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observability-engineer

Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. Use PROACTIVELY for monitoring infrastructure, performance optimization, or production reliability.

47

Quality

50%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/observability-engineer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

16%Weight 40%Scale 1-5

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

The body reads as an LLM persona resume rather than an actionable skill: massive capability lists, no executable guidance, and no progressive disclosure to reference files. It assumes Claude lacks knowledge it already has and provides almost nothing copy-paste ready.

Suggestions

Replace the capability/knowledge bullet catalogs with a concise overview and move detailed tool guidance into reference files (e.g., references/monitoring.md, references/tracing.md) linked one level deep.

Add concrete, executable examples — sample PromQL queries, an OpenTelemetry collector config snippet, or a Grafana dashboard JSON block — so guidance is copy-paste ready rather than abstract.

Tighten the Instructions/Response Approach into a sequenced workflow with explicit validation checkpoints (e.g., "verify the alert fires in a test runbook before enabling in production") and error-recovery feedback loops.

DimensionReasoningScore

Conciseness

Severely verbose: ~150 bullet points enumerate tool ecosystems (Prometheus, Grafana, Jaeger, ELK, Splunk, etc.) and a "Knowledge Base" restates SRE/observability concepts Claude already knows, with heavy padding throughout.

1 / 5

Actionability

Entirely abstract — the Instructions ("Identify critical services", "Define signals", "Build dashboards") and Response Approach describe rather than instruct, with no executable code, commands, or concrete configurations anywhere in the body.

1 / 5

Workflow Clarity

A numbered sequence exists (4-step Instructions, 8-step Response Approach) but validation checkpoints are implicit and lack concrete feedback loops; step 4 "Validate signal quality" names validation without specifying how to check or recover.

3 / 5

Progressive Disclosure

Monolithic single file with no bundle references; the extensive capability catalog and knowledge base clearly belong in separate reference files but are all inlined, despite section headers providing some structure.

2 / 5

Total

7

/

20

Passed

Description

83%Weight 40%Scale 1-5

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

A strong description that clearly states both capabilities and proactive trigger conditions with concrete, natural-language terms. Minor trimming of filler ("comprehensive observability strategies") and added synonyms would tighten it further.

DimensionReasoningScore

Specificity

Names several concrete actions — "Build production-ready monitoring, logging, and tracing systems", "SLI/SLO management", and "incident response workflows" — though "comprehensive observability strategies" is generic filler, leaving minor coverage gaps.

4 / 5

Completeness

Explicitly answers both what (build monitoring/logging/tracing, SLI/SLO management, incident response) and when ("Use PROACTIVELY for monitoring infrastructure, performance optimization, or production reliability") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural trigger phrases users would say ("monitoring infrastructure", "performance optimization", "production reliability", "SLI/SLO") with good coverage, but misses common synonyms and informal variants.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear observability/reliability niche with distinct triggers, but "performance optimization" and "production reliability" overlap slightly with general dev or SRE-adjacent skills.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
rmyndharis/antigravity-skills
Reviewed

Table of Contents

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