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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 for monitoring infrastructure, performance optimization, or production reliability.

Quality

57%

Does it follow best practices?

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

Quality

Content

23%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 is a persona-style skill dominated by exhaustive capability, trait, and knowledge catalogs that restate what Claude already knows, with no executable guidance, code, or commands. The four-step Instructions sequence is the only actionable core and lacks validation checkpoints. Everything is inlined in one file with no progressive disclosure via references.

Suggestions

Cut the Capabilities, Behavioral Traits, Knowledge Base, and Example Interactions catalogs (~180 lines) down to the handful of items that encode genuinely non-obvious project decisions; Claude already knows what Prometheus, ELK, and PagerDuty are.

Replace abstract Instructions like "Define signals, instrumentation, and data retention" with concrete, executable guidance: example PromQL/OTel collector configs, an SLI definition template, and specific commands or scripts to run.

Add explicit validation checkpoints and a feedback loop to the workflow (e.g., verify alerts fire on a canary before rollout, re-tune thresholds when false positives appear), and move detailed material into clearly signaled one-level-deep reference files instead of inlining everything.

DimensionReasoningScore

Conciseness

Roughly 200 lines are padded catalogs of tools and practices Claude already knows (Prometheus, ELK, PagerDuty, chaos engineering, "Behavioral Traits", "Knowledge Base") that add no information Claude could not supply itself. This matches anchor 1 (severely verbose, heavily padded) rather than 2, since the padding dominates the entire body rather than appearing in a few sections.

1 / 5

Actionability

No code, commands, or concrete procedures appear anywhere; the Instructions section offers only high-level directives like "Define signals, instrumentation, and data retention". This fits anchor 2 (high-level hints present but missing specific executable steps) rather than 1, since a rough step sequence does exist.

2 / 5

Workflow Clarity

The Instructions section lists a coherent sequence (identify services and targets, define signals, build dashboards/alerts, validate signal quality and reduce noise), but checkpoints are implicit and there are no feedback loops or error-recovery guidance. Matches anchor 3 (steps listed, validation gaps) rather than 4.

3 / 5

Progressive Disclosure

No bundle files exist and no references are used; ~150 lines of capability catalogs that clearly belong in separate reference files are fully inlined in a single monolithic SKILL.md. Despite section headers, the structure is minimal for a file this size, placing it between anchors 2 and 3 but noticeably below the midpoint.

2 / 5

Total

8

/

20

Passed

Description

75%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 solid description that states concrete capabilities in third person and includes an explicit "Use for..." trigger clause. Its main weaknesses are buzzword phrasing ("comprehensive observability strategies") and a when-clause that misses several natural trigger terms (alerting, dashboards, on-call, SRE) that would improve both completeness and distinctiveness.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions ("Build production-ready monitoring, logging, and tracing systems", "SLI/SLO management", "incident response workflows") with only minor gaps such as dashboards and alerting. Not a 5 because "comprehensive observability strategies" is buzzword-adjacent and action coverage is not comprehensive; clearly above 3 since more than 1-2 concrete actions are listed.

4 / 5

Completeness

Both parts are present: a clear what ("Build production-ready monitoring, logging, and tracing systems. Implements... SLI/SLO management, and incident response workflows") and an explicit when ("Use for monitoring infrastructure, performance optimization, or production reliability"). Not a 5 because the when-clause omits concrete triggers like SLI/SLO definition, alerting setup, or incident investigation.

4 / 5

Trigger Term Quality

Natural phrases users would say appear ("monitoring infrastructure", "logging", "tracing", "incident response", "production reliability"), but common variations like "alerting", "dashboards", "on-call", or "SRE" are absent. Fits anchor 4 (good coverage, a few natural terms missing) rather than 5 (comprehensive synonyms/extensions).

4 / 5

Distinctiveness Conflict Risk

The observability niche is clear and mostly distinct from other skills, but the trigger "performance optimization" is broad and could overlap with performance-tuning or general DevOps skills. Minor overlap risk places it at 4 rather than 5, and clearly above 3 given the specific domain framing.

4 / 5

Total

16

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

rmyndharis/antigravity-skills

Path

skills/observability-engineer/SKILL.md

Reviewed

Table of Contents

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