Results for “output-schema”

Runs SQL queries and data conversions on CSV, Parquet, and JSON files using the DuckDB command-line interface, including schema inspection and output formatting.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Blocks Edit/Write/Bash actions until the agent presents concrete facts about imports, data schemas, and the user's instruction, improving output quality.

Use this skill for Astro static output, islands hydration, content collections, CWV, schema and metadata. Trigger when the task involves seo work related to Astro Islands SEO, implementation, audits, debugging, strategy, or validation.

Validates agent outputs against schemas and quality criteria, scores confidence, detects hallucinations, monitors convergence, decides when to iterate, and synthesizes actionable feedback. Use when checking if a node's output is acceptable, scoring confidence, detecting fabricated content, deciding whether to re-execute, or generating improvement feedback. Activate on "validate output", "check quality", "confidence score", "hallucination check", "should we iterate", "improvement feedback". NOT for executing DAGs (use dag-runtime), planning DAGs (use dag-planner), or matching skills (use dag-skills-matcher).

smart-output

整合智能体输出结果为结构化最终输出，支持多种格式。适用于整合分析报告、生成结构化报告

Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", "chaos engineering", "bulkhead pattern", "retry with backoff", or "health checks". Also trigger when designing resilient microservices, planning zero-downtime deployments, or investigating cascading failure scenarios. Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.

Orchestrator for the eval-output skill suite — evaluate LLM and agent outputs for quality, accuracy, helpfulness, and safety using structured rubrics and LLM-as-judge techniques. Load when the user says "evaluate this output", "score this response", "run an eval", "LLM as judge", "evaluate agent output", "how good is this response", "rate this answer", "eval this", or provides an LLM output that should be assessed for quality. Single entry point for all output evaluation workflows.

Agent skill for release-swarm - invoke with $agent-release-swarm

Transforms raw content into polished, audience-appropriate deliverables by selecting formats, calibrating tone, and applying structure standards.

Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

Generate Minervini-style breakout trade plans from VCP screener output with risk calculation, portfolio heat management, and Alpaca-compatible order templates.

Runs an Opportunity Solution Tree workflow with a lightweight graph database and CLI, routing through outcome, opportunity, solution, and assumption phases.

Guarantee valid JSON, XML, or code structure during text generation using Pydantic models for type-safe outputs, supporting local models (Transformers, vLLM, llama.cpp) and maximizing inference speed with structured generation.

Create release plans with scope and deployment strategy. TRIGGERS - Use when user needs help with release-plan related tasks.

Generate an XLSX timesheet with logged hours, hourly rates, per-entry amount formulas, and totals for client billing or payroll.

Run STORM phase 2 — outline generation. This skill should be used when the user asks to "generate an outline for a storm article", "draft a wikipedia-style outline", or invokes /storm:outline. Produces a draft outline from parametric knowledge then refines it using the research information table.

Create release plans with scope and deployment strategy. TRIGGERS - Use when user needs help with release-plan related tasks.

Reporting pipelines for CSV/JSON/Markdown exports with timestamped outputs, summaries, and post-processing.

Generates detailed, technology-agnostic implementation blueprints by analyzing project architecture, technology stacks, and data flow patterns.

Train, evaluate, distill, quantize, export, and run inference for RT-DETR object detection models using NVIDIA TAO.

Starts a session by initializing a local database, selecting or creating a workspace and outcome, then routing to the relevant phase reference.

Outlines — structured generation with guaranteed JSON/regex output from local LLMs

Transform output-focused roadmaps into outcome-focused ones that communicate strategic intent, rewriting initiatives as outcome statements reflecting user and business impacts.

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

Synthesize market breadth, regime, and flow signals into a unified capital commitment recommendation with exposure ceiling, bias, and action guidance.

Batch Signal Isolation with Recipe-Driven Processing