AI & ML

faberlens Bundle

Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.

v1truv1us-ai-eng-system Bundle

Build a local harness to drive, inspect, and profile an interactive CLI or TUI. Use for CLI UX checks, startup regressions, hangs, or prompt-flow verification.

v1truv1us-ai-eng-system Bundle

Transform a vague idea, request, or prompt into a concrete, actionable goal with clear success criteria, scope boundaries, and measurable outcomes. Use when the user has an intention but needs help defining what "done" looks like.

v1truv1us-ai-eng-system Bundle

Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Four LLM reviewers challenge changes from independent angles.

v1truv1us-ai-eng-system Bundle

Agent evaluation framework. Measure agent performance, identify weaknesses, and track improvement over time. Use when assessing agent quality, comparing approaches, or validating changes.

faberlens Bundle

Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).

faberlens Bundle

Connect Claude to Stripe APIs via Model Context Protocol. Use when managing customers, subscriptions, invoices, products, or searching Stripe documentation. Triggers: payment, billing, checkout, Stripe API, subscription management.

faberlens Bundle

Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawhub CLI.

peterbamuhigire Bundle

Use when coordinating AI-assisted planning, implementation, review, modernisation, documentation, human approval, CI evidence, or bounded multi-agent software work.

simhacker Bundle

YAML is sheet music. The LLM is the jazz musician. Comments are soul.

v1truv1us-ai-eng-system Bundle

Unified agent application scaffolding across 5 harnesses: Anthropic, Cursor, OpenAI, OpenCode, and Pi. Interactive project generator with live SDK docs, per-harness code patterns, and built-in verification. Use when someone says "create an agent app", "new SDK project", "build with [harness] SDK", "scaffold agent", or wants to verify an existing agent setup.

v1truv1us-ai-eng-system Bundle

Conductor/subagent routing for tasks across multiple harnesses. Assesses task complexity and intent, then dispatches to the appropriate subagent model via a harness-specific adapter. Supports Anthropic (Claude), Cursor, OpenCode, Codex (OpenAI), and Pi adapters. Use via /dynamic-task command or direct invocation from other skills.

v1truv1us-ai-eng-system Bundle

Stanford STORM multi-perspective research method. Runs four sequential phases (multi-perspective scan, contradiction map, synthesis, peer review) in one thread to produce a PhD-level briefing on any topic. Use for "storm research X", "multi-perspective research", "STORM method", or any topic where a single-prompt answer is too shallow.

v1truv1us-ai-eng-system Skill

Knowledge graph development for LLM applications. Graph storage selection, graph algorithms, extraction from documents/code/websites, entity extraction, Graph RAG, and visualization. Use when building knowledge graphs, graph databases, or LLM graph applications.

v1truv1us-ai-eng-system Bundle

Build Gemini-backed agent workflows and adapters. Use for Google Gemini API/ADK-style runners, Gemini CLI workflow parity, tool calling, structured outputs, or adding a Gemini variant beside Cursor/OpenCode/Claude runners.

v1truv1us-ai-eng-system Bundle

Convert vague requests into compact TCRO prompts with phase-specific constraints. Used by research, specify, plan, and work workflows.

faberlens Bundle

Query Burp Suite via MCP to extract security findings and proxy data.

faberlens Bundle

Use the ClawdHub CLI to search, install, update, and publish agent skills from clawdhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawdhub CLI.

faberlens Bundle

Query the DeepWiki MCP server for GitHub repository documentation, wiki structure, and AI-powered questions.

faberlens Bundle

Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.

peterbamuhigire Bundle

Use when auditing or improving this engineering engine or a product it produces. Coordinates evidence-backed baselines, small experiments, standardisation, and re-audits without replacing domain skills.

peterbamuhigire Bundle

Use when designing systems where multiple agents collaborate on one task — supervisor/worker, debate, plan-execute, peer handoff. Covers handoff message contracts, shared scratchpad, conflict resolution, deadlock detection, and the cost/SLA discipline that keeps multi-agent setups from spiralling.

peterbamuhigire Bundle

Use when measuring, evaluating, replaying, evidencing, or tracking success for AI agent tasks, steps, traces, and outcomes.

v1truv1us-ai-eng-system Skill

poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.

v1truv1us-ai-eng-system Bundle

Classify every skill in skills/ as user-invoked or model-invoked, ensure disable-model-invocation is set on user-invoked skills, and inject metadata.category on all. Run after adding or changing skills, or when token-cost/routing quality is being reviewed. Use for "sync skill taxonomy", "classify skills", "fix disable-model-invocation", or "skill token audit".

v1truv1us-ai-eng-system Bundle

Extract durable working preferences from recent Cursor chats and convert them into skills, rules, or workflow docs. Use when asked to learn preferences, mine feedback, personalize workflows, or generate team/person-specific agent guidance.

v1truv1us-ai-eng-system Bundle

Continuous iteration loop pattern for well-defined tasks with clear completion criteria. Use when getting tests to pass, implementing features with automatic verification, bug fixing with clear success conditions, or running automated development overnight. Provides prompt templates, safety guidelines, and integration patterns for ai-eng-system workflows.

faberlens Bundle

Wraps the Exa MCP server (mcp.exa.ai) for web search, deep research, and related tools.

peterbamuhigire Skill

Use when defining or enforcing which plan unlocks which AI model tier, generation quota, context limit, tool permission, tenant override, or upgrade behaviour.

peterbamuhigire Bundle

Use when significant implementation, architecture, API, database, routing, or planning changes require aligned project documentation and verified examples.

peterbamuhigire Bundle

Use when capturing kill-switch, red-team, and eval-drift drills as audit-ready compliance evidence — minimum-cadence enforcement, pass/fail recording, and cross-link to the incident drill skill. Turns drills from operational exercises into SOC 2 / ISO 27001 / HIPAA evidence rows with signed packs.

peterbamuhigire Bundle

Use when checking that every irreversible agent action has signed approval evidence linked to the action audit log, and producing an approval-gap register or audit evidence pack.

v1truv1us-ai-eng-system Bundle

Multi-axis code review with optional strict maintainability mode. Use before merging any change—human, agent, or automation output.

v1truv1us-ai-eng-system Bundle

Recursively initialize AGENTS.md in monorepo subdirectories with smart detection. Creates hierarchical agent context files with proper linking to root CLAUDE.md and parent AGENTS.md. Use for setting up multi-package projects, microservices, or any project with important subdirectories that need AI agent guidance.

v1truv1us-ai-eng-system Bundle

Run the full repository compatibility pass: scanner score, startup path, validation loop, and docs reliability.

v1truv1us-ai-eng-system Skill

Comprehensive prompt engineering for coding agents covering structured instruction design, few-shot prompting, chain-of-thought, decomposition, agent workflow patterns, and reliability techniques for multi-step pipelines.