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Bug discovery + structured fix (5-Whys) with regression test, driven by the `agf` CLI — zero MCP
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Basé sur la classification professionnelle SOC
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
| name | graph-bugs |
| description | Bug discovery + structured fix (5-Whys) with regression test, driven by the `agf` CLI — zero MCP |
| triggers | ["graph-bugs"] |
| version | 2.0.0 |
| author | auto-generated |
| date | "2026-06-16T00:00:00.000Z" |
| category | IMPLEMENT |
| phase | IMPLEMENT |
| tokens | ~594 |
| phases | ["IMPLEMENT"] |
Bug discovery + structured fix (5-Whys) with regression test. Drive via the agf CLI — zero MCP. Load context with agf context <id> before changing anything.
agf node add --type bug → agf start → [TDD: red repro → green fix] → agf done <id>
| Command | Does |
|---|---|
agf node add --type bug | register bug with repro AC |
agf start | pull bug + context + in_progress |
agf check <id> | validate fix (regression test green first) |
agf done <id> | finish + root-cause memory |
agf node add --type bug (repro AC: Given-When-Then)agf start (pull, context, in_progress)agf check <id> (DoD + TDD adherence)agf done <id> (DoD + root-cause memory + next)Phase: BUGFIX (IMPLEMENT)
Bug: #N registered and fixed
Reproduction: RED → GREEN
5-Whys: root cause identified
Regression: all tests pass
Status: fixed and documented
Loop link: delegate via
agf brief <id>→ fix →agf submit <id> --result <json>(validate→blast→DoD→done). Spiral:agf savings→agf learning→ next.
agf skill show graph-implementAGENTS.md and use apply_patch for manual edits.Economia de tokens. Os levers compartilhados por todas as skills —
--select,agf retrieve-command,agf exec chain, reuso antes de criação — vivem em_shared.md→ Token Economy. Fonte única: um parágrafo repetido em trinta arquivos é o trigésimo primeiro que envelhece sozinho.