observability-dotnet
Skill4 starsChanged 52 days agoMITView on GitHub
Use when designing or reviewing .NET metrics, distributed traces, OpenTelemetry propagation, sampling, redaction, or operational alerts.
In this repository37 other files it gives its agents.
- global-instructions/AGENTS.mdAGENTS.md
- api-contract-safetySkill
- api-endpoint-deprecationSkill
- aspnet-core-api-developmentSkill
- background-services-dotnetSkill
- bug-investigationSkill
- code-qualitySkill
- code-reviewSkill
- context-resetSkill
- dependency-managementSkill
- deployment-readiness-dotnetSkill
- diff-reviewSkill
- distributed-workflowsSkill
- dotnet-architectureSkill
- dotnet-implementationSkill
- dotnet-securitySkill
- ef-core-safetySkill
- exception-handlingSkill
- git-workflowSkill
- google-bigquery-dotnetSkill
- google-cloud-pubsub-dotnetSkill
- google-firestore-dotnetSkill
- http-client-integrationsSkill
- integration-testing-dotnetSkill
- performance-diagnostics-dotnetSkill
- poc-developmentSkill
- production-debuggingSkill
- production-hotfixSkill
- production-loggingSkill
- redis-dotnetSkill
- relational-database-dotnetSkill
- retry-resilienceSkill
- safe-terminalSkill
- shared-code-impactSkill
- targeted-validationSkill
- task-routerSkill
- unit-testingSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Never record secrets or raw sensitive payloads in logs, traces, metrics, baggage or exception attributes.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Observability Dotnet
Inspect existing telemetry instrumentation, exporter configuration, service naming, sampling and retention conventions first. Identify the operational question and who will act on the signal.
- Propagate trace context across HTTP and messaging boundaries using established instrumentation. Use bounded, meaningful spans and avoid duplicating framework instrumentation.
- Define metrics for actionable throughput, failure, latency and saturation; avoid customer IDs, request IDs, URLs with unbounded values, and other high-cardinality metric labels.
- Never record secrets or raw sensitive payloads in logs, traces, metrics, baggage or exception attributes. Follow approved redaction and retention policies.
- Select sampling and alerts based on volume, severity and cost; ensure critical failure signals remain observable. Test propagation and sensitive-data exclusion where changed.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

