MCPInstall

aws-observability

by aws OfficialDevOps & Cloud

Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/aws/agent-toolkit-for-aws --skill aws-observability
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads aws-observability automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·This skill is safe and provides a comprehensive set of tools for AWS observability using CloudWatch and CloudWatch Omni. It implements robust security practices, particularly concerning the handling of sensitive telemetry data during dynamic instrumentation and agent evaluation.
Socket Warn1 alert: gptAnomaly
Snyk WarnMEDIUM ·Risk: MEDIUM · 1 issue

SKILL.md

The instructions your agent reads when the skill is triggered.

AWS Observability

Overview

Domain expertise for AWS observability across metrics, logs, and traces, for two products that share the CloudWatch name but are separate services with separate control planes, data models, and APIs:

CloudWatchCloudWatch Omni
What it isLog groups, metric namespaces, alarms, Log Insights, X-Ray, Application SignalsApplication Observability / Agent Observability. A Space per account per Region is the access boundary over the account's CloudWatch Dataset (OpenTelemetry logs, traces, and metrics); the Dataset is a CloudWatch resource the Space reads, not something the Space contains
Control planeaws cloudwatch, aws logs, aws xray, aws application-signalsaws cloudwatchomni (endpoint prefix cloudwatch-omni, signing name cloudwatch)
QueryLog Insights query language; GetMetricDataSQL over logs.default / traces.default; PromQL over metrics; named views
NotifyAlarms (metric, composite, anomaly)Alerts (SQL/PromQL rule, contributors, OK/WARNING/CRITICAL/NODATA)
TopologyApplication Signals service mapContext graph (GetContextGraph)
AccessIAM onlyDomain → Space → access grants and access profiles (set up in setting-up-cloudwatch-observability)
Only hereDynamic Instrumentation, Synthetics canaries, CloudTrail auditing, EMFAgent-quality evaluation, views, context graph
First-time setupApplication Signals onboarding — ADOT auto-instrumentation, the amazon-cloudwatch-observability add-on, ServiceEvents, CI/CD metadataDomain → Space → grants → telemetry in → plain-ADOT instrumentation
Referencesreferences/cloudwatch/references/cloudwatch-omni/

This skill covers using both products, never setting either one up. Both first-time setup paths above live in setting-up-cloudwatch-observability (same two-folder split); route there rather than describing an onboarding procedure from memory.

Enabling Omni does not replace CloudWatch; log groups, metrics, and alarms keep working, and most customers use both.

Works best with the AWS MCP server — enables running CLI commands, querying CloudWatch, and validating configurations directly. All guidance also works with standard AWS CLI access.

Note: Reference files contain specific runtime versions, quota values, and feature matrices that may change. When precision matters (e.g. deploying to production, choosing a runtime, or checking a quota), confirm values against current AWS documentation rather than relying solely on the values in these files.

Scope guard — is this an observability request?

This skill owns the scope decision for every request routed to it, and this section is its sole home.

If a request is NOT about AWS observability with CloudWatch or CloudWatch Omni (weather, trivia, general chit-chat, non-observability coding), decline it in one sentence: state plainly that it is out of scope, never fabricate an answer, and never claim a false capability limitation (no "no internet access", no "no weather data") — the reason is simply that it is out of scope. Then redirect by naming what this skill does cover: querying CloudWatch and CloudWatch Omni logs, traces, and metrics, building dashboards, configuring alerts, investigating a service, or agent evaluation.

Do not attempt the off-topic task, and do not call a tool or run a query in pursuit of it. Keep it brief: no lecture, no long refusal.

Step 0 — CloudWatch or CloudWatch Omni?

Decide this before routing. The natural wording ("set up an alert for high latency", "build a dashboard", "query my logs") does not say which product the customer means.

  1. The customer names the product — "Omni", "Application Observability", "Agent Observability", a Space, Domain, Dataset, access grant, spaceId, cloudwatch-omni, Omni SQL, PromQL, views, context graph, evaluators, agent evaluation / scoring traces / online or continuous evaluation / gen_ai.evaluation, and OTel span vocabulary (traces.default, logs.default, spans, durationNano, status.code, resource attributes, service.name) → Omni. "Log Insights", "log group", "metric namespace", "CloudWatch alarm", "metric alarm", "composite alarm", "anomaly alarm", "X-Ray", "Application Signals", "canary", "CloudTrail", "Dynamic Instrumentation" → CloudWatch. A "log group" named inside an agent-evaluation request is the online-evaluation data source to verify, not a CloudWatch signal. A bare "alarm" (or "alert") with no other product signal is ambiguous — fall through to rule 3 and probe: a Space → Omni alert (alerts.md); no Space → CloudWatch alarm (cloudwatch/alarms.md). Exception: a "PromQL alarm" is a CloudWatch alarm on OTel metrics (cloudwatch/alarms.md) — "alarm" wins over "PromQL".

  2. Knowledge or how-to question ("what is an Omni alert", "does Omni have an API", "how do alerts differ from alarms") → answer from the reference files directly. Do not probe the account, and do not divert to the other product. Whether a capability exists is a fact about the product, not the account. concepts.md carries the full feature-equivalence matrix. 2a. Authoring / how-to alert request — "create / set up / write an Omni alert that fires when X", "how should I alert on Y" — with no Space or Region supplied and no go-ahead to actually create it, is a HOW-TO request. Deliver the authoring guidance (the alert row of "Must-state checklists" below, then alerts.md) FIRST, from the reference files. Do NOT stall on a Region/Space clarifying question and do NOT fall back to a CloudWatch alarm for a request that explicitly says "Omni alert". Probe the account only once the user supplies a Space/Region or asks you to create it. 2b. A telemetry object is already in the prompt — the user pastes, or the UI passes as context, a span, trace, log record, or query result and asks what it means, what errors it has, or how long it took. This is not a live-data request: do not probe the account, run a query, or ask the user to fetch it again. Read it in place per the "Reading a span or trace you already have" section of query/sql-logs-traces.md and state every item in its must-state list. 2c. A query request whose live result is empty or unreachable ("show me the slowest spans", "which traces failed") is still answered with the methodology — the exact query and the field rules that make it correct (see the must-state callouts in query/sql-logs-traces.md). Zero rows, a wrong-Region Space, or an unreachable endpoint is reported as a finding alongside the query, never as the whole answer.

  3. Request that must act on live data, and the wording is ambiguous (not a Step 0.5 content question, which is answered from the catalog) → probe the target Region first:

    aws cloudwatchomni list-domains
    aws cloudwatchomni list-spaces --region <target-region> --query "items[?region=='<target-region>']"  # account-global; filter to the Region
    
    • list-spaces is account-global (the --region flag only selects the endpoint), so filter its result to the target Region as shown rather than reading a non-empty list as proof; a Space is one per account per Region. See references/cloudwatch-omni/concepts.md for the full Region-probe rationale.
    • A Domain and a Space in that Region (a non-empty filtered list) → Omni.
    • No Space in that Region (an empty filtered list) → CloudWatch: alarms → cloudwatch/alarms.md, dashboards → cloudwatch/dashboards.md, queries → cloudwatch/log-insights.md, metrics → cloudwatch/metrics.md. If the customer explicitly asked for Omni and has no Space, that is a first-time setup — see step 4.
    • The probe itself errors ("not yet supported", unknown service, endpoint does not resolve) → the CLI/SDK model in use lacks cloudwatchomni. That is not evidence Omni is absent and must not be reported as "Omni is unavailable". The customer's installed AWS CLI/SDK most likely predates the service. If the request carried any Omni signal, give the customer the upgrade command to run (AWS CLI v2 reinstall or brew upgrade awscli; pip install -U boto3 botocore) and have them re-run aws cloudwatchomni list-domains — exact steps in programmatic-access.md. Never run a package-manager upgrade or installer on the host yourself (brew, pip install -U, .pkg/MSI); it mutates the customer's machine beyond the request and can break unrelated tooling — hand over the command and continue with the guidance. Never substitute a CloudWatch or X-Ray command for an Omni request. If the request carried no Omni signal, do not block on the upgrade. When you are already going back to the customer for missing inputs (for example an alert's threshold and period), ask which product they want in that same question: say the Space probe could not run on this CLI, describe both options, and build neither until they answer. When the request is fully specified or says not to ask, proceed on the CloudWatch path (the pre-Omni default) and mention the upgrade only in passing.
    • Still inconclusive → ask the customer.
  4. First-time setup, on EITHER product → STOP and route to the setting-up-cloudwatch-observability skill. This skill covers a service or Space that already reports and holds no onboarding procedure for either product, so there is nothing here to fall back on: not Omni setup (creating a Domain or Space, granting access, ingestion, forwarding, Slack, instrumenting an app or AI agent for a Space) and not CloudWatch setup (onboarding a service to Application Signals — ADOT auto-instrumentation, the amazon-cloudwatch-observability add-on, monitored service, ServiceEvents, CI/CD metadata, the per-platform enablement guides). Any instrumentation / ADOT / collector request is a setup request either way; the setup skill owns the product decision too, so hand the whole request over rather than probing list-spaces yourself. Application Signals once it is reporting — service map, alarms on its metrics, Dynamic Instrumentation debugging — belongs here.

Under-specified alert requests: When an alert or alarm request names what to watch (a symptom or a service) but not the inputs it needs — the threshold value and the evaluation period — ask for those rather than inventing them. Notifications are optional (per alerts.md), so ask for a notification destination only if the user wants to be notified. This holds on both paths (an Omni alert or a CloudWatch alarm).

Under-specified dashboard requests: When a dashboard request names what to show but not which metrics, panels, or layout, ground those against the data and confirm the panel set rather than inventing panels; a dashboard has no threshold, period, or notification. For ANY dashboard authoring/save request, also open dashboards.md and surface its "Facts you MUST surface when building or saving an Omni dashboard" checklist (see "Must-state checklists" below). Which signals or panels a named resource type needs is a Step 0.5 catalog question, not a dashboards-file question.

Step 0.5 — Service-health investigation (routing)

A large share of real questions are phrased as an operator symptom, not as a tool: "is my <service> throttled / slow / erroring / unhealthy," "which of my <service>s are <symptom>," "what's the health of my <service>," "what does <service> depend on and which is broken," "what signals / what should be on a dashboard or view for <service>." These are observability-data questions. Start from the telemetry, and answer with the methodology (the correct signals, aggregation, scoping, and caveats) even when you also pull live numbers and even when no matching resource exists in the account. Telemetry shows the symptom. The cause is often a configured value, so when the question is why something fails, also read the configuration of the resources involved, for example an API Gateway integration timeout, an SQS visibility timeout, or a Lambda timeout or event source mapping. A read-only or "logs only" role can usually still call these Get and Describe APIs. Make the call and report AccessDenied if it happens.

Route by the symptom, then open the reference and surface every applicable item in its "facts you MUST surface" checklist — the checklist is the output contract, and it lives in the reference file, not here:

  • A metric symptom about one AWS service (throttling, latency, error rate, restarts, saturation, "what signals should it get", which signals or panels a named resource type needs on a dashboard or view) → query/promql-metrics.md. Open its "Service-health question — facts you MUST surface" section and surface every applicable item. Dashboard or view wording does not send this to either dashboards file (neither carries the signal facts) nor to rule 3's probe — it is a content question.
  • "What does <service> depend on / what's broken downstream" / blast radius / who is affected / which direction do I walk the graph / what do CALLS, ACCESSES, RUNS_ON mean → context-graph.md. Open its "Dependency / blast-radius question — facts you MUST surface" section and surface every applicable item. A slowness or error symptom phrased in terms of the graph, dependencies, or edge types routes here, not to the metric bullet above.
  • Individual slow or failing spans / traces ("slowest spans for <service>", "which traces failed") are trace SQL, not a metric aggregate → query/sql-logs-traces.md. Open its "Span Duration" and "Finding failed spans" sections and state every item in their must-state callouts — a request about a service's latency or error rate (an aggregate signal) is the PromQL bullet above instead.

Must-state checklists — the output contract

Three Omni tasks carry a checklist the answer text must carry, not just the plan. Open the reference and surface every item relevant to the request; the reference holds the per-item detail and is the source of truth, so do not restate it here.

TaskOpenSection to surface
Authoring or advising on an Omni alertalerts.md"Facts you MUST surface when authoring an alert"
Scoring traces, choosing an evaluator, reading stored scores, online/continuous evaluation, evaluation datasetsagent-evaluation.mdevery "tell the user ALL of this" callout
Authoring, saving, reading back, or debugging an Omni dashboarddashboards.md"Facts you MUST surface when building or saving an Omni dashboard"

Routing — CloudWatch (references/cloudwatch/)

User needAction
Enabling/onboarding a service to Application Signals (auto-instrumentation, the amazon-cloudwatch-observability add-on, monitored service), propagating ServiceEvents git/deployment metadata through CI/CD, or the per-platform × per-language enablement stepsSTOP — this is first-time CloudWatch setup and no reference here covers it. Route to the setting-up-cloudwatch-observability skill
Writing Log Insights queries (pipe-delimited syntax: fields, filter, stats, sort, parse, display)Read log-insights.md. If StartQuery rejects the window as before the log group's creation time, read the same window with FilterLogEvents. See Known issues 11 there
Configuring alarms (metric, composite, anomaly)Read alarms.md. For an Omni alert, see the Omni table
Publishing custom metrics or using EMFRead metrics.md
X-Ray / ADOT tracing behaviour — X-Ray-SDK-vs-ADOT choice, trace and segment structure, annotations vs metadata, sampling rules, collector pipeline config, X-Ray→OTel migration trapsRead tracing.md. Onboarding an un-instrumented service is the setup skill's job (see the first row)
Building CloudWatch dashboards (widget mechanics; which signals a given AWS service needs is Step 0.5)Read dashboards.md
Debugging observability issuesRead troubleshooting.md — starts with the 5 most common fixes
Debugging canary failuresRead synthetics.md — see Common failures table
CloudTrail operational auditingRead cloudtrail.md
Setting up Lambda monitoring with CDKUse alarm-template.ts as a starting point
Creating synthetic canariesRead synthetics.md
Configuring ADOT collectorUse otel-config.yaml as a starting point
Debugging a running service with breakpoints/snapshots — Dynamic Instrumentation (modifies live services and captures live data)Read dynamic-instrumentation.md in full before acting. Confirm with the user before any create/delete, and narrate before significant actions: observation → hypothesis → proposed action → expected result. Source inspection alone identifies hypotheses, not confirmed root causes; keep suspected causes tentative until runtime evidence confirms them.

Routing — CloudWatch Omni (references/cloudwatch-omni/)

Rows that act on live Space data assume Step 0 found a Space. Knowledge questions are answered from the file directly.

User needAction
Concepts. What Omni is, what a Domain / Space / Dataset / grant / profile / view / alert / context graph is, whether a feature is Omni or CloudWatch, where setup startsRead concepts.md
Query logs or traces — SQL (SELECT … FROM logs.default / traces.default / default), field access, schema discovery, slowest / failed spans (durationNano, status.code), TABLESAMPLERead query/sql-logs-traces.md. For slowest or failed spans, state every item in its "Span Duration" / "Finding failed spans" must-state callouts, even when the live result is empty
A span, trace, or log record supplied in the prompt — "I have this span open, what errors are in it", a pasted telemetry objectRead the "Reading a span or trace you already have" section of query/sql-logs-traces.md. Answer from the object's own fields; do not probe, query, or ask the user to fetch it
Query metrics — PromQL, which metric answers which symptom per AWS service, why a metric is missing, gauge vs counterRead query/promql-metrics.md. Metrics are PromQL, never SQL
Views — create, manage, or query named reusable SQL (FROM view.<name>)Read query/views.md
Dashboards in Omni — compose, ground panel queries, author panels[], lay out the grid, the API save semantics (an unknown root- or panel-level key, a missing type/layout, or a bad variant is REJECTED at save with a 400 ValidationException; a bad enum VALUE, x+w>60, or an unknown key inside config saves 200 and fails or is ignored at render; validate before save), fix an empty or blank panel, the *OmniDashboard APIsRead dashboards.md
Alerts in Omni — any mention of an Omni alert, CreateAlert / GetAlert / ListAlerts / UpdateAlert / DeleteAlert, a profileId, an alert ARN, or how alerts differ from alarms; create, tune, tag, list, delete; notificationsRead alerts.md. The alert API is real and first-class — do NOT redirect to CloudWatch alarms. For CloudWatch alarms when Omni is not enabled, read cloudwatch/alarms.md
Context graph — why is service X slow or failing, what depends on it, upstream/downstream, which direction to walk, edge types CALLS / ACCESSES / RUNS_ON, blast radius, walking from an insight or anomaly to a root cause, GetContextGraphRead context-graph.md and state every applicable item in its "facts you MUST surface" section
Agent evaluation — score traces on demand, choose an evaluator, read back stored gen_ai.evaluation.* scores ("which evaluators are doing worst", "which online evaluators are unhealthy / underperforming"), build datasets from traces, set up online evaluation, author a custom evaluator, audit whether an agent's traces are flowingRead agent-evaluation.md and state every applicable item in its "tell the user ALL of this" callouts
Programmatic access — "is there an API or SDK for Omni", calling Omni from code, CI, IaC, or an AI coding agentRead programmatic-access.md. Omni has a real public SigV4 API; never answer that it has none, never substitute the CloudWatch or X-Ray CLI/SDK, and answer without probing for a Space
Who has access to a Space, granting or revoking access, access profiles, creating a Space or Domain, ingestion, forwarding, Slack, Azure, instrumenting an app or AI agent — and, on the CloudWatch side, onboarding a service to Application SignalsRoute to the setting-up-cloudwatch-observability skill. If it is not installed locally, load it with the AWS MCP retrieve_skill tool (skill_name: setting-up-cloudwatch-observability; pass file for a reference it cites)
Spans multiple areasRead the most specific reference first, then consult others as needed

Files

references/cloudwatch/

FileContent
alarms.mdMetric, composite, anomaly detection alarms — configuration, constraints, recommended defaults
log-insights.mdComplete query syntax, commands, functions, known issues, reusable query library
metrics.mdCustom metrics, EMF spec, metric filters, high-resolution, retention
tracing.mdX-Ray → ADOT migration, sampling rules, annotations vs metadata, collector config
dashboards.mdWidget types, cross-account/region, dynamic labels, sharing
troubleshooting.mdError → cause → fix for all observability services
cloudtrail.mdOperational auditing, event types, S3+Athena queries
synthetics.mdCanary runtime/blueprint constraints, VPC networking, common failures
dynamic-instrumentation.mdDynamic Instrumentation debugging loop — breakpoints/probes on live code, snapshot capture + correlation analysis, create/delete gating, snapshot PII handling. Runs via scripts/cloudwatch/di_instrumentation.py + scripts/cloudwatch/di_snapshots.py; details in dynamic-instrumentation/
alarm-template.tsBest-practice CDK Lambda monitoring (alarms + dashboard)
otel-config.yamlADOT collector config for X-Ray traces + CloudWatch EMF metrics

Not here, by design: Application Signals onboarding (the enablement procedure, the ServiceEvents CI/CD chain, the 16 per-platform guides) is first-time setup and lives in setting-up-cloudwatch-observability. Do not reconstruct it here from memory; route.

references/cloudwatch-omni/

FileContent
concepts.mdWhat Omni is and is not; glossary (Domain, Space, Dataset, grant, profile, view, alert, dashboard, context graph, evaluator); Omni-vs-CloudWatch feature-equivalence matrix; how to tell which product the customer means; the setup sequence and where it lives
context-graph.mdThe service/resource topology Omni builds from traces and metrics; GetContextGraph request/response and CLI; reading upstream vs downstream and blast radius; walking from an insight or anomaly hop-by-hop to a root cause, then pivoting to queries
programmatic-access.mdThe public SigV4 API (cloudwatch-omni endpoint prefix, cloudwatch signing name), how access grants authorize a programmatic caller, CLI/SDK access (and why an unsupported-service error is a client-version issue), CloudFormation/CDK, AI coding agents, and the wrong answers to avoid
query/sql-logs-traces.mdSQL over logs and traces — table addressing, required time range, system fields, field access and quoting, schema discovery, supported operations, functions, common patterns (including durationNano span duration), constraints, TABLESAMPLE
query/promql-metrics.mdMetrics in Omni are PromQL — what is queryable (OTLP, span RED, OTel-enriched vended metrics) and what is not, label conventions, __name__ matcher, rate() on counters, per-AWS-service metric catalog with derived formulas and dimension traps
query/views.mdNamed SQL views: CreateView / UpdateView / DeleteView / ListViews, FROM view.<name>, naming and definition rules, composition patterns
dashboards.mdOmni dashboards — composition recipes, grounding panel queries, the panels[] body and panel types, visualizations, the 60-column grid, the API save semantics (unknown root/panel keys are rejected 400; unknown keys inside config save 200 and are ignored at render; validate before save), troubleshooting empty/blank panels, the Create/Get/List/Update/DeleteOmniDashboard APIs, archetype templates
alerts.mdOmni alerts — alert vs alarm, evaluation (FIELD_VALUE / COUNT_OF_RESULTS, contributors), states and no-data treatment, notification rules, step-by-step create / update / delete / tag / fetch, and the alert APIs
agent-evaluation.mdAgent-quality evaluation on OTel traces — instrumentation health audit, evaluator selection, on-demand scoring, online evaluation, custom evaluators, datasets from traces, and reading back stored gen_ai.evaluation.* scores (retrieval plan + SQL mechanics). Uses scripts/cloudwatch-omni/evaluate_traces.py and scripts/cloudwatch-omni/capture_dataset_from_traces.py

FAQ

What does the aws-observability skill do?

Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging

How do I install aws-observability?

Run npx skills add https://github.com/aws/agent-toolkit-for-aws --skill aws-observability in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/aws-observability/ (personal) or .claude/skills/aws-observability/ (project).

Which AI agents can use aws-observability?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is aws-observability safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket flagged items to review; Snyk flagged items to review. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains aws-observability?

It is published by aws in aws/agent-toolkit-for-aws, and it is an official skill from the maker of the technology it covers. It has 10,042 recorded installs.

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microsoft-foundry

microsoft/azure-skills

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure

OfficialDevOps & Cloud579.1K installs

azure-diagnostics

microsoft/azure-skills

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

OfficialDevOps & Cloud569.8K installs

azure-prepare

microsoft/azure-skills

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

OfficialDevOps & Cloud569K installs

azure-ai

microsoft/azure-skills

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

OfficialDevOps & Cloud568.8K installs

azure-deploy

microsoft/azure-skills

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

OfficialDevOps & Cloud568.6K installs

azure-validate

microsoft/azure-skills

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

OfficialDevOps & Cloud568K installs