Results for “agent-observability”

Installs and configures the Manifest observability plugin for AI agents, including API key setup, custom endpoint configuration, and troubleshooting.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Installs and configures the Manifest observability plugin for AI agents, including API key setup, endpoint configuration, and connection verification.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Instrument a shipped product's AI agents with tracing and observability so you can see what they did, why outputs happened, and what each run cost. Plain-language primer plus free-tier-first backend selection (Langfuse, Phoenix, LangSmith, Braintrust) and OpenTelemetry/OpenInference instrumentation. Load when the user asks to add observability, add tracing, instrument my agents, see what my agent is doing in production, set up Langfuse or Phoenix or LangSmith, debug why my agent gave a bad answer, or track LLM cost per request. Also fires when agent-system-architecture or setup-evaluation requires an observability plan for an agent-chain product. NOT for tracing the coding agent itself — that is run-trace. Precondition for runtime-learning-loop.

Sets up the Manifest observability plugin for AI agents, including installing the plugin, configuring the API key and endpoint, and verifying the gateway connection.

`analysis-agent`/`task-agent`/`review-agent`: primary-Skill-selected for logs, metrics, traces, alerts, SLI/SLO, or diagnostics; never task owner; skip without signal impact.

Sets up the Manifest observability plugin for agents, including installing the plugin, configuring an API key and optional custom endpoint, and verifying the gateway logs.

Fetches and analyzes LangSmith execution traces to debug LangChain and LangGraph agents, investigating errors, tool calls, and performance.

Install and configure the Manifest observability plugin for your agents. Use when setting up telemetry, configuring API keys, or troubleshooting the plugin.

Use this skill for performance, reliability, observability, SLO risk, production diagnostics. Trigger when the task involves agent profile work related to Performance SRE Agent, implementation, audits, debugging, strategy, or validation.

Watch, audit, and fix another agent's work by reconstructing the original request, inspecting evidence, and reporting gaps.

Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks, scanning for controls and generating a compliance report.

Agent skill for agent - invoke with $agent-agent

Agent validation v4.3.0 — Make agents act effectively by disabling harmful actions, lowering gates, and injecting cross-run learning

Use this when the system needs logging, metrics, tracing, alerting, or operator-visible runtime signals for APIs, workers, integrations, serverless functions, or local-to-production supportability.

Operate and extend barretlee/agent-pulse, the evidence-backed AI industry intelligence system: inspect source catalog and lifecycle, collect and normalize signals, bind evidence, cluster Events, evaluate system health, generate Scout hypotheses, export the privacy-safe public site, and verify release gates. Use when the user asks to run, configure, debug, extend, or explain Agent Pulse, its collectors, Control Room, narratives, Scout, or GitHub Pages output. Triggers on: agent-pulse, Agent Pulse, evidence-backed intelligence, source catalog, signal collection, Event clustering, source audit, Scout opportunity, public export, weekly brief, or AI industry intelligence pipeline.

Agent profile for inspect screenshots, viewports, layout overlaps, visual regressions, spacing, typography, and interaction states. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Skill for the Observability area of paddock. 105 symbols across 26 files.

Decision-theoretic framework for agents embedded within the environments they model and act upon

Agent skill for researcher - invoke with $agent-researcher

Compare coding agents head-to-head on reproducible tasks with pass rate, cost, time, and consistency metrics.

Install and configure the Manifest observability plugin for your agents. Use when setting up telemetry, configuring API keys, or troubleshooting the plugin.

Design reproducible evaluations for AI agents with representative task sets, explicit rubrics, appropriate graders, baselines, regression gates, and failure analysis. Use when defining agent quality, comparing prompts or models, validating a release, measuring tool-use reliability, investigating regressions, or deciding whether an agent is ready for production.

Observability and reliability engineer — SLOs, alerting, instrumentation, and incident response.

`task-agent`: use for repository methods, query behavior, record mapping, visibility, errors, or transaction participation; skip schema, migration, DTO, and domain-rule work.

`analysis-agent`/`task-agent`: use when actor journeys change entries, branches, interruption, recovery, authority, or side effects; skip route/state-only work.

`analysis-agent`/`task-agent`/`review-agent`: use when CI/CD checks, artifacts, deployment gates, IaC, or Helm behavior changes; skip when pipelines are unaffected.