Explorar skills

Runtime debugging and live project inspection via godot-mcp. Use when headless tools cannot diagnose the problem: code compiles but runtime behavior is wrong, tests pass but the game does not work as expected, or you need to inspect live state (node tree, console output, rendering). Escalation trigger: a task has failed 2+ times through the headless path (headless-build, gdunit-driver), or the iss

Asset collection + generation. Reads ASSETS.md MISSING entries (rows whose Tag matches the current tag), dispatches an analyst subagent for image inspection, generates AI images through the configured asset_image_model path, updates ASSETS.md status. ASSETS.md is cross-tag — every row carries a Tag column marking the introducing tag. Re-runnable any time during a tag. Explicit invocation only — us

Write and run E2E (end-to-end) game tests using the godot-e2e framework. Python controls a live Godot game over TCP — Locator-based semantic queries, expect() auto-retry assertions, and engine log capture make failures self-diagnosing. Use this skill whenever you need to: - Test actual gameplay: player movement, collisions, scoring, scene transitions - Verify UI interactions: button clicks, label

Visual quality assurance: analyze game screenshots for defects, compare against reference, check motion in frame sequences. Supports runtime-native inspection plus Gemini or OpenAI API-backed VQA.

Run gdUnit4 unit tests and parse results into structured output. Use this skill after writing or modifying code to verify correctness via unit tests, when diagnosing test failures, or when writing new test files. Triggers: "run tests", "test fails", "write a test", any gdUnit4/unit test mention. Supports both GDScript (.gd) and C# (.cs) test files.

Find keywords competitors rank for that the target property does not, and prioritize them by opportunity. Uses Ahrefs MCP for keyword and competitor data. Use this skill when planning content investment, identifying quick wins, building a content calendar against a competitor set, or scoping a market entry. Triggers on keyword gap, content gap, competitor keywords, opportunity keywords, what shoul

Pre-publish QA framework for content. Brief adherence, voice consistency, fact accuracy, structure and clarity, AI-content audit, SEO and AEO compliance, internal linking and schema validation, QA at scale via sampling, the QA workflow, and the discipline that distinguishes catch-problems QA from checkbox QA. Triggers on editorial QA, content review, pre-publish review, content audit, content QA p

Designing meeting schedulers and booking experiences that qualify leads, set up calls well, and convert at higher rates than a generic Calendly link. Availability logic, qualification gating, prep automation, follow-up sequencing. Honest about any-time-friction (no qualification, just a booking link), interrogation-gate (so much qualification it scares users off), and qualified-fast-path (just eno

How to design a content hub that earns topical authority. Pillar topic selection, cluster planning, internal linking architecture, URL structure, pillar and cluster page anatomy, topical authority signals for SEO and AEO/GEO, and the maintenance discipline that distinguishes intentional hubs from accidental orphans. Triggers on pillar content, content hub, topic cluster, topical authority, content

Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality,

Generate, evaluate, and narrow brand concepts during early ideation including positioning territories, naming candidates, mood directions, and narrative angles. Use this skill whenever the user is in the early phase of brand creation, exploring brand directions, brainstorming names, building moodboards, generating positioning options, or trying to choose between multiple brand directions. Triggers

Designing conversational flows for website chatbots and AI agents. Intent recognition architecture, branching logic, fallback handling, escalation to human, conversation analytics. Honest about scripted-bot (rigid trees, fail edge cases), hallucinating-bot (LLM without structure, makes things up), and structured-guided-conversation (LLM-powered with intent architecture and fallback discipline) pat