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advanced-analytics-dashboard

Dashboard metric register: metric, source module, formula, period, value, target, trend, owner and last-updated, as CSV, SQL, JSON Schema or Notion on request. Use for KPI dashboards.

Quality

74%

Does it follow best practices?

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tessl review fix ./plugins/agentic-awesome-skills-claude/skills/advanced-analytics-dashboard/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 highly actionable, with complete copy-paste CSV/SQL/JSON Schema/Notion artifacts, a clear five-step interaction flow, and good safety/pitfall guidance. Its weaknesses are repetition of the same interaction rules across multiple sections and the absence of any progressive disclosure — a ~290-line monolith whose artifact templates would fit better in reference files.

Suggestions

Deduplicate the interaction rules: state 'one question per message' and the Step 4 recommendation once, and have Best Practices, Pitfalls, and Examples reference them instead of restating them verbatim.

Move the SQL DDL, JSON Schema, Notion property mapping, and Field Reference tables into reference files (e.g. references/artifacts.md) and keep SKILL.md as an overview with one-level-deep, clearly signaled links.

Add an explicit post-build validation step (e.g. verify emitted column names match the Field Reference across CSV/SQL/JSON before presenting artifacts) to close the feedback loop that is currently only implied by 'Report material validation failures or limitations separately'.

DimensionReasoningScore

Conciseness

The body is mostly procedural and free of concept explanations Claude already knows, but repeats the same guidance several times: 'ask one question at a time' appears in Step 2, Best Practices ('One question per message'), Common Pitfalls ('asked all six questions in one message'), and the Reusable Prompt; the Step 4 recommendation text is restated verbatim in the Examples section. This matches 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than 4, whose trimming burden would be minor.

3 / 5

Actionability

The skill provides fully copy-paste-ready artifacts: a concrete CSV header row, complete PostgreSQL CREATE TABLE DDL, a full JSON Schema object, a Notion property mapping table, and a worked example dialogue with the exact next-step offer. The intent-dispatch table in Step 1 and the internal YAML context shape give exact executable guidance, matching 'fully executable; copy-paste ready code or commands; specific examples cover the common cases'.

5 / 5

Workflow Clarity

Steps 1-5 are clearly sequenced (identify intent, ask only what is missing, hold context, recommend, build only on request) with an explicit workflow chain 'Metric defined → Source data → Calculation → Refresh → Decision review' and some checkpoints ('build it after resolving essential missing facts', 'Report material validation failures or limitations separately'). It is not 5 because there is no explicit validate-and-fix feedback loop after artifact generation — verification detail is delegated to the unbundled shared contract and @notion-manual-import — matching 'clear sequence with most checkpoints present; minor validation gaps'.

4 / 5

Progressive Disclosure

Sections are well organized (Overview, When to Use, Steps, Field Reference, Examples, Pitfalls), and external skill references (@notion-manual-import, Module Catalog) are clearly signaled. However the full SQL DDL, JSON Schema, Notion mapping, field reference and select-option tables — roughly half the file — are inlined rather than split into reference files, and the skill is ~290 lines, well past the under-50-line simple-skill exception. This matches 'some structure but could be better organized; content that should be separate is inline' rather than 4, where most content would be appropriately placed in separate files.

3 / 5

Total

15

/

20

Passed

Description

67%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.

The description is concrete and specific about what the skill produces (field list plus four artifact formats) and includes an explicit 'Use for...' trigger, both in third person without fluff. Its main weakness is the thin trigger coverage — a single 'KPI dashboards' phrase misses the natural synonyms users would say when they need this skill.

Suggestions

Broaden the 'when' clause with 2-3 concrete trigger phrases users would naturally say, e.g. 'Use when the user mentions a KPI dashboard, analytics dashboard, business metrics dashboard, or metric tracking'.

Include common keyword variations such as 'metrics register', 'KPI tracking', or 'dashboard template' so the description matches how users actually phrase the request.

Name the core action verbs (define metrics, map sources, emit templates) alongside the field list so capabilities read as actions rather than only an inventory.

DimensionReasoningScore

Specificity

The description enumerates concrete deliverables — "metric, source module, formula, period, value, target, trend, owner and last-updated, as CSV, SQL, JSON Schema or Notion" — listing several specific outputs with only minor gaps (it names artifacts more than actions). It is not score 5 because the coverage is a field/format list rather than a comprehensive set of actions, and not 3 because far more than 1-2 concrete capabilities are named.

4 / 5

Completeness

It answers both parts: 'what' is explicit ("Dashboard metric register: metric, source module, formula, period, value, target, trend, owner and last-updated, as CSV, SQL, JSON Schema or Notion on request") and 'when' is present ("Use for KPI dashboards"). It is not 5 because the 'when' clause is a single brief trigger with no concrete phrase variations, matching the anchor 'has both what and when; when could be more explicit or specific'.

4 / 5

Trigger Term Quality

The only natural trigger phrase is "Use for KPI dashboards"; the keyword "dashboard" appears once with a single qualifier. Common variations a user would actually say — "analytics dashboard", "business metrics", "metric tracking", "KPI tracking" — are missing, matching the anchor 'Some relevant keywords but missing common variations or synonyms'. It is above 2 because 'KPI dashboards' is a genuinely natural phrase, and below 4 because coverage of synonyms is thin.

3 / 5

Distinctiveness Conflict Risk

The trigger "KPI dashboards" plus the specific field register (source module, formula, trend, owner) carves out a clear niche distinct from generic spreadsheet or database-register skills. It is not 5 because 'KPI dashboards' could still overlap with sibling analytics/metrics modules in the same catalog, matching 'mostly distinct; minor overlap risk with closely related skills'.

4 / 5

Total

15

/

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

sickn33/agentic-awesome-skills

Path

plugins/agentic-awesome-skills-claude/skills/advanced-analytics-dashboard/SKILL.md

Reviewed

Table of Contents

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