<< All versions

Skill v1.0.1

currentAutomated scan100/100
synaptiai/agent-capability-standard/generate

+4 new

──Details
PublishedOctober 29, 2026 at 11:14 PM
Content Hashsha256:be4278923008f379...
Git SHA4ca65f8c08d8
Bump Typepatch
Compare with v1.0.0
──Files
Files (1 file, 11.6 KB)
SKILL.md11.6 KBactive
SKILL.md · 359 lines · 11.6 KB

name: generate description: Create a new artifact (text, code, plan, data) under specified constraints. Use when producing content, writing code, designing solutions, or synthesizing outputs. argument-hint: "[specification] [format] [constraints]" disable-model-invocation: false user-invocable: true allowed-tools: Read, Grep context: fork agent: explore metadata: version: "1.0.1"


Intent

Produce a new artifact that satisfies specified constraints and serves a defined purpose. Generation is creative synthesis bounded by requirements, not mere retrieval or transformation.

Success criteria:

  • Artifact satisfies all stated constraints
  • Rationale explains design decisions
  • Quality signals demonstrate fitness for purpose
  • Safety considerations documented

Compatible schemas:

  • schemas/output_schema.yaml

Inputs

ParameterRequiredTypeDescription
specificationYesstring\objectWhat to generate
formatNostringOutput format: markdown, json, yaml, typescript, etc.
constraintsNoobjectRequirements the artifact must satisfy

Inputs not listed here are outside the capability's contract: a workflow step that binds them gets W604 (STANDARD v1.1 §5.5).

Procedure

1) Clarify artifact requirements: Ensure constraints are understood

  • Must-have: absolute requirements (format, structure, compatibility)
  • Should-have: preferences (style, conventions, optimization)
  • Must-not-have: exclusions (patterns to avoid, security constraints)

2) Gather context: Collect relevant reference material

  • Read existing code/docs for style consistency
  • Identify patterns to follow or avoid
  • Understand integration points and dependencies

3) Design approach: Plan the generation strategy

  • Outline structure before detailed generation
  • Consider multiple approaches if request is complex
  • Document key design decisions

4) Generate artifact: Produce the content systematically

  • Follow identified patterns and conventions
  • Satisfy constraints in priority order
  • Document any constraints that conflict

5) Validate constraints: Verify each constraint is satisfied

  • Mark each constraint as satisfied/unsatisfied
  • Note any compromises or partial satisfaction

6) Assess quality: Evaluate fitness for purpose

  • Correctness: Does it work as intended?
  • Completeness: Is anything missing?
  • Maintainability: Is it understandable and modifiable?
  • Safety: Are there security or reliability concerns?

7) Document rationale: Explain why this design

  • Key decisions and their reasoning
  • Alternatives considered and why rejected
  • Known limitations or future considerations

8) Ground claims: Reference sources that informed generation

Output Contract

Return a structured object:

yaml
content: string | object # The generated artifact
metadata: # Generation metadata
type: string # text, code, plan, config, schema, etc.
format: string # markdown, json, yaml, typescript, etc.
constraints_used:
- constraint: string # Constraint description
satisfied: boolean # Was it met?
notes: string # How it was satisfied or why not
rationale: string # Why this design/approach
alternatives_considered: array[string] # Other approaches evaluated
quality_signals:
- metric: string # Quality dimension
value: number | string # Assessment
confidence: number # 0.0-1.0 in artifact quality
evidence_anchors: array[string] # References to source material
assumptions: array[string] # Conditions affecting the artifact
safety_notes: array[string] # Security/reliability considerations
next_actions: array[string] # Suggested follow-ups

Field Definitions

FieldTypeDescription
contentstring\objectThe generated artifact itself
metadataobjectGeneration metadata: type (category of content) and format
constraints_usedarrayEvaluation of constraint satisfaction
rationalestringDesign decision explanation
alternatives_consideredarrayOther approaches that were rejected
quality_signalsarrayQuality metrics and assessments
confidencenumber0.0-1.0 in artifact fitness
evidence_anchorsarray[string]Sources that informed generation
safety_notesarray[string]Security/reliability concerns
next_actionsarray[string]Recommended follow-up steps

Examples

Example 1: Generate API Endpoint

Input:

yaml
specification:
artifact_type: "code"
endpoint: "POST /api/users"
schema: "{ name: string, email: string, role: 'admin' | 'user' }"
constraints:
must_have:
- "TypeScript with strict mode"
- "Express.js middleware pattern"
- "Input validation with Zod"
- "Return 200 on success, 400 on validation error, 500 on server error"
format: "typescript"

Output:

yaml
content: |
import { Request, Response, NextFunction } from 'express';
import { z } from 'zod';
const CreateUserSchema = z.object({
name: z.string().min(1).max(100),
email: z.string().email(),
role: z.enum(['admin', 'user'])
});
type CreateUserInput = z.infer<typeof CreateUserSchema>;
export async function createUser(
req: Request,
res: Response,
next: NextFunction
): Promise<void> {
try {
const parsed = CreateUserSchema.safeParse(req.body);
if (!parsed.success) {
res.status(400).json({
error: 'Validation failed',
details: parsed.error.issues
});
return;
}
const userData: CreateUserInput = parsed.data;
// TODO: Implement actual user creation logic
const user = await userService.create(userData);
res.status(200).json({ user });
} catch (error) {
next(error);
}
}
metadata:
type: "code"
format: "typescript"
constraints_used:
- constraint: "TypeScript with strict mode"
satisfied: true
notes: "All types explicit, strict null checks compatible"
- constraint: "Express.js middleware pattern"
satisfied: true
notes: "Standard (req, res, next) signature with async handler"
- constraint: "Input validation with Zod"
satisfied: true
notes: "Zod schema with safeParse for type-safe validation"
- constraint: "HTTP status codes"
satisfied: true
notes: "200 success, 400 validation error, 500 via error middleware"
rationale: "Used safeParse over parse for explicit error handling without exceptions. Separated schema definition for reuse in tests. Left business logic as TODO for service layer."
alternatives_considered:
- "class-validator with decorators - rejected for runtime overhead"
- "Manual validation - rejected for type safety"
quality_signals:
- metric: "type_safety"
value: "high"
- metric: "error_handling"
value: "comprehensive"
- metric: "testability"
value: "high"
confidence: 0.9
evidence_anchors:
- "zod:docs:safeParse"
- "express:docs:error-handling"
assumptions:
- "userService exists and is imported"
- "Error middleware handles uncaught exceptions"
safety_notes:
- "Email validation does not prevent all injection attacks"
- "Consider rate limiting for user creation endpoint"
next_actions:
- "Implement userService.create method"
- "Add authentication middleware"
- "Write unit tests for validation logic"

Evidence pattern: Read existing codebase for patterns, reference library documentation for best practices.


Example 2: Generate Configuration Schema

Input:

yaml
specification:
artifact_type: "schema"
description: "Database connection configuration"
constraints:
must_have:
- "JSON Schema draft-07"
- "Required fields: host, port, database"
- "Optional: ssl, poolSize, timeout"
should_have:
- "Sensible defaults where appropriate"
format: "json"

Output:

yaml
content:
$schema: "http://json-schema.org/draft-07/schema#"
title: "DatabaseConfig"
type: "object"
required: ["host", "port", "database"]
properties:
host:
type: "string"
description: "Database server hostname"
examples: ["localhost", "db.example.com"]
port:
type: "integer"
minimum: 1
maximum: 65535
description: "Database server port"
default: 5432
database:
type: "string"
description: "Database name"
minLength: 1
ssl:
type: "boolean"
description: "Enable SSL/TLS connection"
default: true
poolSize:
type: "integer"
minimum: 1
maximum: 100
description: "Connection pool size"
default: 10
timeout:
type: "integer"
minimum: 0
description: "Connection timeout in milliseconds"
default: 30000
additionalProperties: false
metadata:
type: "schema"
format: "json"
constraints_used:
- constraint: "JSON Schema draft-07"
satisfied: true
notes: "$schema declaration included"
- constraint: "Required fields: host, port, database"
satisfied: true
notes: "Listed in required array"
- constraint: "Optional: ssl, poolSize, timeout"
satisfied: true
notes: "Not in required, have defaults"
- constraint: "Sensible defaults"
satisfied: true
notes: "port=5432 (PostgreSQL), ssl=true, poolSize=10, timeout=30s"
rationale: "Used PostgreSQL port as default assuming most common use case. SSL enabled by default for security. Pool size 10 balances resource usage with concurrency."
alternatives_considered:
- "MySQL port 3306 - rejected, PostgreSQL more common in modern stacks"
quality_signals:
- metric: "completeness"
value: "high"
- metric: "documentation"
value: "descriptions and examples included"
confidence: 0.95
evidence_anchors:
- "json-schema:draft-07:spec"
assumptions:
- "PostgreSQL is the target database"
- "Production deployment expects SSL"
safety_notes:
- "Consider encrypting credentials in actual config files"
- "poolSize limits should match database max_connections"
next_actions:
- "Add validation for connection string format"
- "Consider environment variable substitution"

Verification

  • [ ] All required constraints marked as satisfied
  • [ ] Artifact format matches requested format
  • [ ] Quality signals include at least correctness and completeness
  • [ ] Rationale explains key design decisions
  • [ ] Safety notes address security considerations

Verification tools: Read (for pattern consistency), schema validators, linters

Safety Constraints

  • mutation: false
  • requires_checkpoint: false
  • requires_approval: false
  • risk: low

Capability-specific rules:

  • Generated code must not contain hardcoded secrets or credentials
  • Flag any security-sensitive patterns in generated content
  • Do not generate content that violates constraints - report conflicts instead
  • Include safety_notes for any security-relevant artifact

Composition Patterns

Commonly follows:

  • compare - Generate solution based on comparison winner
  • plan - Generate artifacts specified in plan
  • identify - Generate based on identified requirements
  • discover - Generate to address discovered gaps

Commonly precedes:

  • verify - Generated artifacts should be verified
  • act - Generated content may be written to files
  • critique - Generated plans should be critiqued

Anti-patterns:

  • Never generate without constraints (unbounded generation)
  • Avoid generate for retrieval (use search or retrieve)
  • Do not use generate for analysis (use estimate, compare, etc.)

Workflow references:

  • See reference/composition_patterns.md#capability-gap-analysis for generate-plan usage
  • See reference/composition_patterns.md#debug-code-change for code generation in fixes
← v1.0.0All versions