analyze-dashboard
Deeply analyze Amplitude dashboards by analyzing key charts, surfacing top areas for concern and takeaways, identify anomalies, then explain changes using customer feedback trends.
77
72%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./analytics-skills/skills/analyze-dashboard/SKILL.mdQuality
Discovery
67%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 does a good job specifying concrete analytical actions and targets a clear niche by naming Amplitude specifically and combining dashboard analysis with customer feedback. Its main weakness is the lack of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. Adding trigger guidance and a few more natural keyword variations would strengthen it significantly.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks to review Amplitude dashboards, investigate metric changes, or understand product analytics trends.'
Include additional natural trigger terms users might say, such as 'metrics', 'product analytics', 'usage data', 'dashboard review', or 'data anomalies'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'analyze key charts', 'surfacing top areas for concern and takeaways', 'identify anomalies', 'explain changes using customer feedback trends'. These are concrete, distinct analytical steps. | 3 / 3 |
Completeness | The 'what' is well-covered with specific analytical actions. However, there is no explicit 'Use when...' clause or equivalent trigger guidance telling Claude when to select this skill, which caps this at 2 per the rubric guidelines. | 2 / 3 |
Trigger Term Quality | Includes 'Amplitude dashboards', 'charts', 'anomalies', and 'customer feedback' which are relevant keywords. However, it misses common variations users might say like 'metrics', 'analytics', 'product data', 'usage data', 'trends', or 'dashboard review'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'Amplitude dashboards' with 'customer feedback trends' creates a very specific niche. The mention of Amplitude as a specific platform and the cross-referencing with customer feedback makes this clearly distinguishable from generic analytics or dashboard skills. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, actionable skill that provides clear workflow sequencing with specific tool calls and well-defined output formatting. The chart-type analysis guidance in Step 3 adds genuine domain-specific value that Claude wouldn't inherently know. Minor weaknesses include some verbosity in the 'When to Use' and 'Best Practices' sections, and the lack of progressive disclosure through supporting files, though the content length is reasonable for a single file.
Suggestions
Trim the 'When to Use' section to 2-3 core use cases and consolidate overlapping best practices to reduce token usage.
Consider extracting the chart-type analysis patterns (Step 3) into a separate reference file if the skill grows, to keep the main workflow lean.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient and avoids explaining concepts Claude already knows, but some sections are slightly verbose—e.g., the 'When to Use' section has 5 bullet points that could be trimmed, and some best practices repeat guidance already implicit in the workflow (like 'be concise'). The chart-type analysis guidance in Step 3 is dense but earns its place as domain-specific knowledge. | 2 / 3 |
Actionability | The skill provides concrete, specific tool calls (Amplitude:get_dashboard, Amplitude:query_charts, Amplitude:get_feedback_insights, Amplitude:get_feedback_mentions) with clear parameters and sequencing. The output format is well-specified with exact section headers, emoji markers, and priority tags ([p0]-[p3]). Chart-type analysis guidance is specific and decision-relevant. | 3 / 3 |
Workflow Clarity | The 6-step workflow (Steps 0-5) is clearly sequenced with logical progression from URL parsing to dashboard retrieval to chart analysis to feedback contextualization to synthesis. Step 4 includes explicit skip conditions (a form of validation/branching), and the prioritization guidance in Step 2 helps with decision-making. The workflow handles the optional feedback step gracefully. | 3 / 3 |
Progressive Disclosure | The content is well-organized with clear sections and headers, but it's a single monolithic file with no references to supporting documents. The chart-type analysis guidance in Step 3 and the extensive best practices section could potentially be split into reference files for cleaner navigation, though the overall length is manageable. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- amplitude/builder-skills
- Commit
221ffaa
- Reviewed
Table of Contents
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