structured-output
De la autor
Get parseable, trustworthy structured results out of a model — schema design, the enforcement mechanism the provider actually offers, validation at the boundary, bounded retry that feeds the error back, and recognising where a schema stops buying correctness. Use when a model's output feeds code rather than a human, when parsing keeps failing or fields come back plausible-but-wrong, or when designing an extraction, classification or grading step. Not for designing the tools an agent calls (tool-design), and not for free-form prose quality.
Instalare
npx skills add nahid-sparktales/agent-dispatcher --skill structured-output -a claude-code
Se instalează în .claude/skills/structured-output/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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De ce 82
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- structured-extractionericrisco/rsc-harnessUse when text must become a typed, schema-conformant object you can trust — pulling fields into a fixed JSON shape, extracting line items as typed records, classifying into enums, and building the Pydantic or Zod model plus the validate-and-retry loop. Covers extractors that throw parse errors, leak markdown fences, or fabricate a value where the field is absent instead of returning null. NOT getting the text out of a PDF, scan or DOCX first (that is `document-processing`), NOT general prompt craft untied to a schema (that is `prompt-engineering`).Documente★ 272
- create-structured-outputVapiAI/skillsDesign, create, inspect, update, attach, detach, preview, execute, and verify reusable Vapi Structured Outputs through public API or Server SDK workflows. Use for post-call extraction, typed call artifacts, AI-versus-regex extraction, JSON Schema design, backfilling existing calls, or retrieving structured results programmatically.Design★ 67
- system-designanthropics/knowledge-work-pluginsDesign systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.OficialDesign★ 32.8K
- schema-markupalirezarezvani/claude-skillsWhen the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,' 'schema.org,' 'JSON-LD,' 'rich results,' 'rich snippets,' 'schema markup,' 'FAQ schema,' 'Product schema,' 'HowTo schema,' or 'structured data errors in Search Console.' Also use when someone asks why their content isn't showing rich results or wants to improve AI search visibility. NOT for general SEO audits (use seo-audit) or technical SEO crawl issues (use site-architecture).Browser★ 28.7K
- tool-schema-designseb1n/awesome-ai-agent-skillsDesign and validate model-facing tool definitions with clear names, action-oriented descriptions, bounded JSON Schema parameters, explicit side effects, safe defaults, idempotency, errors, and realistic tests. Use when creating function-calling tools, MCP tools, agent actions, structured tool inputs, or when a model selects the wrong tool, invents arguments, or causes unsafe side effects.Design★ 229
- tool-designnahid-sparktales/agent-dispatcherDesign the tools a model calls — names, parameter shapes, what a result returns, and error text written as an instruction the model can act on. Use when adding or reshaping a tool or function an LLM invokes, when an agent keeps calling the wrong tool or passing malformed arguments, or when reviewing a tool surface someone else defined. Not for building the MCP server that hosts the tools (mcp-design), not for forcing a model's final answer into a schema (structured-output), and not for prompt wording outside the tool definition.Design★ 59
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