performance, style.
{
"tool": "nity_quality_gate",
"params": {
"dimension": "security"
}
}self_reflect
Trigger post-task reflection to extract learnings.
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | ✅ | The task to reflect on |
Returns: ToolResult with data: ReflectionRecord
{
"tool": "nity_reflect",
"params": {
"action": "reflect",
"task": "Optimize database query performance"
}
}Reflection produces:
- Insights — categorized learnings (approach, quality, efficiency, gaps)
- Confidence — how confident the reflection is in its findings
- Applied skills — which skills were updated based on this reflection
evolve_strategy
Improve the execution approach based on accumulated evidence.
| Parameter | Type | Required | Description |
|---|---|---|---|
focusArea | string | ✅ | Area to optimize (e.g., speed, quality, coverage) |
Returns: ToolResult with data: { previous: ExecutionStrategy, updated: ExecutionStrategy, rationale: string }
evolve_strategy is typically called by the MetaLearner during periodic
optimization cycles (controlled by NityConfig.meta.optimizeInterval).
Manual invocation is useful after noticing systematic patterns.
{
"tool": "nity_reflect",
"params": {
"action": "evolve_strategy",
"focusArea": "speed"
}
}Tool Group Mapping
The 5 registered tool groups map to the 12 primitives:
| Registered Tool | Primitives Exposed |
|---|---|
nity_analyze | load_brain, analyze_task |
nity_execute | autonomous_loop, recommend_adapter |
nity_quality_gate | quality_gate, validate_evidence |
nity_reflect | record_episode, recall_episodes, self_reflect, evolve_strategy |
nity_skills | skill_find, skill_create |
Next Steps
- Extension Entry Point ← — How tools are registered
- Data Flows → — How tools compose into workflows
- Overview → — Architecture and component systems