AI & ML

jacob-balslev Bundle

Use when deciding WHICH free or cheap agent model to route a piece of work to (e.g. MiniMax M3 Free, NVIDIA Nemotron, GLM, GPT-5 Nano, or another OpenCode Zen free-tier model), what each is good at, where its quality ceiling sits, and when to escalate the same work to a frontier model instead. Covers cost-routing: matching deterministic/mechanical/high-volume work to the cheapest model that clears its bar, and the hard rule that quality-creating and quality-judging work never goes to a free/cheap model. Do NOT use for choosing or operating the OpenCode runtime itself (use `opencode`), for authoring the agent loop (use `autonomous-loop-patterns`), or for GitHub Copilot premium-request budgeting (use `github-copilot`).

jacob-balslev Bundle

Use when designing or auditing deterministic health tooling for a skill library: schema/source validation, manifest/protocol parity, relation integrity, routing health, drift/export checks, supply-chain scanning, and eval-verdict evidence honesty. Covers checker ownership, the library-as-database model, release gates, and maintenance workflows after batch skill changes. Do NOT use for authoring one SKILL.md (use `skill-scaffold`), repo conformance audits (use `graph-audit`), generic lint rules (use `lint-overlay`), or reviewing checker code (use `code-review`).

jacob-balslev Bundle

Use when diagnosing organizational alignment with the McKinsey 7S framework: shared values, strategy, structure, systems, style, staff, and skills; how the seven elements reinforce or conflict; change-readiness gaps; and implementation risks. Covers internal organization effectiveness, operating-model alignment, transformation diagnostics, post-merger integration checks, and strategy-to-execution gap analysis. Do NOT use for external industry profit-pressure diagnosis (use porters-five-forces), activity-level value and cost mapping (use value-chain-analysis), durable resource advantage testing (use vrio), broad internal/external option generation (use swot-tows), or execution goal-setting alone (use okrs).

jacob-balslev Bundle

Use when reasoning about agent autonomy levels, designing auto-improve loops, evaluating AI-generated code quality, or measuring agent productivity in an LLM-assisted codebase. Covers Karpathy's three eras of software (1.0 explicit / 2.0 learned / 3.0 natural-language), the vibe-coding-vs-agentic-engineering distinction, the 0–5 autonomy slider with task-type recommendations, the one-asset / one-metric / one-time-box AutoResearch loop, Software 3.0 productivity metrics, and the documented quality regressions of ungated AI-generated code (the 'vibe hangover'). Do NOT use for choosing a specific autonomy-loop topology (use `agent-engineering`), for the per-prompt authoring discipline (use `prompt-craft`), or for reviewing the AI-generated code that comes out of a Software 3.0 workflow (use `code-review`).

jacob-balslev Bundle

This skill provides expertise in data and context compression: SaaS payload optimization (Zstd, Brotli, Gzip), database storage compression, and AI context window compression (Semantic Summarization, Token Pruning). Use when optimizing API latency, reducing storage costs, or managing long-running agent sessions near context limits. Do NOT use for image/video lossy compression (use product-photo) or file archiving.

jacob-balslev Bundle

Use when reasoning about how a system, user, or designer's internal model of behavior may diverge from reality — applies across UX, distributed systems, type systems, API design, and team collaboration. Covers the three-model frame (designer / system image / user), the two gulfs (execution and evaluation), analogy and metaphor as model-seeding, the five failure modes (transfer, overgeneralization, underspecification, drift, invariant blindness), the surface/operational/architectural/domain layering, and the discipline of validating a model against the system it claims to represent. Do NOT use for the visual representation of a model (use knowledge-modeling), for the formal-domain entities-attributes-relationships of conceptual modeling (use conceptual-modeling), for cognitive biases in decision-making (out of scope), or for empirically eliciting user models via research methods (use user-research).

jacob-balslev Bundle

Use when an agent is making too many tool calls, when context is filling from verbose tool outputs, when the same operation could be a script instead of N individual calls, or when designing a tool-use protocol for a new agent or harness. Covers the three costs of every call (token, latency, context pollution), the script-vs-call decision gate, tool-selection decision trees (file-search vs content-search vs targeted-read vs full-read), call batching and parallelization, redundancy avoidance, the poka-yoke principle, subagent delegation for context protection, and cost-benchmark heuristics by task type. Do NOT use for prompt wording (use `prompt-craft`), broader context stack design across the five layers (use `context-engineering`), runtime tool failures or production debugging (use `debugging`), or behaviour-preserving refactor mechanics (use `refactor`).

jacob-balslev Bundle

Use when designing, reviewing, or debugging an autonomous AI agent loop: repeated agent execution, completion signals, checkpoints, supervisor respawn, stall detection, safety caps, and human handoff rules. Covers the core loop patterns from simple bounded runs through sentinel-based continuation, checkpoint-resume, and external supervisor loops. Do NOT use for choosing a specific agent product command (use agent-engineering or the product's docs), writing ordinary task instructions (use prompt-craft), or optimizing individual tool calls (use tool-call-strategy).

jacob-balslev Bundle

Use when choosing semantically precise names for files/functions/variables/types/columns, resolving overloaded terms, reviewing error messages or UI copy for blame/register clarity, or adapting language for end-user/agent/developer/global-audience contexts. Covers morphology, compound-word order, abbreviation policy, verb-noun naming, polysemy qualification, audience register, blame-free error structure, and cross-cultural language awareness. Do NOT use for casing convention policy (use `naming-conventions`), call-site-wide renames (use `refactor`), docs/navigation structure (use `information-architecture`), specialized UI text pattern catalogs (use `microcopy`), or final prose humanization (use `writing-humanizer`).

jacob-balslev Bundle

Use when designing how a database keeps multiple copies of its data in agreement across nodes for availability, read scaling, and disaster recovery: the three foundational topologies (single-leader / primary-replica, multi-leader / multi-primary, leaderless / quorum), synchronous vs asynchronous replication and the replication-lag trade-off, log shipping vs statement replication vs trigger-based replication, the read-after-write consistency problem and its mitigations (sticky session, read-from-leader, monotonic reads), the failover model and split-brain risk, and the relationship to the CAP/PACELC choices the topology realizes. Do NOT use for horizontal partitioning across nodes (use sharding-strategy), the CAP theoretical frame itself (use cap-theorem-tradeoffs), single-node transactional guarantees (use transaction-isolation), or query tuning (use query-optimization).

jacob-balslev Bundle

Use when authoring any artifact that makes claims — skill content, documentation, audit findings, architecture proposals, code review comments, research summaries, or agent output. Covers the discipline of grounding every claim to a verifiable source, distinguishing verified-by-evidence from inferred-from-context, Chain-of-Verification-style claim checking, RFC 2119/RFC 8174 modality, Toulmin argument structure, citation faithfulness, native citation-tool limits, and honest handling of inference, absence, conflict, and currentness. Do NOT use for execution-level evidence protocols or output-completeness enforcement (use methodology), naming precision (use semantics), or grader/rubric design (use evaluation or eval-driven-development).

jacob-balslev Bundle

Use when auditing for recurring issues, clustering errors, detecting drift from conventions, or when an agent keeps fixing symptoms instead of root causes. Covers the Observe -> Cluster -> Name -> Codify -> Detect -> Prevent loop, grep-based audits, normalize-then-hash error clustering, board-health patterns, design-token and heading drift, domain-encoding patterns, eval-as-pattern-tests, 5 Whys, pattern lifecycle states, and drift traps. Do NOT use for one-off bug localization without recurrence, or for designing the classification system itself; this skill detects violations of conventions that already exist.

nahisaho Skill

MLOps モデル監視スキル。データドリフト検出 (Evidently/NannyML)・ モデル性能劣化検出・特徴量ドリフト・コンセプトドリフト・ A/B テスト統計・モデルレジストリ・再学習トリガー。

nahisaho Skill

モデル生物データベース統合スキル。FlyBase (ショウジョウバエ)、 WormBase (線虫)、ZFIN (ゼブラフィッシュ)、RGD (ラット)、 MGI (マウス) の REST API を統合した モデル生物遺伝子・表現型・疾患モデル横断検索パイプライン。 ToolUniverse 連携: impc, mpd。

codyswanngt Bundle

Answer a question from the LLM…

codyswanngt Bundle

Enable the Maestro CLI's…

codyswanngt Bundle

Best practices for designing…

eskcti Skill

Extrai o modelo de domínio implícito em código legado — Bounded Contexts, entidades, value objects, agregados, serviços de domínio e Linguagem Ubíqua. Usar antes de modelar DDD sobre um sistema existente.

yogsoth-ai Skill

Fauconnier-Turner 4-space model: Generic + Input1 + Input2 → Blended Space

bilal140202 Skill

Delegate analytical, sandboxed, or long-running work to the Google Antigravity (agy) CLI via a JSON-bridge wrapper. Use when you need a second opinion, sandboxed execution, or a detached long-running agent loop. Install location is .agents/skills/collaborating-with-antigravity/.

bilal140202 Skill

给 stdagent 新增一个 AI CLI 工具 target（transformer + 调研 + 测试 + 文档），逐步指引

bilal140202 Skill

Analyze the dispatch-log for per-feature spend, cache hit rate, and model routing, surfacing optimization opportunities. Use when costs look high, before a budget review, or when hunting for ways to cut LLM spend.

bilal140202 Skill

Roll up the yakos dispatch-log into a per-runtime / per-agent / per-day cost summary, optionally posting to a webhook. Use when reviewing spend, before a budget check, or when asked "what did this cost?".

bilal140202 Bundle

Automate any website with AI-powered browser automation. Use when the user needs to interact with a website like filling forms, extracting data, downloading files, logging in, or running multi-step workflows. Skyvern navigates sites it has never seen before using LLMs and computer vision. Integrates via Python SDK, TypeScript SDK, REST API, MCP server, or CLI.

bilal140202 Skill

Core Observal CLI operations: pull agents into your IDE, scan installed components, diagnose and patch IDE configs, authenticate, and manage CLI settings. Use when the user wants to install an agent, check their IDE setup, login, or configure the CLI.

bilal140202 Skill

Get your AI agent a real US/Canada phone number in one API call. Make voice calls, send and receive SMS, and hold actual conversations — all via API.

bilal140202 Skill

17 Claude Code skills for AI-context, testing, and MCP development. IANA-registered format (application/vnd.faf+yaml). Create .faf project DNA, score AI-readiness (0-100%), sync with CLAUDE.md, build MCP servers, generate test suites. 36,000+ downloads across npm, PyPI, crates.io.

bilal140202 Skill

Run an A/B test of the same task at multiple model tiers (Haiku, Sonnet, optionally Opus). Captures outputs, computes structural and semantic diffs, scores quality, writes a markdown comparison report. Use when the user wants to validate "is Haiku good enough for this task class?" or runs /tokenwise:ab "<task description>".

bilal140202 Skill

Adversarially review anything - a plan, design, code change, piece of writing, decision, argument, config, or idea - with the `agy` (Antigravity) CLI. A fast second opinion from an independent model that pokes holes in whatever you give it - questionable assumptions, flaws, risks, gaps, failure modes, and a SHIP/REVISE/RETHINK verdict. Use when you want to red-team / stress-test / sanity-check / critique something, "poke holes in this", "what am I missing", "what's wrong with this", "get a second opinion", "review this with agy", or harden it before committing. Pairs with brainstorming and writing-plans.

bilal140202 Skill

Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's repo.

bilal140202 Skill

Use when Unity UI needs layout-focused implementation or repair through `unity-mcp`: attached UI mockup, mockup screenshot, uploaded design image, dropped design image, reference image, wireframe, or UI 시안; analyze visual layers into a layer-to-Transform tree/레이어 트리 구조; map item-level UI rects; turn or convert into UGUI/UI Toolkit; create Unity UI prefabs/프리팹 생성; or fix drift, safe area, text overflow, structured exports, tokens, or shared prefab reuse.

bilal140202 Skill

Helium MCP — News, Markets & AI Intelligence

bilal140202 Skill

Security scanner for supply chain attacks, malicious dependencies, prompt injection, and suspicious code patterns. Use this skill whenever the user asks to audit a project, scan for malicious packages, check dependencies for threats, look for prompt injection, detect typosquatting, review supply chain security, or investigate suspicious code. Also trigger for: "check if this is safe", "scan my deps", "audit my project", "is there anything malicious", "security review", "check for backdoors", "supply chain attack", "dependency confusion", "malicious npm/pip/cargo package". Works with Python, Node.js, Go, Rust, Java/Maven/Gradle, and mixed projects. ALWAYS use this skill when security scanning of any kind is requested.

bilal140202 Skill

Deep codebase exploration using IDE bridge LSP tools. Maps architecture, traces call chains, discovers entry points, and builds a mental model of unfamiliar code. Use when onboarding to a new codebase or understanding a module.

bilal140202 Skill

Diagnose CCB runtime, mounted daemon graph, tmux namespace and panes, provider context, queue/inbox/trace, replies/artifacts, config drift, and storage boundaries. Use when the user asks what is broken, which agent is stuck, whether CCB is mounted, why a reply did not arrive, or what to check first.

bilal140202 Skill

Implements formal mathematical verification for Python AI agents. Use when generating agent code like PydanticAI or LangGraph, or when user asks to add TLA+ verification, make the agent safe, prevent hallucinations, or implement antigravity guardrails.