Explorar skills

Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.

Measure first, optimize second. Data-driven performance improvements with before/after benchmarks and production validation.

Audits any domain's AI-readiness by using curl to directly probe robots.txt, llms.txt, and llms-full.txt, then scores each file against a structured checklist and delivers a formatted report with pass/warn/fail findings and actionable fixes. Use this skill whenever a user provides a domain or URL and wants to know if llms.txt or llms-full.txt is available, discoverable, or properly structured. Tri

Prevents overengineering by enforcing minimum viable code. No speculative features, no premature abstractions, no unnecessary complexity.

Patterns for Retrieval-Augmented Generation (RAG) and agent memory systems. Retrieves only relevant context, prevents context bloat, and maintains coherent state across sessions.

Validates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and fallback handling.

Automated quality gates from commit to production. Every merge to main is potentially shippable. No manual steps in the deployment path.

Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and response schema completeness. Produces a polished interactive HTML report with a summary scorecard, site-wide pattern analysis, ranked top issues, and per-endpoint findings with specific fix guidance. Trigge

Structured logging, distributed tracing, and alerting for AI systems and traditional services. You can't fix what you can't see.

Use when interacting with Jira issues - searching, creating, updating, moving, transitioning, commenting, logging work, downloading attachments, managing sprints, boards, issue links, web links, fields, or users. Auto-triggers on Jira URLs and issue keys (PROJ-123). Also use when MCP Atlassian tools fail or are unavailable for Jira Server/DC.

Transforms imperative instructions into declarative goals with verifiable success criteria. Enables autonomous looping until verified completion.

Test real system boundaries, not mocks of mocks. Integration tests verify that components work together, not that they work in isolation.