develop-ai-functions-example
Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support, demonstrate features, or create test fixtures.
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Newest skills
3102 skills
AgentDB Memory Patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
fetch-vcpkg-ci-logs
Fetch vcpkg Azure DevOps metadata, failed-step logs, and selected artifacts. Use for acquiring CI evidence, not diagnosing or reporting regressions; use analyze-ci-failures for those tasks. Skip when supplied logs are sufficient.
k12-lesson-prep
Helps a teacher prepare to teach an existing K-12 lesson (math / ELA / science / social studies) — a prep partner that thinks through the lesson's key student task with the teacher and leaves a short teacher-only prep note. Triggers on asks to internalize, prepare for, get ready to teach, or understand a lesson, including implicit ones ("help me get ready for tomorrow's lesson"), and right after another skill built a lesson, which it can follow. Not for building or adapting a lesson, grading, rubrics, assessment feedback, or generating quizzes or student-facing material, and not for single-fac
AgentDB Learning Plugins
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
evaluate-new-port
Audit a vcpkg port locally. Reads the port metadata and build recipe, installs the port, inspects extracted sources and installed files, and produces a report covering license risks, vendored code, optional dependencies, and other port review suggestions.
k12-lesson-plan-creation
Creates a lesson plan, student-facing materials, and observation template. Load this skill BEFORE asking the teacher any clarifying question about grade, subject, topic, standard, or timing. Use when a K-12 teacher needs a math, ELA, science, or social studies lesson built from scratch — even if grade, subject, or topic isn't yet stated. Do NOT load for grading, a rubric, assessment feedback, a quiz, or a standards lookup — answer those directly. Triggers on explicit requests (lesson plan, mini-lesson, unit plan, daily plan) and implicit teacher intent: "I'm teaching long division to 5th grade
adr-skill
Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.
AgentDB Advanced Features
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
analyze-ci-failures
Analyze collected vcpkg CI failure evidence, classify regressions and known failures, identify root causes, recommend actions, and generate a report by package and triplet. USE FOR: explicit requests for CI regression triage, a failure inventory, baseline classification, action recommendations, or a formal CI failure report. DO NOT USE FOR: fetching logs as the final output, targeted debugging of one failure, answering a one-off question about logs the user pasted or pointed at, general coding, creating ports, or modifying portfiles. When requested analysis lacks local evidence, run fetch-vcpk
k12-lesson-differentiation
Adapts an existing K-12 lesson (math, ELA, science, or social studies) for students at different proficiency levels (below / at / above grade level). Load this skill BEFORE asking the teacher any clarifying question about the lesson, tiers, or student levels. Triggers on explicit asks to differentiate, tier, or scaffold a lesson, and on implicit signals like "my students are at different levels". Produces 1 teacher-facing differentiation plan + 3 student-ready tier documents as editable Word documents in a single output turn, rendered from one material-source JSON via bundled scripts (shared c
add-provider-package
Guide for adding first-party AI provider packages to the AI SDK. Use when creating a provider package under packages/ to integrate an external AI service.
agent-coordination
Agent spawning, lifecycle management, and coordination patterns. Manages 60+ agent types with specialized capabilities. Use when: spawning agents, coordinating multi-agent tasks, managing agent pools. Skip when: single-agent work, no coordination needed.
test-unbranded-emitter
Build and test the @typespec/http-client-python emitter. Use this skill whenever the user wants to test their local changes to the emitter, run the generator test suite, check if their http-client-python changes are passing, or validate a fix. Triggers on phrases like "test the emitter", "run tests", "check if my changes pass", "run test:generator", "run CI", or any mention of testing/validating changes in the emitter package.
k12-check-for-understanding
Creates a Check for Understanding (CFU) for a math topic or standard: 1–3 targeted formative items whose distractors come from documented student misconceptions, plus a teacher guide routing each likely response to a specific next instructional step. Load BEFORE asking any clarifying question about grade, standard, or topic. This skill is for math; for other subjects, help as you normally would and don't mention the skill to the user. Triggers on asks to create, write, generate, or design a check for understanding, formative check, quick check, or exit ticket for a math concept or standard, an
add-harness-package
Guide for adding new AI SDK harness packages. Use when creating a new @ai-sdk/harness-<name> package that adapts a coding-agent runtime to HarnessV1.
generate-from-typespec
Generate Python SDK code from a TypeSpec specification using the local emitter. Use this skill when the user wants to generate/regenerate a Python client from a TypeSpec spec, provides a GitHub URL or local path to a TypeSpec project, or says things like "generate from this spec", "emit Python from this tsp", "regenerate the SDK", or "compile this TypeSpec for Python".
value-creation-plan
Structure post-acquisition value creation plans with revenue, cost, and operational levers mapped to an EBITDA bridge. Includes 100-day priorities, KPI targets, and accountability frameworks. Use when planning post-close execution, preparing operating partner materials, or building a board-ready value creation roadmap. Triggers on "value creation plan", "100-day plan", "post-close plan", "EBITDA bridge", "operating plan", or "value creation levers".
add-function-examples
Guide for adding new AI function examples, for testing specific features against the actual provider APIs.
diff-upstream
Regenerate the local emitter and diff the generated code against the upstream baseline checked into autorest.python. Use this skill when the user wants to see how their emitter changes affect generated code compared to what's currently in production, says things like "diff upstream", "compare to baseline", "what changed vs production", "show me the diff", "how does this affect generated code", or wants to validate their changes produce the expected output differences.
unit-economics
Analyze unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".
ai-elements
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
writing-python-sdk-spector-mock-api-tests
Writes TypeSpec http-client-python generator mock API tests (azure/unbranded/shared) from a Spector case. Use when given a Spector case link or a PR link that modifies Spector cases under http-specs/azure-http-specs.