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positioning-icp

When the user wants to define their ideal customer profile, position an AI product, build messaging architecture, or validate product-market fit. Also use when the user mentions 'ICP,' 'ideal customer profile,' 'positioning,' 'PMF,' 'product-market fit,' 'messaging,' 'buyer persona,' 'enrichment signals,' 'market positioning,' or 'competitive positioning.' This skill covers market positioning, ICP definition, messaging architecture, and PMF validation for AI-native products. Do NOT use for technical implementation, code review, or software architecture.

63

Quality

73%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./packages/skills-catalog/skills/(gtm)/positioning-icp/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

47%

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

This skill demonstrates strong domain expertise and excellent workflow structure with clear sequencing and validation checkpoints. However, it is severely over-length, explaining many concepts Claude already understands (PMF definitions, what enrichment signals are, April Dunford's methodology basics) and including extensive reference tables that should be in separate files. The content would be significantly more effective at roughly one-third its current length with heavy reference material moved to bundle files.

Suggestions

Reduce the body to ~150 lines by moving the scoring models, competitor tables, pricing landscape, and buyer shift analysis into separate reference files (e.g., references/scoring-models.md, references/competitor-positioning.md, references/buyer-shift.md)

Remove explanations of concepts Claude already knows: what PMF is, why positioning matters, what enrichment signals are, what April Dunford's methodology is. Instead, jump directly to the AI-specific adaptations and actionable steps.

Cut the 'Common Positioning Mistakes in AI' and 'Messaging Validation Checklist' tables to bullet points with just the fix/action, removing the explanatory columns that state obvious problems.

Add concrete output templates or examples showing what a completed positioning stack or ICP document should look like as a deliverable, rather than just describing the framework abstractly.

DimensionReasoningScore

Conciseness

This skill is extremely verbose at ~500+ lines. It explains concepts Claude already knows (what PMF is, what enrichment signals are, how SEO works, what April Dunford's methodology is). Massive tables repeat information that could be condensed significantly. The buyer shift section, pricing model landscape, and competitive intelligence sections add substantial token cost with information Claude could infer or already knows.

1 / 3

Actionability

The skill provides structured frameworks, checklists, scoring formulas, and templates that are reasonably actionable. However, there is no executable code, no concrete API calls, and the guidance remains at the strategic/conceptual level rather than providing copy-paste-ready deliverables. The scoring formulas are illustrative but not tied to specific tooling implementations.

2 / 3

Workflow Clarity

The implementation playbook (Weeks 1-6) provides a clear sequenced workflow with explicit checkpoints. The 90-day PMF revalidation cadence is well-structured with weekly actions, methods, and outputs. The ICP Definition Workflow has numbered steps with a clear validation step (back-testing against pipeline). The enrichment waterfall has explicit confidence thresholds and decision points.

3 / 3

Progressive Disclosure

The skill references `references/quick-reference.md` and cross-references other skills, which is good. However, the massive amount of inline content (scoring models, competitor tables, pricing landscapes, buyer shift analysis) should be split into separate reference files. The main SKILL.md tries to be both overview and comprehensive reference, resulting in a monolithic document.

2 / 3

Total

8

/

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.

This is a strong skill description that clearly defines its scope around AI product marketing strategy, provides comprehensive trigger terms covering both abbreviations and full phrases, and explicitly delineates boundaries with a 'Do NOT use' clause. The description is well-structured, uses third person voice appropriately, and would allow Claude to confidently select or reject this skill from a large pool.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'define their ideal customer profile, position an AI product, build messaging architecture, or validate product-market fit.' These are clear, actionable capabilities.

3 / 3

Completeness

Clearly answers both 'what' (market positioning, ICP definition, messaging architecture, PMF validation for AI-native products) and 'when' (explicit trigger terms listed, plus a 'Use when' equivalent at the start and 'Also use when' clause). Also includes a 'Do NOT use' boundary which adds clarity.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms including abbreviations and full forms: 'ICP,' 'ideal customer profile,' 'positioning,' 'PMF,' 'product-market fit,' 'messaging,' 'buyer persona,' 'enrichment signals,' 'market positioning,' 'competitive positioning.' These are terms users would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche in AI product marketing/positioning strategy. The explicit exclusion of 'technical implementation, code review, or software architecture' further reduces conflict risk with engineering-focused skills. The domain-specific trigger terms like 'ICP,' 'enrichment signals,' and 'buyer persona' are unlikely to overlap with other skills.

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
tech-leads-club/agent-skills
Reviewed

Table of Contents

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