165 skills · sorted by relevance
Add a model page to the SGLang Cookbook using shared templates. Organize verified launch settings and measured benchmarks, create configuration files and documentation, and update navigation, vendor cards, and page validation.
Turn user data and interviews into research-backed personas, or representative user profiles. The toolkit also supports mapping user journeys, planning usability tests, and combining research findings to guide and validate design decisions.
Refresh installed NanoClaw channel and agent provider code from its registry branches. Update all integrations or a selected subset, check a structured result report, and validate the updated installation with builds and tests.
Review database structures and relationships, identify design issues, and generate relationship diagrams. The skill recommends indexes, which help queries find data efficiently, and prepares migration steps with validation and rollback planning.
Prepare for FDA medical device quality audits through six evidence-focused questions. Review complaints, adverse event reports, process validation, manufacturing records, corrective actions, labeling, and inspection history, then organize readiness gaps and three next actions with owners.
Manage the AI models offered through OpenWork, including model additions, removals, aliases, and pricing discounts. Validate configuration consistency and trigger the GitHub workflow that refreshes models from models.dev, then report its merge or failure result.
Expose REST APIs as tools for AI agents through Google Cloud API Gateway using MCP, a protocol for connecting agents to tools. Covers OpenAPI migration, authentication, client connections, validation, and troubleshooting.
Create or update Claude skills that capture specialized knowledge and repeatable workflows. Guides the organization of instructions, scripts, references, and templates, then covers initialization, validation, and packaging into a distributable skill file.
Evaluate a driving agent on CARLA Leaderboard routes after checking the required setup. Select routes and repetitions, save driving scores and infractions, record runs, and resume interrupted evaluations from a saved checkpoint.
Verify whether a reported vulnerability is fixed in the current code without changing repository files. Trace the original attack path, examine possible bypasses and legitimate behavior, and return an evidence-based verdict for each supplied finding.
Run TypeScript checks that detect type errors without generating files. When shell execution fails because of environment problems or timeouts, switch to shell_agent to locate tools, address setup issues, and report the check results.
Diagnose slow loading, high memory use, and low frame rates in USD 3D scenes. Coordinate scene structure checks, validation, optimization, and before-and-after performance comparisons, then produce a report documenting findings and changes.
Verify whether a reported vulnerability is fixed in the current code without changing repository files. Trace the original attack path, examine possible bypasses and legitimate behavior, and return an evidence-based verdict for each supplied finding.
Compare two or more dotnet new templates using their installed options, features, and supported frameworks. Get a focused comparison table and a recommendation that explains which template best fits the project you want to build.
Move NuGet package versions from individual .NET projects into a shared management file. The skill audits version conflicts, preserves project conditions, validates builds before and after conversion, and produces comparison files and a migration report.
Guide npm package releases through dependency checks, version alignment, publishing procedures, and post-release smoke tests, which are basic installation and operation checks. It also documents fallback steps for failed automation and project-specific rules about who initiates releases.
Security considerations for Jackson JSON deserialization in Java applications. Covers timing of validation, raw input interception, and common deserialization attack patterns.
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Generate JSON Schema definitions for MCP tool input parameters. Creates well-documented, AI-consumable schemas with proper types, descriptions, and validation rules.
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Detect insecure JWT (JSON Web Token) implementations in a codebase using a two-phase approach: first map all JWT issuance and verification sites to understand the token lifecycle and signing configuration, then check each verification site for exploitable weaknesses such as algorithm confusion, missing signature verification, weak secrets, header injection, and missing claim validation. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/jwt-results.md. If no JWT usage is found in Phase 1, Phase 2 is skipped. Use when asked to find JWT, token forgery, or authentication bypass bugs.
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Retrieve machine-readable context with tanstack libraries, tanstack doc, tanstack search-docs, tanstack create --list-add-ons --json, and --addon-details for agent-safe discovery and preflight validation.
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Extract structured data matching a JSON schema from websites. Handles complex nested schemas, arrays, pagination, and validation. Always outputs via formatOutput.
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Workflow for publishing skills and agents to the dotnet-skills Claude Code marketplace. Covers adding new content, updating plugin.json, validation, and release tagging.
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MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
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Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key constraints, OCC retry patterns, ORM migration (Django/EF Core/Hibernate/Rails/SQLAlchemy), DDL operations, query plan explainability, system diagnostics via CloudWatch AAS, SQL compatibility validation, and bulk data loading. Load before answering DSQL limit or error-code questions; it has limits docs omit. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader, DSQL slow, DSQL performance, DSQL wait events, DSQL AAS.
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