BuildOfficial

add-lens

Add Redis Iris Lens tracing to an existing AI agent through redis-iris, so every agent turn is one trace in the Lens UI with its LLM calls, tokens, tool calls, memory and document retrievals, and which of them entered the prompt. Detects how the agent runs (LangGraph or ADK attach, workflows.turn, another framework, or a plain loop), installs redis-iris[llm-tracing], calls lens.init(agent_id=...), opens one lens.turn() per turn where Iris does not open it already, and covers coexistence with an OpenTelemetry setup or LLM instrumentation the app already has. Use when the user asks to add Lens, tracing, observability, or per-turn traces to their agent, or asks why their Lens traces are missing.

v1.0.0New

#redis

Unsigned, install at your own risk

Unverified

This skill has no cryptographic signature attached. We can't verify the contents match what the publisher intended.

Install this skill

Run this command in your terminal. No account required — it auto-detects your AI tool and installs the skill file.

npx @skills-hub-ai/cli install redis-add-lens

Or download directly:

Browse all CLI commands →

Setup by platform

Claude Code

~/.claude/skills/<skill>/SKILL.md

Setup guide →

Install

One-click setup for your editor

Run in your project root

npx @skills-hub-ai/cli install redis-add-lens --target claude-code

Instructions

This skill doesn’t include stateful context yet, instructions only. Learn about stateful skills.

Security

Loading security scan...

Reviews (0)

View full changelog & diffs →

Browse all →

add-agent-playbooksAdd Redis Iris Agent Playbooks to an existing agent. Use when approved answers or repeatable procedures live in prompts, document retrieval, or a semantic response cache. Connect or provision a Playbook, publish FAQs and Skills, and verify the first application turn with optional review proposals.0 installs redis-connectionsRedis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.0 installs add-redis-irisAdd Redis Iris to an existing AI agent in any framework (LangGraph, LangChain, OpenAI Agents SDK, Google ADK, Pydantic AI, CrewAI, or a plain loop). Use when the user asks to add Iris, Redis Agent Memory, Agent Playbooks, Context Gateway, Intent Router, or Lens to their agent, or asks which Iris product their agent needs. Detects the framework and routes to the product skill.0 installs iris-developmentIris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.0 installs add-context-gatewayPut the MCP servers an existing agent uses behind one Redis Iris Context Gateway with redis-iris, so the agent connects to one MCP endpoint with one agent key instead of configuring each server and its secret. Asks whether the Gateway is in Redis Cloud or self-managed, then five questions (which MCP servers and secrets the agent has today, how many tools it sees, which read-only tools may be cached, which tools return large results, whether the framework speaks MCP itself). Self-managed, it provisions the Gateway and its Upstreams from the terminal with `iris context-gateway` and sets cache and compression policies. In Redis Cloud the developer creates them in the console. Then it points the agent at the Gateway in any framework and verifies it with `tools list` and `tools call`. Use when the agent configures several MCP servers one by one, carries one secret per server, loads too many tool schemas into the prompt, or the user asks for Context Gateway, one MCP endpoint, tool caching, o0 installs redis-query-engineRedis Query Engine (RQE) guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR), DIALECT 2 query syntax, efficient FT.SEARCH and FT.AGGREGATE queries, zero-downtime index updates via aliases, and the SKIPINITIALSCAN option. Use when defining a search index on Hash or JSON documents, picking between TEXT and TAG for filtering, writing FT.SEARCH queries with filters and SORTBY, managing or swapping indexes in production, or troubleshooting slow searches with FT.PROFILE.0 installs

More from Redis

View source →

redis-observabilityRedis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.2 installs redis-clusteringRedis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.2 installs redis-coreCore Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.2 installs redis-vector-searchRedis vector search guidance covering HNSW vs FLAT algorithm choice, vector index configuration (dims, distance metric, datatype), filtered hybrid search combining vector similarity with TAG or NUMERIC filters, and the RAG retrieval pattern with RedisVL. Use when defining a VECTOR field in FT.CREATE, integrating embeddings (OpenAI, Cohere, sentence-transformers), tuning HNSW parameters (M, EF_CONSTRUCTION, EF_RUNTIME), building a retrieval-augmented generation pipeline, or filtering vector results by attribute.2 installs add-intent-routerReplace an existing agent's hand-written routing (keyword if/else chains, regex, or an LLM call that only picks a route) with a Redis Iris Intent Router through redis-iris, so a message maps to a defined intent and its dispatch target by example phrasings and a score threshold. Asks five questions (what the routes are today, a few real phrasings per route, what each route dispatches to, what happens when nothing matches, which embedding model), writes the answers to intents.yaml, provisions the Router from the terminal with `iris intent-router service create`, loads the intents with `iris intent-router intents add`, then wires `router.match()` where the agent decides today. Use when the agent routes with keywords or an extra LLM call, or the user asks for intent detection, intent routing, or semantic routing.0 installs redis-docs-mcpWorking with the redis-docs MCP server (search / fetch / ask at redis.io/mcp) — how its index is shaped and how to read what it returns. Use when those tools are available and you are about to look something up in the Redis documentation, or when a result is confusing — fetch returned one short section instead of a page, several hits share one url, ids look like #sec:w1, metadata.version reads 1.0.0, a search came back empty, or ask was rate-limited or said the docs do not cover it. Also covers what redis.io does and does not index.0 installs

More Build skills

Browse category →

senior-frontendBuild and review React, Next.js, TypeScript or Tailwind frontends: components, scaffolding, performance and bundle size. Use whenever the user wants a new component or app, a page feels slow, the bundle is too big, or asks for a frontend code review.602 installs ui-design-systemUse when building a design system: tokens, component docs, responsive scales or developer handoff. Generates tokens with design_token_generator.py.514 installs frontend-designGuidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.318 installs senior-backendBuild and fix backend services: REST or GraphQL APIs, auth, microservices, PostgreSQL queries, migrations and load tests. Use whenever the user's API is slow or broken, needs login or auth added, a schema change, or a new endpoint or service scaffolded.233 installs self-improving-agentCurate what the agent has learned into durable project knowledge. Reviews Claude Code auto-memory (MEMORY.md and its topic files) for learnings worth keeping, promotes proven ones into CLAUDE.md or .claude/rules/, records a correction as a lesson that persists across sessions, prunes stale or duplicate entries, and turns a recurring fix into a reusable skill. Use whenever the user asks what you have learned or saved about the project, which memories should become permanent rules, to remember a lesson or stop repeating a mistake, or to clean up, audit or check memory health.164 installs using-superpowersUse when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions138 installs

Frequently asked questions about add-lens

What does the add-lens skill do?

How do I install the add-lens skill?

Run `npx @skills-hub-ai/cli install redis-add-lens` from your terminal. The CLI writes the SKILL.md to the correct location for your AI tool (e.g. ~/.claude/skills/redis-add-lens/ for Claude Code or ~/.cursor/skills/ for Cursor with --target cursor) and adds it to your project's .skills.json lockfile.

Which AI tools does add-lens work with?

add-lens runs in Claude Code. It follows the open Agent Skills standard (SKILL.md), so the same skill works in every supported tool without modification.

Is the add-lens skill free?

Yes. Every skill on skills-hub.ai is free and open-source. There are no premium tiers, paywalls, or usage limits. You only pay for whatever AI assistant you're already using.

How do I use add-lens after installing it?

In Claude Code, type `/redis-add-lens` (or whatever slash command the skill registers) and the AI follows the skill's instructions immediately. You can also reference it by name in natural language, your AI loads the skill into context when relevant.

Can I share the add-lens skill with my team?

Yes. Commit your project's .skills.json lockfile and teammates run `npx @skills-hub-ai/cli install` (no args) to install every skill at the exact version you pinned. Organization-scoped installs work via skills-hub.ai organizations.