Compatibility alias for agent-principles. Use when an existing workflow, install surface, or exact-name request still references agent-development-principles; the substantive collaboration-principles work should route to agent-principles. Triggers on: legacy agent-development-principles, old install docs, exact-name…
Layered agent safety — prompt-injection defense, data exfiltration prevention, tool-misuse blocking via NeMo Guardrails + Lakera / LLM Guard / Llama Guard. Use before any agent reads untrusted input or executes tools with real-world side effects.
Simple, installation-agnostic AI agent lifecycle management using tmux + Python. Manage multiple AI agents without running a server, wiring HTTP APIs, or pulling in heavy dependencies.
Design tiered agent memory — core / recall / archival — with backend selection (mem0, Letta, Zep/Graphiti, LangMem) and temporal vs snapshot tradeoffs. Use when an agent needs persistent context across sessions, personalization, or temporal knowledge graphs.
Instrument LLM agents with traces, metrics, and replay. Use when an agent in production is silently failing, regressing, drifting, or burning tokens. Selects LangSmith / Langfuse / Phoenix, defines node-level spans, attaches evals to traces, and enables session replay.
Core principles for collaborative development with AI agents. Defines divide-and-conquer, context management, abstraction-level selection, automation philosophy, and verification/retrospectives. Apply optimal collaboration patterns when using any AI agent. Also the owner of the retired agent-development-principles…
Production agent SLA discipline — MAXLOOPS, MAXTOKENS, MAXCOST, MAXLATENCY, MAXTOOLCALLS, circuit breakers, sovereignty boundaries, degradation modes. Use before deploying any autonomous loop to production.
Tool registry, capability discovery, schema-first routing, router policies and fallbacks. Use when an agent has more than 15 tools, multiple MCP servers, or needs dynamic tool selection based on context.
Plan and improve day-to-day AI coding-agent workflow across Claude Code, Codex, Gemini CLI, and MCP-heavy repos: session startup, context recovery, fast repo loops, runtime verification, worktree use, and multi-agent handoffs. Use when the user wants a practical operating workflow, even if they ask in shorthand like…
Analyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk. Use when reviewing customer feature requests, triaging a backlog, or making prioritization decisions.
Generate an Ansoff Matrix analysis mapping growth strategies across market penetration, market development, product development, and diversification. Use when considering growth options, planning market expansion, or evaluating strategic growth paths.
Identify the first beachhead market segment for a product launch. Evaluates segments against burning pain, willingness to pay, winnable market share, and referral potential. Use when choosing a first market, targeting an initial customer segment, or planning market entry strategy.
Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.
Design lean startup experiments (pretotypes) for a new product. Creates XYZ hypotheses and suggests low-effort validation methods like landing pages, explainer videos, and pre-orders. Use when validating a new product idea, creating pretotypes, or testing market demand.
Brainstorm product ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints. Use when generating new feature ideas, brainstorming solutions for an identified opportunity, or ideating with a product trio.
Brainstorm feature ideas for a new product in initial discovery from PM, Designer, and Engineer perspectives. Use when starting product discovery for a new product, exploring features for a startup idea, or doing initial ideation.
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results. Use when setting quarterly OKRs, aligning team goals with company strategy, drafting objectives, or learning how to write effective OKRs.
Generate a Business Model Canvas with all 9 building blocks. Use when creating a business model, documenting how a business creates value, or analyzing an existing business model.
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
Create sales-ready competitive battlecards comparing your product against a specific competitor — positioning, feature comparison, objection handling, and win/loss patterns. Use when preparing sales teams, creating competitive materials, or responding to 'why not competitor X?'.
Analyze competitors with strengths, weaknesses, and differentiation opportunities. Identifies direct competitors and maps the competitive landscape. Use when doing competitive research, preparing a competitive brief, or finding differentiation opportunities.
Create a Product Requirements Document using a comprehensive 8-section template covering problem, objectives, segments, value propositions, solution, and release planning. Use when writing a PRD, documenting product requirements, preparing a feature spec, or reviewing an existing PRD.
Create an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities. Use when mapping the customer experience, identifying friction points, improving onboarding, or visualizing the user journey.
INVOKE THIS SKILL when building ANY Deep Agents application. Covers createdeepagent(), harness architecture, SKILL.md format, and configuration options.
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