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dashboard-builder

Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.

64

Quality

76%

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tessl review fix ./skills/dashboard-builder/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

A disciplined, token-efficient skill body with a clear question-driven workflow and a useful quality checklist. Its main gap is actionability — the guidance stays at the level of direction rather than executable example, with no dashboard JSON or query samples to anchor output.

Suggestions

Add a minimal dashboard JSON skeleton (or a link to one per platform) under 'Build the minimum useful board' so output has a concrete structural anchor.

Include one example query per representative panel (e.g. a PromQL/MetricsQL snippet for consumer lag or p99 latency) in the Example Panel Sets to make panel guidance executable rather than nominal.

Insert an explicit validation feedback loop into the workflow (e.g. import/validate the JSON against the target platform, fix errors, re-validate) before the 'Cut vanity panels' step.

DimensionReasoningScore

Conciseness

Lean and efficient throughout — terse bullet lists, no padding, and no explanation of concepts Claude already knows ("The goal is not 'show every metric.'" frames intent without lecturing). Every token earns its place.

5 / 5

Actionability

The workflow steps and per-service panel lists are concrete direction, but there is no executable artifact anywhere: no example dashboard JSON skeleton, no sample PromQL/MetricsQL query, and no command for importing or validating a dashboard. Guidance like "Inspect existing dashboards first: JSON structure, query language" remains a high-level hint rather than executable instruction.

3 / 5

Workflow Clarity

A clearly sequenced 4-step workflow (define operating questions → study platform schema → build minimum useful board → cut vanity panels) with a final Quality Checklist acting as a validation gate ("valid dashboard JSON", "titles and units are present"). Falls short of a 5 because there is no explicit validate → fix → re-validate feedback loop inside the workflow itself.

4 / 5

Progressive Disclosure

No bundle files exist, and none are needed: the ~100-line body is cleanly sectioned with no inline bulk that belongs in a separate reference; the "Related Skills" entries point to sibling skills, not nested references. Well-organized sections fully cover this scope.

5 / 5

Total

17

/

20

Passed

Description

73%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 focused, well-scoped description in third-person voice with explicit what and when clauses and strong platform-specific triggers. Its main limitation is breadth of action coverage and an abstract when-clause that could name concrete user-request phrasings.

DimensionReasoningScore

Specificity

Names the domain clearly ("monitoring dashboards", "Grafana, SigNoz") and one concrete action ("Build monitoring dashboards that answer real operator questions"), but offers only a single action rather than the several specific actions required for a 4.

3 / 5

Completeness

Both parts are explicit: what ("Build monitoring dashboards that answer real operator questions...") and when ("Use when turning metrics into a working dashboard instead of a vanity board"). The when-clause is present but abstract, lacking the concrete user-mention triggers that distinguish a 5 (e.g. "when the user mentions Grafana, SigNoz, or consumer lag").

4 / 5

Trigger Term Quality

Includes natural phrases operators actually say — "monitoring dashboards", "Grafana", "SigNoz", "metrics", "dashboard" — but misses common variations such as "observability", "panels", or platform-agnostic synonyms like "monitoring board".

4 / 5

Distinctiveness Conflict Risk

Clear niche — building operator-facing monitoring dashboards on named platforms (Grafana, SigNoz) — with distinct trigger terms; minimal risk of firing for the wrong skill.

5 / 5

Total

16

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
affaan-m/ECC
Reviewed

Table of Contents

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