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Found 102 Skills
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
Provides guidance on OpenTelemetry SDK setup, custom instrumentation, and sending data to Honeycomb. Trigger phrases: "instrument my app", "add tracing", "set up OpenTelemetry", "configure OTel", "add custom spans", "add attributes to spans", "send traces to Honeycomb", "set up OTLP", "configure sampling", "add span events", "add span links", "set up tracing for [any language]", "configure the OTel Collector", or any request about OpenTelemetry SDK setup, custom instrumentation, or sending data to Honeycomb.
OpenTelemetry in Python — SDK setup, declarative config, zero-code instrumentation (opentelemetry-instrument, opentelemetry-distro), contrib auto-instrumentation, manual API, performance tuning, breaking changes. Use when configuring or troubleshooting OpenTelemetry in a Python service. Triggers on "setup otel in python", "python telemetry", "python tracing", "opentelemetry-instrument", "opentelemetry-distro", "TracerProvider python", "MeterProvider python", "FastAPI/Flask/Django otel", "python logging bridge".
Evidence-driven investigation for network, streaming, and protocol-layer bugs. Use when debugging connection resets (ECONNRESET, HTTP/2 RST_STREAM, INTERNAL_ERROR), SSE or long-polling stalls, fixed-time connection drops, CDN/proxy/CGNAT idle timeouts, or any incident where symptoms do not match the obvious cause. Applies falsification-first methodology — layered isolation experiments to pin down the responsible network layer, env-gated runtime instrumentation for non-invasive observation, and counter-review agent teams to challenge single-cause assumptions. Strongly trigger on "socket closed unexpectedly", "stream interrupted", "ECONNRESET", "HTTP/2 INTERNAL_ERROR", "fails after N seconds", "works sometimes but not always", "upstream silent for X seconds", or any scenario where the investigator might jump to conclusions before evidence. Generalizes to any multi-layer system investigation where assumption-first thinking is the failure mode.
Hypothesis-driven debugging with ranked hypotheses, git bisect strategy, instrumentation planning, and minimal reproduction design. Triggers on: "debug this systematically", "root cause analysis", "bisect this bug", "rank hypotheses", "isolate this issue", "minimal reproduction". NOT for general reasoning.
OpenTelemetry in Go — SDK setup, API surface, breaking changes, contrib instrumentation libraries (otelhttp, otelgrpc, otelmongo), compile-time zero-code instrumentation (otelc), and performance tuning. Use when adding, reviewing, or configuring OpenTelemetry in a Go service. Triggers on "setup otel in go", "go telemetry", "go tracing", "otelconf go", "otelhttp", "otelgrpc", "TracerProvider go", "MeterProvider go", "otelc", "compile-time instrumentation go", "zero-code go instrumentation", "go build instrumentation", or any Go-related OTel question.
Datadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.
Expert evaluator for Prometheus label strategy. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, histogram bucket discipline, instrumentation hygiene, and source-side prevention via relabel_config / metric_relabel_configs. Use when the user asks to evaluate, audit, design, or improve Prometheus labels — or asks how to prevent high cardinality at the source. For post-ingest aggregation, see the adaptive-metrics skill. For "why is my Prometheus slow / expensive right now" triage, see prometheus-cardinality-troubleshooter.
Debugging and Root Cause Localization for AscendC Operator Precision Issues. Used when operator precision tests fail (such as allclose failure, result deviation, all-zero/NaN output, etc.). Process: Error Distribution Analysis → Code Error-Prone Point Review → Experimental Isolation → printf/DumpTensor Instrumentation → Fix Verification. Keywords: precision debugging, precision issue, result inconsistency, error localization, allclose failure, output deviation, NaN, all-zero, precision debug.
Instrument web applications to send telemetry data to Azure Application Insights for observability and monitoring. USE FOR: instrument app with app insights, add appinsights instrumentation, configure application insights, set up telemetry monitoring, enable app insights auto-instrumentation, add observability to azure web app, instrument webapp to send data to app insights, configure telemetry for app service. DO NOT USE FOR: non-Azure monitoring (use CloudWatch for AWS, Datadog for third-party), log analysis (use azure-kusto), cost monitoring (use azure-cost-optimization), security monitoring (use azure-security).
End-to-end analytics instrumentation workflow for a PR, branch, file, directory, or feature. Reads the code, discovers what events should be tracked, and produces a concrete instrumentation plan — all in one shot. Use this skill whenever a user wants to add analytics to a PR, asks "instrument this PR", "add tracking to this branch", "what analytics does this file need", "instrument the checkout flow", "run the full instrumentation workflow", or any request that implies going from code changes to a tracking plan. Also trigger when the user gives you a PR link, branch name, file path, or feature description and mentions analytics, events, or instrumentation. This is the main entry point for the analytics workflow — prefer it over calling the individual steps (diff-intake, discover-event-surfaces, instrument-events) separately.
Reads a PR or branch diff and produces a structured YAML change brief for downstream analytics instrumentation skills. Use this as the first step whenever a user shares a PR link, branch comparison, or raw diff and wants to understand what changed, what needs tracking, or how to instrument a feature. Trigger on phrases like "review this PR", "what changed in this branch", "help me instrument this diff", "check analytics coverage for this change", or any request to start the analytics review workflow.