ailang

Run ONE outer-loop iteration of a long-running mission (default: the V1 mission) — observe mission state, pick the top backlog item, route it through design-doc-creator → sprint-planner → sprint-executor → sprint-evaluator with the mission's model routing policy, record a log entry, and run the retro. Use when user says "run mission control", "mission iteration", "work the v1 backlog", or when fired nightly by the dev.ailang.mission-control launchd job.

Create AILANG design documents in the correct format and location. Use when user asks to create a design doc, plan a feature, or document a design. Handles both planned/ and implemented/ docs with proper structure.

Execute approved sprint plans with test-driven development, continuous linting, progress tracking, and pause points. Supports parallel milestone execution via Task sub-agents. Use when user says "execute sprint", "start sprint", or wants to implement an approved sprint plan.

Triage SonarCloud issues and hotspots via the SonarCloud Web API — check gate status, list open BLOCKER/CRITICAL bugs + vulns, group hotspots by rule, bulk-mark hotspots Safe per rule, transition issues to False Positive, and change the New Code period. Use whenever the user mentions SonarCloud, Sonar, quality gate red/failing, code smells to triage, marking hotspots safe, marking issues as false positive, setting new code period, or asks "why is the Sonar gate red" — even if they only reference a specific rule like go:S2245 without naming SonarCloud.

Run automated post-release workflow (eval baselines, dashboard, docs) for AILANG releases. Runs the tier-based benchmark suite (core+stretch+frontier by default) for standard + agent evals with validation and progress reporting. Use when user says "post-release tasks for vX.X.X" or "update dashboard". Fully autonomous with pre-flight checks.

Create and manage AILANG eval benchmarks. Use when user asks to create benchmarks, fix benchmark issues, debug failing benchmarks, or analyze benchmark results.

Create new AILANG releases with version bumps, changelog updates, git tags, and CI/CD verification. Use when user says "ready to release", "create release", mentions version numbers, or wants to publish a new version.

Evaluate sprint implementations against design docs and acceptance criteria. Runs after sprint-executor to assess quality with concrete scoring rubric (100 points, 70 to pass). Provides actionable feedback loop on failure. Use when user says "evaluate sprint", "review implementation", "assess sprint quality", or automatically via coordinator after sprint execution.

Test, validate, and add new AI models to the eval suite. Use when user asks to add new models, test model access, check pricing, or update models.yml.

Onboard a new on-device model to the Mac Studio eval rig end-to-end — hardware size/shape feasibility gate, OpenRouter quality pre-screen, ollama pull, opencode+pi cross-harness registration in models.yml, and continuous-rotation wiring. Use when the user wants to add/test/try a new local (Ollama) model on the rig, asks whether a model is the right size/shape for the hardware, or wants to evaluate a candidate before committing rig time.

Run AILANG agent-mode evaluations against local Ollama models on a dedicated Mac Studio rig. Use when user mentions "local ollama", "gemma4", "run eval locally", "smoke tier on the rig", "ollama benchmark", or wants to start/monitor a local-model eval rotation. Covers the M-EVAL-LOCAL-OLLAMA + M-EVAL-LOCAL-OBSERVABILITY workflow.

Robustly observe, audit, and respond to GitHub PRs we author (or have changes-requested on). Use when waiting on review feedback, when the user says "any new comments?", when reviewing CR/maintainer asks, or when replying to inline review threads. Codifies lessons from missing the `/pulls/N/reviews` endpoint and from `since=` cursor resets.

Diagnose AILANG WASM browser failures — frozen pages, silent loadModule hangs, type-checker stack overflows, missing effect handler bridges, version drift between wasm/ailang.wasm and the .ail source. Use when a browser demo using AILANG WASM behaves differently than the CLI, or when the page freezes without a console error.

Investigate why an `ailang publish` cascade didn't fire (or fired and silently failed) on multivac. Inspects gcloud logs across the registry validator, the Pub/Sub `ailang-cascade` topic, and the coordinator's task queue. Use when the user says "auto-cascade didn't work", "why didn't multivac pick this up", "check cloud logs for cascade", or "the dependents didn't get bumped".

Write and run AILANG code with correct syntax. Use when user asks to write AILANG programs, fix AILANG syntax errors, run AILANG code, or needs help with AILANG syntax. Includes version checking, syntax validation, and common patterns.

Find AILANG vs Python eval gaps and improve prompts/language. Use when user says 'find eval gaps', 'analyze benchmark failures', 'close Python-AILANG gap', or after running evals.

Check and process messages from autonomous AILANG agents. Use when starting a session, after agent handoffs, or when checking for completion notifications.

Identify AILANG language gaps from agent struggles, analyze eval baselines, and generate actionable insights. PRIMARY PURPOSE is finding what stdlib/prompt improvements would help agents succeed. Use when analyzing eval results, checking benchmarks, or investigating failures.

Guides development of AILANG builtin functions. Use when user wants to add a builtin function, register new builtins, or understand the builtin system. Reduces development time from 7.5h to 2.5h (-67%).

Maintain AILANG CLI help as single source of truth. Use when: adding new commands, adding environment variables, updating command behavior, auditing CLI documentation, ensuring help.go matches codebase implementation, improving CLI discoverability for AIs.

Set up Claude Code cloud/mobile environments for AILANG development. Use when starting a new cloud session, when tools are missing (Go, make, gh), or when user says "setup cloud", "setup environment", or mentions mobile Claude Code.

Monitor and refactor large files into smaller, AI-friendly modules. Use when user asks to check file sizes, split large files, or organize the codebase. Ensures tests pass before and after refactoring.

Manage coordinator daemon tasks, approve/reject work, monitor autonomous agents. Use when user asks to delegate tasks, check task status, review agent work, manage the coordinator, or use GitHub-driven approval workflow.

Verify code implementation aligns with design specifications. Use after implementing features, during code reviews, or when refactoring to ensure architectural compliance. Compares design docs with actual code.

Run Gemini CLI commands from Claude with correct Node version. Use when user asks to run Gemini CLI, test Gemini traces, or debug Gemini telemetry.

Monitor and triage GitHub issues against design docs and implementation status. Use when user asks to "check issues", "triage issues", "sync issues", "what issues are open", or wants to ensure issues are up-to-date with development progress.

Run Claude Code in headless/programmatic mode for automation, CI/CD, and agent workflows. Use when user asks about headless mode, programmatic execution, scripting Claude, or automating Claude workflows.

Guides AILANG parser development with conventions and patterns. Use when user wants to modify parser, understand parser architecture, or debug parser issues. Saves 30% of development time by preventing token position bugs.

Review code for performance issues and run benchmarks. Use when user asks to analyze performance, compare AILANG vs Python vs Go, run benchmarks, or review code for optimization opportunities.

Optimize and manage AILANG teaching prompts for maximum conciseness and accuracy. Use when user asks to create/update prompts, optimize prompt length, or verify prompt accuracy.

Analyze design docs, calculate velocity from recent work, and create realistic sprint plans with day-by-day breakdowns. Use when user asks to "plan sprint", "create sprint plan", or wants to estimate development timeline.

Analyze test coverage, identify gaps, detect dead code, and improve test quality. Use when user asks to check coverage, review tests, find untested code, or improve test robustness.

Debug performance issues and understand code flow using AILANG telemetry traces. Use when user asks to debug slow compilation, analyze benchmarks, find bottlenecks, investigate hangs, or understand system behavior.

Run ai-coding-lang-bench benchmark trials against AILANG, monitor active sessions, analyze results (cost/tokens/time/pass-rate), compare prompt strategies, and identify language gaps. Use when user says "run benchmark", "benchmark AILANG", "run trials", "analyze results", "find gaps", "monitor benchmark", or "compare prompt strategies".

Sync AILANG documentation website with codebase reality. Use after releases, when features are implemented, or when website accuracy is questioned. Checks design docs vs website, validates examples, updates feature status.

Develop and modify the AILANG Collaboration Hub UI. Use when user asks to add features to the monitoring dashboard, modify the approval queue, update the message center, or make changes to the React frontend.