ai-pricing

When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products. Do NOT use for technical implementation, code review, or software architecture.

Quality

88%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

82%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 comprehensive, highly actionable pricing-strategy body with concrete frameworks, real examples, and appropriate offloading of detailed topics to verified reference files. Minor improvements possible in trimming framing prose, adding validation checkpoints, and moving some deep-dive detail to references.

Suggestions

Add an explicit validation checkpoint to the workflow (e.g., confirm the recommended price lands between cost floor and 1/3-1/10 of human-equivalent cost before finalizing).

Trim framing prose such as "Pure pricing models have weaknesses. Consumption scares buyers. Per-seat misses expansion." to tighten token efficiency.

Consider moving the GitHub Copilot pricing-evolution detail into references/implementation-guide.md to keep the body focused on decision frameworks.

Dimension	Reasoning	Score
Conciseness	Dense, mostly-efficient reference material (decision trees, tables of real pricing data) where most tokens earn their place, but there is some framing prose ("Pure pricing models have weaknesses. Consumption scares buyers...") that could be trimmed.	4 / 5
Actionability	Highly concrete and executable: ASCII decision-tree flowchart, step-by-step hybrid design (STEP 1-4), outcome-pricing steps 1-5, specific dollar figures, and real company pricing examples (Intercom Fin $0.99/resolution, GitHub Copilot tiers).	5 / 5
Workflow Clarity	Clear sequences with a "Before Starting" clarification checklist, branching decision framework, and numbered design steps; lacks explicit validation/feedback checkpoints (e.g., verify margin target met before finalizing), though this is advisory strategy rather than a destructive operation.	4 / 5
Progressive Disclosure	Good structure with clearly signaled one-level-deep references to real files (`references/implementation-guide.md`, `references/quick-reference.md`, both verified present); some inline deep-dive detail (e.g., GitHub Copilot pricing evolution) could arguably live in references.	4 / 5
	Total	17 / 20 Passed

Description

95%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 strong, well-structured description with explicit what/when guidance, rich natural trigger terms including synonyms, and a clear negative boundary to avoid conflicts. The only minor gap is that the action list does not fully reflect the body's breadth (hybrid, BYOK, migration).

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ("choose a charge metric, design pricing tiers, or optimize margins" plus "pricing strategy, packaging, and margin management") but does not enumerate the full breadth covered in the body (hybrid models, BYOK, migration, competitive analysis).	4 / 5
Completeness	Explicitly answers both what (price an AI product, choose charge metric, design tiers, optimize margins) and when ("When the user wants..." / "Also use when the user mentions...") with concrete trigger phrases and an explicit negative boundary.	5 / 5
Trigger Term Quality	Comprehensive natural trigger terms with synonyms and abbreviations ("AI pricing," "usage-based pricing," "consumption pricing," "outcome pricing," "BYOK," "bring your own key," "per-seat pricing," "pricing tiers," "AI margins," "cost per token," "pricing model").	5 / 5
Distinctiveness Conflict Risk	Clear AI-product-pricing niche with distinct triggers and an explicit "Do NOT use for technical implementation, code review, or software architecture" boundary, minimizing overlap with adjacent skills.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

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: tech-leads-club/agent-skills
Path: packages/skills-catalog/skills/(gtm)/ai-pricing/SKILL.md
Commit: fc886b7

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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