Drift-specific ADR workflow for signal, scoring, output, and architecture decisions. Use when creating, updating, or validating ADRs before implementation. Keywords: ADR, decision record, proposed, signal design, scoring change, architecture boundary, output format, Decision trailer.
Drift-specific workflow for creating, extending, and validating ground-truth fixtures for signal precision and recall. Use when adding TP/TN fixtures, confounders, boundary cases, or file_history_overrides in tests/fixtures/ground_truth.py. Keywords: ground truth, fixture, precision recall, TP, TN, confounder, boundary, file_history_overrides, ALL_FIXTURES.
End-to-end Drift workflow for adding or materially changing a signal. Use when designing a signal, implementing BaseSignal logic, adding weights, creating fixtures, updating audits, and validating precision/recall before commit. Keywords: signal development, BaseSignal, register_signal, incremental_scope, signal design, precision recall, mutation benchmark, audit_results, ADR.
Operationaler Workflow für den internen MCP-Server aus scripts/mcp_product_health_server.py. Immer verwenden, wenn Agenten Produktstatus, Release-Gates, Working-Tree-Gates oder Audit-Freshness direkt per MCP abrufen sollen statt manuelle Git-/Script-Aufrufe zu bauen. Keywords: drift_product_health, drift_release_readiness, drift_working_tree_context, drift_audit_freshness, mcp server, pre-push gates, blast report, audit freshness.
Log learnings, errors, and corrections to .learnings/ for continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects the agent, (3) A knowledge gap is identified, (4) A better approach is found. Captures corrections, insights, errors, and feature requests; promotes broadly applicable learnings to project memory files.
Post-completion self-review for coding agents that runs simplify, harden, and micro-documentation passes on non-trivial code changes. Use when: a coding task just completed, the diff touches executable source files with 10+ changed lines or high-impact logic (auth, validation, queries, file paths, network, concurrency). Feeds recurring findings into self-improving-agent via .learnings/LEARNINGS.md.
Erkennt wiederkehrende manuelle Entwicklungsprozesse im Workspace, priorisiert sie nach ROI und fuehrt sichere lokale Automationen automatisch aus. IMMER verwenden, wenn der User repetitive manuelle Schritte, Produktivitaetsverluste, wiederholte QA/Gate-Ablaufe oder den Wunsch nach weniger manuellem Agent-Anstossen beschreibt. Keywords: automate workspace, repetitive tasks, auto run, quality gates, drift workflow automation, productivity.
Drift-spezifischer Workflow zum Erstellen und Verbessern von Agent-Prompts unter .github/prompts/. Verwenden bei neuen .prompt.md-Dateien, bei der Schärfung von Evaluierungs-Prompts, bei der Trennung zwischen internem Prompt und Field-Test-Prompt sowie bei der Ausrichtung auf Drift-Policy und Shared Partials. Keywords: agent prompt, prompt authoring, .prompt.md, evaluation prompt, field-test prompt, work_artifacts, issue filing, bewertungs-taxonomie.