Claude Skills by sunholo-data

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

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

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%).

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.

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.

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.

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.

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.

Analyze evaluation baseline results, identify failure patterns, and generate actionable insights. Use after running eval baselines or when user asks to analyze eval results, check benchmarks, investigate failures, or understand what's failing.

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.

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.

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.

Run automated post-release workflow (eval baselines, dashboard, docs) for AILANG releases. Executes 46-benchmark suite (medium/hard/stretch) + full standard eval 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.

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.

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.

Execute approved sprint plans with test-driven development, continuous linting, progress tracking, and pause points. Use when user says "execute sprint", "start sprint", or wants to implement an approved sprint plan.

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.

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.

Bidirectional messaging between AILANG core and external projects.

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

Create, validate, and publish AILANG packages with correct conventions. Use when user asks to create a new package, fix package errors, add dependencies, publish to registry, or import packages. Also use when encountering IMP010, LDR001, MOD010, or export type errors during package development.

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

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".

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.

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".

Set up Codex 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 Codex.

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.

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.

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.

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. Also use when asked to run a design doc through quorum or review — `ailang design-quorum` (N off-Anthropic reviewers, optional step) and `ailang design-review` (single reviewer) are documented here.

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.

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.

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.

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.

Run Gemini CLI commands from Codex 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 Codex in headless/programmatic mode for automation, CI/CD, and agent workflows. Use when user asks about headless mode, programmatic execution, scripting Codex, or automating Codex workflows.

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.

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.

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.

Run ONE motoko-mission improvement cycle with deterministic diagnostic gates (observe → diff → cheap-confirm → build → validate). Use when working on the motoko mission, running improvement cycles, or when the mission diagnostic loop or its gates are mentioned.

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.

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.

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.

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.

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.