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beyla

Grafana Beyla eBPF auto-instrumentation for application observability without code changes. Covers supported languages/runtimes, requirements, installation, configuration (discovery, eBPF settings, OTLP traces export, Prometheus metrics export), Kubernetes deployment, and integration with Grafana Cloud. Use when setting up zero-code instrumentation, configuring eBPF probes, deploying Beyla to Kubernetes, connecting to Tempo/Prometheus, or troubleshooting instrumentation issues.

68

Quality

82%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

64%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a solid reference skill with excellent actionability — concrete, executable configurations for multiple deployment scenarios. Its main weaknesses are the lack of a clear end-to-end workflow with validation/verification steps and the monolithic structure that could benefit from splitting detailed YAML manifests into separate files. The content is slightly verbose but generally well-organized.

Suggestions

Add an explicit end-to-end workflow section with numbered steps and validation checkpoints (e.g., 'verify BTF support → deploy Beyla → check logs for successful eBPF attachment → confirm traces in backend → configure routes decorator').

Add a troubleshooting section or verification commands (e.g., checking Beyla logs for common errors like 'failed to attach eBPF probe', verifying traces arrive at the OTLP endpoint).

Split the large Kubernetes manifests (DaemonSet, RBAC) and Alloy config into separate referenced files to keep SKILL.md as a concise overview with pointers.

DimensionReasoningScore

Conciseness

The skill is mostly efficient with good use of tables and code blocks, but includes some unnecessary commentary (e.g., 'Beyla is a Grafana eBPF auto-instrumentation tool that captures HTTP/gRPC traffic and generates traces and metrics without modifying application code' is something Claude already knows from the skill description). The supported languages table and environment variables table are useful reference material but the overall document is quite long (~200 lines) and could be tightened.

2 / 3

Actionability

Provides fully executable, copy-paste ready code for Docker, Helm, DaemonSet YAML, configuration files, RBAC setup, and Alloy integration. Commands and configurations are concrete with specific values and clear alternatives noted in comments.

3 / 3

Workflow Clarity

The skill presents individual configuration blocks clearly but lacks an explicit end-to-end workflow with validation checkpoints. There's no verification step after deployment (e.g., 'check Beyla logs for successful attachment', 'verify traces appear in Tempo'), and no troubleshooting feedback loop for common failure modes like missing BTF support or insufficient privileges.

2 / 3

Progressive Disclosure

The content is well-sectioned with clear headers, but it's a monolithic document with no references to supporting files. Several sections (like the full DaemonSet YAML, RBAC config, and Alloy config) could be split into separate reference files, keeping the SKILL.md as a concise overview. The single docs link at the top is helpful but insufficient for progressive disclosure.

2 / 3

Total

9

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is an excellent skill description that clearly defines a narrow, specific domain (Grafana Beyla eBPF instrumentation), lists concrete capabilities and topics covered, and provides explicit trigger guidance with a well-constructed 'Use when...' clause. The description uses proper third-person voice and includes rich, natural trigger terms that users in the observability/Kubernetes space would actually use.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions and topics: supported languages/runtimes, requirements, installation, configuration (with sub-topics like discovery, eBPF settings, OTLP traces export, Prometheus metrics export), Kubernetes deployment, and Grafana Cloud integration.

3 / 3

Completeness

Clearly answers both 'what' (Beyla eBPF auto-instrumentation covering languages, installation, configuration, deployment, integration) and 'when' with an explicit 'Use when...' clause listing five specific trigger scenarios including setup, configuration, deployment, connecting, and troubleshooting.

3 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'Beyla', 'eBPF', 'auto-instrumentation', 'zero-code instrumentation', 'Kubernetes', 'Tempo', 'Prometheus', 'Grafana Cloud', 'OTLP traces', 'observability'. These are all terms a user working in this domain would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a very clear niche: Grafana Beyla eBPF auto-instrumentation. The combination of 'Beyla', 'eBPF', and specific observability tooling (Tempo, Prometheus, Grafana Cloud) makes it extremely unlikely to conflict with other skills.

3 / 3

Total

12

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
grafana/skills
Reviewed

Table of Contents

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