service-mesh-observability

Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.

Quality

71%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/service-mesh-observability/SKILL.md

Quality

Content

58%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.

Highly actionable template catalog with excellent executable coverage of Istio, Linkerd, Jaeger, Grafana, Kiali, and OpenTelemetry, but it lacks a real sequenced workflow with validation checkpoints and inlines a large volume of content that would benefit from progressive disclosure into bundle files.

Suggestions

Replace the generic 'Instructions' boilerplate with a concrete end-to-end observability setup workflow with explicit validation checkpoints (e.g., apply config -> verify Prometheus targets are up -> confirm traces appear in Jaeger -> check alerts fire).

Move the bulky reference material (Grafana dashboard JSON, full alerting rules, per-tool install YAMLs) into files under references/ and keep SKILL.md as a concise overview that links to them one level deep.

Trim concept explanations Claude already knows (the Three Pillars ASCII diagram and Golden Signals table) to free context budget.

Dimension	Reasoning	Score
Conciseness	The body is mostly dense, useful templates, but includes unnecessary padding Claude does not need: the 'Three Pillars of Observability' ASCII diagram, the Golden Signals concept table, and generic boilerplate in 'Instructions' ('Clarify goals... Apply relevant best practices and validate outcomes').	3 / 5
Actionability	Provides fully executable, copy-paste-ready configs and commands across the common cases — Prometheus ConfigMap/ServiceMonitor, PromQL queries, Jaeger deployment YAML, Linkerd CLI, Grafana dashboard JSON, Kiali, OpenTelemetry collector, and alerting rules.	5 / 5
Workflow Clarity	The content is a template catalog rather than a sequenced workflow; the only 'sequence' is three lines of generic boilerplate ('Clarify goals... Apply best practices and validate outcomes... Provide actionable steps and verification') with poorly defined steps and no concrete validation checkpoints for the actual mesh task.	2 / 5
Progressive Disclosure	Sections are clearly headed (Templates 1-7, Alerting Rules, Best Practices, Resources) and external doc links are provided, but at ~390 lines with no bundle files, substantial content that could live in separate reference files (full Grafana JSON, alerting rules, tool configs) is inlined in SKILL.md.	3 / 5
	Total	13 / 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 explicitly answers both 'what' and 'when' with concrete, third-person trigger phrases. It is specific and distinct, with only minor gaps in capability coverage and trigger synonyms.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions — 'distributed tracing, metrics, and visualization' plus 'implementing SLOs' — but leaves minor gaps (logging and alerting are not explicitly named as capabilities).	4 / 5
Completeness	Clearly states what ('Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization') and when ('Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs'), with concrete trigger phrases.	5 / 5
Trigger Term Quality	Natural trigger phrases like 'setting up mesh monitoring', 'debugging latency issues', and 'implementing SLOs for service communication' are present, but mesh-specific synonyms (Istio, Linkerd, Jaeger, Kiali) are missing from the triggers.	4 / 5
Distinctiveness Conflict Risk	'Service mesh observability' is a clear niche with mesh-specific triggers, but there is minor overlap risk with general observability/Prometheus monitoring skills.	4 / 5
	Total	17 / 20 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: rmyndharis/antigravity-skills
Path: skills/service-mesh-observability/SKILL.md
Commit: 3eff4af

Reviewed: 5 days ago

Table of Contents

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