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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.

70

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is highly actionable and well-structured with effective progressive disclosure to two verified reference files. Its weaknesses are moderate verbosity (redundant prose around tables and undated time-sensitive statistics) and the absence of explicit validation/feedback checkpoints in its workflows.

Suggestions

Trim prose that restates adjacent tables (e.g., the 'Agents replace human tasks...' paragraph and similar framing sentences) so tables and decision trees carry the load and every token earns its place.

Move or date-stamp time-sensitive adoption statistics (e.g., '126% growth... end of 2024 to end of 2025', '27% to 41%... Growth Unhunged 2025') into a clearly labeled dated/benchmark section so stale figures don't penalty conciseness over time.

Add explicit validation checkpoints to the workflow — e.g., after designing tiers, verify target gross margin and CPT are met, and iterate the charge metric if win/loss data shows value is diffuse.

DimensionReasoningScore

Conciseness

The body is dense with concrete, non-obvious domain data, but it is long (~240 lines) with prose that restates what tables already show, some Claude-known framing, and time-sensitive claims ('126% growth... end of 2024 to end of 2025', '27% to 41%... 2025') that could be tightened or localized to a dated section.

2 / 3

Actionability

Highly actionable for an instruction/strategy skill: explicit decision trees, concrete pricing formulas ('1/3 to 1/10 of human equivalent cost', '1.2-2x your unit cost'), real benchmark prices, and step-by-step hybrid-design steps that are directly usable.

3 / 3

Workflow Clarity

Discovery ('Before Starting') and design steps are sequenced via decision trees and numbered steps, but 'Before Starting' is a flat checklist with no explicit validation checkpoints or feedback loops (e.g., validate tier breaks against a margin target and iterate), which the score-3 anchor requires.

2 / 3

Progressive Disclosure

The body is an overview of core frameworks and clearly signals two real, one-level-deep bundle files — references/implementation-guide.md and references/quick-reference.md — both verified to exist on disk with their scopes stated, matching the well-signaled one-level-deep anchor.

3 / 3

Total

10

/

12

Passed

Description

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.

The description is specific, trigger-rich, and complete, explicitly covering both what the skill does and when to invoke it while actively de-conflicting adjacent technical skills. It is written in third person and avoids fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('choose a charge metric, design pricing tiers, or optimize margins') plus three coverage areas ('pricing strategy, packaging, and margin management'), matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both 'what' ('This skill covers pricing strategy, packaging, and margin management for AI-native products') and 'when' ('When the user wants to price an AI product... Also use when the user mentions...'), with explicit trigger guidance and a negative scope clause.

3 / 3

Trigger Term Quality

Provides broad natural-language triggers a GTM/product leader would actually say ('AI pricing,' 'usage-based pricing,' 'BYOK,' 'bring your own key,' 'cost per token,' etc.), including common variations, matching the good-coverage anchor.

3 / 3

Distinctiveness Conflict Risk

Clear niche (AI-native product pricing) with distinct triggers and an explicit de-confliction scope ('Do NOT use for technical implementation, code review, or software architecture'), making it unlikely to trigger for the wrong skill.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
tech-leads-club/agent-skills
Reviewed

Table of Contents

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