Generalized Cherny-style autonomous improvement loop. Reads a domain-scoped baseline.json + oracle script, runs the oracle, picks the worst-scoring item, proposes a fix, validates rollback safety, commits if metric improved AND roundtrip passes. Use for chatbot-qa, embeddings, voicing-analysis, or any other domain…
Backlog grooming. Reads BACKLOG.md (H2 epics → H3 sub-sections), recent open GitHub issues, state/quality/ trend snapshots, state/digests/latest.md, and stale docs/plans/, then proposes a ranked top-3 work items with rationale. Writes the same content to state/backlog-grooming/ .md so the proposal survives session…
L2 chatbot-development loop. Picks the next chatbot-shaped item from BACKLOG.md, runs feature → plan → work → review → PR while enforcing the Demerzel tribunal gate on any change touching GA.Business.ML/Agents, MCP tooling, DSL parser, or DI composition. Use when iterating on chatbot capability, not for general…
Per-commit roundtrip validator for the chatbot-qa /auto-optimize loop. Re-runs the prompt corpus after a proposed fix and rejects the commit if the metric regressed, the canonical-trace gate broke, or a protected path was modified. The Harness rollback equivalent for the chatbot domain per…
Self-improvement reflex. When the user corrects an approach ("no, don't do that", "we discussed this before", "stop X"), captures the lesson as a permanent project rule appended to CLAUDE.md so the pattern doesn't repeat in this or future sessions. Cherny called this "the most important loop" in his 2026 Sequoia talk.
Opt-in pre-merge gate that convenes a virtual council of specialist sub-agents for one-way-door PRs (schema changes, public APIs, OPTIC-K dim changes, pricing). Adopts the claude-codex-forge council pattern. Use sparingly — only for high-stakes decisions the team would lose sleep about reverting. Invoked as /council…
Use when building C# applications with .NET 8+, ASP.NET Core APIs, or Blazor web apps. Builds REST APIs using minimal or controller-based routing, configures database access with Entity Framework Core, implements async patterns and cancellation, structures applications with CQRS via MediatR, and scaffolds Blazor…
Capture meaningful session state (current cursor, in-flight work, live hypotheses, open questions, do-NOT-carry-forward) to state/digests/latest.md so the next session — including one after auto-compaction — can re-enter without re-discovering context cold. Distinct from /learnings (which captures surprises).
Use when building .NET 8 applications with minimal APIs, clean architecture, or cloud-native microservices. Invoke for Entity Framework Core, CQRS with MediatR, JWT authentication, AOT compilation.
Per-commit roundtrip validator for the embeddings /auto-optimize loop. Re-runs OPTIC-K leak-detection diagnostics after a proposed change to the encoder / embedding pipeline and rejects if the leak metric regressed, the snapshot schema broke, or a protected path was modified. Mirrors chatbot-qa-roundtrip-validate but…
End-to-end autonomous (AFK) harness that develops AND QAs the GA chatbot. Orchestrates the existing Level-3 /auto-optimize dev loop + the semantic /ga-chatbot-qa-panel judge workflow, instruments every step to a dashboard the human can watch, and enforces branch-only / never-merge safety. Use to run unattended…
Use when building game systems, implementing Unity/Unreal Engine features, or optimizing game performance. Invoke to implement ECS architecture, configure physics systems and colliders, set up multiplayer networking with lag compensation, optimize frame rates to 60+ FPS targets, develop shaders, or apply game design…
Post-merge intent-vs-delivery evaluator. Resolves the most recent squash-merged PR, captures its stated intent (title + Summary), diffs it against what actually landed, runs /octo:review for specialist commentary, scans Codex bot comments (P0/P1 degrade the grade), computes a high/medium/low alignment score, and…
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
End-of-session compound learning capture. Identifies up to 3 surprising/non-obvious things that came out of the session, writes each as a docs/solutions/ / - .md entry with the standard frontmatter so the next session can grep it.