diagnose-monetization
Diagnose revenue leaks, analyze willingness-to-pay, evaluate packaging and pricing, and identify expansion revenue opportunities. Use when a PM needs to improve conversion to paid, optimize pricing, reduce revenue churn, or find upsell and expansion opportunities.
73
67%
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 ./growth-skills/skills/diagnose-monetization/SKILL.mdQuality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly articulates specific capabilities in the monetization/pricing domain and provides explicit trigger guidance via a 'Use when...' clause. It uses third-person voice correctly, includes natural keywords a PM would use, and carves out a distinct niche that minimizes conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'diagnose revenue leaks', 'analyze willingness-to-pay', 'evaluate packaging and pricing', and 'identify expansion revenue opportunities'. These are distinct, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (diagnose revenue leaks, analyze willingness-to-pay, evaluate packaging/pricing, identify expansion revenue) and 'when' with an explicit 'Use when...' clause covering conversion, pricing optimization, revenue churn, and upsell scenarios. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords a PM would use: 'revenue leaks', 'willingness-to-pay', 'pricing', 'packaging', 'conversion to paid', 'revenue churn', 'upsell', 'expansion opportunities'. These cover a good range of terms users would naturally say when seeking monetization help. | 3 / 3 |
Distinctiveness Conflict Risk | Occupies a clear niche around monetization and pricing strategy for PMs. The specific focus on revenue leaks, willingness-to-pay, packaging, and expansion revenue makes it highly distinguishable from general analytics, financial modeling, or other PM skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a comprehensive monetization diagnosis framework with good analytical structure and useful cross-references to other skills. However, it is significantly over-verbose, explaining concepts Claude already knows (LTV:CAC, freeloaders vs future converts, expansion revenue basics) and could be compressed by 50%+ without losing actionable content. The lack of executable code/commands and missing validation checkpoints in a high-stakes workflow are notable gaps.
Suggestions
Cut explanatory prose by at least 50% — remove definitions of concepts Claude already knows (LTV:CAC, freeloaders, expansion revenue, value metrics) and keep only the specific analytical steps and sizing formulas.
Add validation checkpoints between steps, e.g., 'Before proceeding to Step 3, confirm you have sized all funnel components with actual numbers — if data is missing, flag it and use estimates with confidence ranges.'
Include a concrete worked example showing the revenue decomposition formula applied to a sample SaaS product with real numbers, making the framework immediately executable rather than abstract.
Extract the detailed step-by-step framework into a separate reference file and keep SKILL.md as a concise overview with the prompt template and key decision points.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~200+ lines. It explains general monetization concepts Claude already understands (what LTV:CAC means, what freeloaders are, what expansion revenue is). Much of the content reads like a textbook rather than actionable instructions, and the extensive prose explanations could be compressed significantly without losing clarity. | 1 / 3 |
Actionability | The skill provides a structured framework with specific formulas (Revenue = Users x Conversion Rate x ARPU x ...) and concrete analytical steps like sizing opportunities and building matrices. However, there is no executable code, no concrete data analysis commands, and the guidance remains at the strategic/analytical level with fill-in-the-blank templates rather than copy-paste-ready artifacts. | 2 / 3 |
Workflow Clarity | The five steps are clearly sequenced and logically ordered from decomposition through diagnosis to prioritization. However, there are no validation checkpoints or feedback loops — no step says 'verify this before proceeding' or 'if this analysis reveals X, go back to step Y.' For a high-stakes monetization change process, the lack of explicit validation gates is a gap. | 2 / 3 |
Progressive Disclosure | The skill references other skills (build-metric-tree, craft-experiment-design, diagnose-retention, create-chart) which is good cross-referencing. However, the main body is a monolithic wall of text with everything inline — the detailed step-by-step framework, anti-plays, and output format could benefit from being split into referenced files. No bundle files exist to support progressive disclosure. | 2 / 3 |
Total | 7 / 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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