DiegoNogueiraDev

Accessibility compliance audit using WCAG 2.2 AA standards, ARIA validation, screen reader testing, keyboard navigation, color contrast analysis, and i18n readiness

Execute the ANALYZE phase of the lifecycle via the `agf` CLI — PRD creation, requirements, Definition of Ready (7 checks), cross-project learning

API governance and design audit using OpenAPI/Swagger spec generation, REST maturity model, contract validation, and breaking change detection

Architecture governance using C4 Model, ADR lifecycle, Architecture Fitness Functions, layer boundary enforcement, and drift detection

Human-in-the-loop PLANNING skill — investigates the project (graph + git + harness/gaps) and runs the whole ANALYZE→DESIGN→PLAN chain in one faceted loop to produce a COMPLETE PRD injected as graph backlog (epics, tasks, testable AC) for a separate agent to implement. Applies the project's planning methodologies — Impact Mapping + OKR per epic, JTBD, MoSCoW, WSJF/Cost-of-Delay, User Story Mapping, Example Mapping (Rules/Examples → Given-When-Then AC), SPIDR splitting, INVEST, Definition of Ready, Risk Matrix; the full catalogue lives in the skill body. Stops for the human after each complete PRD and iterates the next cycle from the project's own findings (dogfood). Does NOT implement. Triggers — graph-backlog-generation, gerar backlog, criar PRD, planejar feature, detalhar épico, novo ciclo, "plan the next thing", "what should we build next".

Automated bug discovery through static analysis, LSP diagnostics, pattern detection, regression hotspot analysis, and error catalog mining

Bug discovery + structured fix (5-Whys) with regression test, driven by the `agf` CLI — zero MCP

Use when an unblocked task exists in the agf graph and you want it built end-to-end — autonomously and perpetually — pulling the next task (WIP=1), investigating, implementing with TDD, learning, and selecting the next until the backlog is exhausted. Use right after graph-backlog-generation injects a backlog, or to make agf dogfood its own backlog. NOT for planning or writing a PRD (that is graph-backlog-generation). Triggers — graph-builder-leafcutter, leafcutter, golden-wren, build loop, implement the backlog, dogfood loop, continuous improvement, self-heal loop, loop de implementação, esgotar backlog, melhoria contínua.

Human-in-the-loop PLANNING skill — investigates the project (graph + git + harness/gaps) and runs the whole ANALYZE→DESIGN→PLAN chain in one faceted loop to produce a COMPLETE PRD injected as graph backlog (epics, tasks, testable AC) for a separate agent to implement. Applies the project's planning methodologies — Impact Mapping + OKR per epic, JTBD, MoSCoW, WSJF/Cost-of-Delay, User Story Mapping, Example Mapping (Rules/Examples → Given-When-Then AC), SPIDR splitting, INVEST, Definition of Ready, Risk Matrix; the full catalogue lives in the skill body. Stops for the human after each complete PRD and iterates the next cycle from the project's own findings (dogfood). Does NOT implement. Triggers — graph-backlog-generation, gerar backlog, criar PRD, planejar feature, detalhar épico, novo ciclo, "plan the next thing", "what should we build next".

Use when an unblocked task exists in the agf graph and you want it built end-to-end — autonomously and perpetually — pulling the next task (WIP=1), investigating, implementing with TDD, learning, and selecting the next until the backlog is exhausted. Use right after graph-backlog-generation injects a backlog, or to make agf dogfood its own backlog. NOT for planning or writing a PRD (that is graph-backlog-generation). Triggers — graph-builder-leafcutter, leafcutter, golden-wren, build loop, implement the backlog, dogfood loop, continuous improvement, self-heal loop, loop de implementação, esgotar backlog, melhoria contínua.

Decide which output format (HTML, Markdown, JSON, SVG, hybrid) an agent should generate based on the task's intent, consumer, lifecycle, size, and content type. Use this skill whenever the user asks for a report, spec, code review, dashboard, summary, plan, doc, data extraction, or any deliverable where the format choice is implicit — even when they don't explicitly ask "what format should I use?". Apply this skill before generating any substantive artifact (>20 lines) to avoid defaulting to Markdown when HTML, JSON, or a hybrid would serve the consumer better.

Decide which output format (HTML, Markdown, JSON, SVG, hybrid) an agent should generate based on the task's intent, consumer, lifecycle, size, and content type. Use this skill whenever the user asks for a report, spec, code review, dashboard, summary, plan, doc, data extraction, or any deliverable where the format choice is implicit — even when they don't explicitly ask "what format should I use?". Apply this skill before generating any substantive artifact (>20 lines) to avoid defaulting to Markdown when HTML, JSON, or a hybrid would serve the consumer better.