📦

typesafe-ai

Name: typesafe-ai
Author: typesafe-ai

Revisão do conteúdo r1 Seguro ⚙️ Comandos externos🌐 Acesso à rede

Build Typed AI Decisions with TypeSafe

Many application features need semantic judgments, but free-form model responses are difficult to combine reliably in code. TypeSafe helps developers design small typed judgments and compose them into routing, ranking, extraction, verification, and interactive workflows.

Suporta: Claude Codex Code(CC)

🥉 78 Bronze

Instalar com meu Agente

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Solicitação do agente

Review the Skillstore skill "typesafe-ai" from https://skillstore.io/skills/typesafe-ai-typesafe-ai.md and its manifest at https://skillstore.io/api/skills/typesafe-ai-typesafe-ai/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

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Recursos legíveis por agentes

Use estes links quando um agente de IA, crawler ou script precisar de contexto limpo em vez de ler a página completa.

Detalhe em Markdown GET /skills/typesafe-ai-typesafe-ai.md manifest assinado GET /api/skills/typesafe-ai-typesafe-ai/manifest lockfile assinado GET /api/skills/typesafe-ai-typesafe-ai/lockfile

Testar

Usando "typesafe-ai". A support application must route incoming messages to a known team and fill the team-specific fields.

Resultado esperado:

Use a routing judgment to select a team and a separate typed judgment for branch-specific arguments. Ask only the questions relevant to the selected branch, then let application code execute the handoff.

Usando "typesafe-ai". A search workflow has many retrieved candidates and needs reliable context for an answer.

Resultado esperado:

Retrieve candidates in code, judge relevance with comparable scores, select useful evidence, and send uncertain or failing cases to verification or human review.

Usando "typesafe-ai". A product team wants to replace a broad prompt that returns parsed text.

Resultado esperado:

Split the broad request into narrow judgments with explicit criteria, named state fields, typed outputs, a no-match result, and tests for representative cases.

Auditoria de segurança

Seguro

v1 • 17/09/2026 Abrir o relatório versionado

All 26 static findings are false positives. The flagged backticks are Markdown examples, the URLs are documentation links, and the fallback guidance does not perform system reconnaissance; no semantic security findings were identified.

Arquivos analisados

172

Linhas analisadas

Itens de revisão

Falsos positivos ignorados

Fatores de risco

⚙️ Comandos externos (3)

SKILL.md:34 SKILL.md:37 SKILL.md:110

🌐 Acesso à rede (22)

A auditoria estática e semântica concluída mais recente não detectou achados de segurança confirmados. Isso não comprova que a skill não tenha efeitos colaterais.

Auditado por: claude

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Citações acadêmicas (APA · BibTeX · CFF)

Citação APA

typesafe-ai. (2026). typesafe-ai security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/typesafe-ai-typesafe-ai/audits/1

Citação BibTeX

@techreport{typesafe-ai-typesafe-ai-typesafe-ai-2026,
  author = {typesafe-ai},
  title = {typesafe-ai security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/typesafe-ai-typesafe-ai/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "typesafe-ai security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "typesafe-ai"
date-released: "2026-09-17"
url: "https://skillstore.io/skills/typesafe-ai-typesafe-ai/audits/1"
identifiers:
  - type: other
    value: "skillstore:typesafe-ai-typesafe-ai:audit:1"
    description: "Skillstore immutable audit report identifier"

Pontuação do Skillstore

Por que esta pontuação Confiança das evidências: Médio

Arquitetura

Manutenibilidade

Conteúdo

Comunidade

Conformidade com a especificação

O que você pode criar

Plan semantic application features

Turn a product behavior into focused judgments, typed outputs, and bounded application actions.

Design evidence and review workflows

Combine retrieval, relevance judgments, confidence thresholds, verification, and human escalation.

Improve an existing model integration

Replace broad prompt-and-parse steps with reusable primitives, explicit state, and testable composition.

Teste estes prompts

Find the right judgment

I am building [feature]. It must [observable behavior]. Identify the smallest semantic judgment it needs, the relevant state, and a suitable TypeSafe primitive. Keep deterministic rules in code.

Choose a primitive

For this decision, compare Choice, Noul, and Score: [decision]. Define what each output means, when each primitive fits, and what no-match or uncertainty outcome the application needs.

Compose a workflow

Design a TypeSafe workflow for [goal]. Separate observed state, inferred state, policies, and execution. Identify independent questions that can run together, dependent follow-up steps, thresholds, and human escalation.

Audit a production design

Review this proposed semantic workflow: [design]. Check question scope, candidate coverage, state freshness, confidence interpretation, policy handling, latency and cost, failure categories, test cases, and the boundary between model judgments and application code.

Boas práticas

Start from the application behavior, then define the smallest judgment that supports it.
Keep rules, calculations, lookups, execution, and authorization in deterministic code.
Test judgments and resulting behavior with representative data, thresholds, and failure cases.

Evitar

Do not use a model judgment for exact rules, arithmetic, lookups, or permission enforcement.
Do not treat confidence as proof of correctness or reuse example thresholds without validation.
Do not send stale inferred state into actions without checking the current application state.

Perguntas frequentes

What is TypeSafe used for?

It helps developers add focused semantic judgments to software for routing, ranking, extraction, verification, and interactive decisions.

Which primitive should I choose?

Use Choice for one option, Noul for whether a condition holds, and Score for a degree along a defined dimension.

Does this skill write integration code?

It provides design guidance and points to API and SDK documentation. It does not implement or execute an integration.

How should I handle uncertainty?

Define thresholds using target data and consequences, include no-match outcomes, and escalate uncertain or failing cases when appropriate.

Can TypeSafe replace application logic?

No. Keep deterministic rules, calculations, lookups, execution, authorization, and workflow control in code.

What should I test?

Test representative inputs, state freshness, questions, candidates, outputs, composition, thresholds, service failures, and observed application behavior.