Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/xyruscode/ai-sync/aws-observabilitynpx skills add XyrusCode/ai-sync --skill aws-observabilitygit clone --depth 1 https://github.com/XyrusCode/ai-syncWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00223 | $0.01468 |
| Opus 5 | $0.00112 | $0.00734 |
| Sonnet 5 | $0.00045 | $0.00294 |
| Haiku 4.5 | $0.00022 | $0.00147 |
Grade A, and why
aws-observability scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to aws-observability — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AWS Observability
Overview
Domain expertise for AWS observability across metrics, logs, and traces, covering the full lifecycle: enabling/onboarding a service to Application Signals using ADOT (AWS Distro for OpenTelemetry) auto-instrumentation SDKs and ServiceEvents — making the service show up in Application Signals — on EC2, ECS, EKS, and Lambda in Python, Node.js, Java, and .NET.
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.
Routing
| User need | Action |
|---|---|
| Enabling/onboarding a service to Application Signals (auto-instrumentation) | Read application-signals-onboarding.md |
| Propagating ServiceEvents git/deployment metadata through CI/CD | Read application-signals-cicd-metadata.md |
| Per-platform/per-language enablement steps | Read the matching references/appsignals-guides/<platform>-<language>.md (e.g. eks-python.md) |
| Writing Log Insights queries | Read log-insights.md |
| Configuring alarms (metric, composite, anomaly) | Read alarms.md |
| Publishing custom metrics or using EMF | Read metrics.md |
| Setting up X-Ray tracing or ADOT | Read tracing.md |
| Building dashboards | Read dashboards.md |
| Debugging observability issues | Read troubleshooting.md — starts with the 5 most common fixes |
| Debugging canary failures | Read synthetics.md — see Common failures table |
| CloudTrail operational auditing | Read cloudtrail.md |
| Setting up Lambda monitoring with CDK | Use alarm-template.ts as a starting point |
| Creating synthetic canaries | Read synthetics.md |
| Configuring ADOT collector | Use otel-config.yaml as a starting point |
| Debugging a running service with breakpoints/snapshots — Dynamic Instrumentation (modifies live services and capture 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. Diagnosing running-service root cause from source/code inspection. Source inspection alone identifies hypotheses, not confirmed root causes. Keep suspected causes tentative until runtime evidence confirms them. |
| Spans multiple areas | Read the most specific reference first, then consult others as needed |
What ships with it
56 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .aws-skill-metadata 18 B
- assets/alarm-template.ts 3.9 KB runs code
- assets/otel-config.yaml 1.4 KB
- references/alarms.md 11 KB
- references/application-signals-cicd-metadata.md 6.5 KB
- references/application-signals-onboarding.md 20 KB
- references/appsignals-guides/ec2-dotnet.md 16 KB
- references/appsignals-guides/ec2-java.md 10 KB
- references/appsignals-guides/ec2-nodejs.md 19 KB
- references/appsignals-guides/ec2-python.md 24 KB
- references/appsignals-guides/ecs-dotnet.md 8.3 KB
- references/appsignals-guides/ecs-java.md 5.6 KB
- references/appsignals-guides/ecs-nodejs.md 6.5 KB
- references/appsignals-guides/ecs-python.md 7.9 KB
- references/appsignals-guides/eks-dotnet.md 3.9 KB
- references/appsignals-guides/eks-java.md 3.9 KB
- references/appsignals-guides/eks-nodejs.md 4.1 KB
- references/appsignals-guides/eks-python.md 5.2 KB
- references/appsignals-guides/lambda-dotnet.md 3.9 KB
- references/appsignals-guides/lambda-java.md 4.4 KB
- references/appsignals-guides/lambda-nodejs.md 5.2 KB
- references/appsignals-guides/lambda-python.md 5.7 KB
- references/cloudtrail.md 3.9 KB
- references/dashboards.md 5.8 KB
- references/dynamic-instrumentation.md 38 KB
- references/dynamic-instrumentation/breakpoint-creation.md 16 KB
- references/dynamic-instrumentation/call-tree-and-directions.md 5.7 KB
- references/dynamic-instrumentation/snapshot-parsing.md 4.2 KB
- references/log-insights.md 7.0 KB
- references/metrics.md 7.4 KB
- references/synthetics.md 6.5 KB
- references/tracing.md 9.0 KB
- references/troubleshooting.md 6.8 KB
- scripts/di_app_signals_client.py 3.3 KB runs code
- scripts/di_capture.py 8.5 KB runs code
- scripts/di_constants.py 560 B runs code
- scripts/di_crud_rendering.py 13 KB runs code
- scripts/di_crud_tools.py 29 KB runs code
- scripts/di_error_translation.py 5.6 KB runs code
- scripts/di_formatting.py 992 B runs code
- scripts/di_gateway.py 7.0 KB runs code
- scripts/di_instrumentation.py 13 KB runs code
- scripts/di_location.py 15 KB runs code
- scripts/di_logs_client.py 4.2 KB runs code
- scripts/di_region.py 2.0 KB runs code
- scripts/di_result.py 2.0 KB runs code
- scripts/di_session.py 2.0 KB runs code
- scripts/di_snapshot_parsing.py 11 KB runs code
- scripts/di_snapshot_queries.py 2.4 KB runs code
- scripts/di_snapshot_rendering.py 12 KB runs code
- scripts/di_snapshot_tools.py 12 KB runs code
- scripts/di_snapshots.py 13 KB runs code
- scripts/di_status_assessment.py 4.7 KB runs code
- scripts/di_status_rendering.py 12 KB runs code
- scripts/di_status_tools.py 13 KB runs code
- scripts/di_validation.py 11 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 68 lines · 223 tokens per session scan A 99b4abac4a39
aws-observability is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed 2d ago), licensed MIT. It adds 223 tokens to every session and 1,468 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to aws-observability, differing in 26 lines, and is treated as a copy.
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