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

69%

Does it follow best practices?

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Passed

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

Quality

Content

51%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 skill uses excellent progressive disclosure by offloading templates to a clearly signaled reference, but the body itself lacks an executable workflow with validation checkpoints and includes some conceptual padding. Adding a short sequenced implementation procedure with verification steps would markedly improve it.

Suggestions

Add a numbered implementation workflow (e.g., 1. enable metrics/tracing in mesh config, 2. deploy collector, 3. verify scraping/traces are flowing, 4. import dashboards) with explicit validation checkpoints between steps.

Trim the three-pillars ASCII art and golden-signals table or move them to the reference file, since these are concepts Claude already knows; keep only the mesh-specific signal thresholds.

Inline one or two copy-paste-ready commands (e.g., a key PromQL query or an Istio telemetry apply snippet) so the body is actionable without requiring the reference for the most common case.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient, but the three-pillars ASCII diagram and golden-signals table re-explain concepts Claude already knows, and the 'When to Use This Skill' list duplicates the description's triggers.	3 / 5
Actionability	The Do's/Don'ts give some concrete values (sample rates, alert thresholds), but all executable code and commands live in the reference file rather than inline, leaving the body's guidance incomplete on its own.	3 / 5
Workflow Clarity	There is no sequenced implementation workflow with validation checkpoints; the body is organized thematically (concepts, when-to-use, best practices) rather than as an operational process, and validation steps are absent.	2 / 5
Progressive Disclosure	The body is a clear overview that points to a single, well-signaled one-level-deep reference ('references/details.md') for templates and worked examples, with content appropriately split and easy navigation.	5 / 5
	Total	13 / 20 Passed

Description

87%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, well-structured description that clearly states capabilities and provides explicit, natural trigger guidance for a distinct niche. Minor gains are possible by adding a few more concrete actions and synonyms (tool names).

Dimension	Reasoning	Score
Specificity	Names the domain and lists several concrete actions ('distributed tracing, metrics, and visualization'), but stops short of comprehensive coverage by omitting logging, alerting, and dashboarding as explicit actions.	4 / 5
Completeness	It explicitly answers both 'what' (implement observability via tracing, metrics, visualization) and 'when' with concrete trigger phrases, matching the score-5 anchor pattern.	5 / 5
Trigger Term Quality	The 'Use when' clause supplies natural phrases users would say ('setting up mesh monitoring', 'debugging latency issues', 'implementing SLOs for service communication'), though common synonyms like tool names (Istio/Linkerd) or 'troubleshooting' are absent.	4 / 5
Distinctiveness Conflict Risk	'Service mesh observability' is a clear niche with distinct, mesh-specific triggers, giving minimal conflict risk with other skills.	5 / 5
	Total	18 / 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: wshobson/agents
Path: plugins/cloud-infrastructure/skills/service-mesh-observability/SKILL.md
Commit: d6837ae

Reviewed: about 12 hours ago

Table of Contents

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