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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.

72

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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-sequenced with concrete formulas, templates, and validation checkpoints, but it is verbose and keeps most detail inline rather than splitting it into referenced files. Tightening prose and moving dense reference material into bundle files would lift the two middle dimensions.

Suggestions

Trim conceptual exposition Claude already knows (e.g. 'Why AI PMF Expires' prose, the buyer-shift narrative) to the bare claims needed to justify the frameworks, keeping the specialized tables and formulas.

Move the dense reference material — the ICP scoring model, enrichment waterfall thresholds, Sean Ellis benchmarks, and pricing landscape — into `references/quick-reference.md` (or dedicated reference files) and link to them from the body so SKILL.md stays an overview.

Signal the reference earlier and more explicitly (e.g. a 'Reference' section near the top listing what `references/quick-reference.md` contains) rather than a single trailing mention.

DimensionReasoningScore

Conciseness

The ~466-line body pads specialized tables with prose explaining concepts Claude largely already knows ('Why AI PMF Expires,' the buyer-shift narrative, what positioning is), so it is mostly efficient but noticeably over-long and could be tightened; not a 1 because the scoring models, thresholds, and templates are genuinely specialized reference material, and not a 3 because the conceptual framing is far from lean.

2 / 3

Actionability

Provides concrete, copy-paste-ready guidance for an instruction skill: weighted scoring formulas with explicit weights, confidence thresholds (e.g. 0.85), named tools (Clay, Apollo, ZoomInfo), the positioning-statement template, the landing-page structure, Sean Ellis score bands, and a week-by-week playbook with checkboxes.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced (6-week implementation playbook, 7-step ICP workflow, weekly PMF cadence table) with explicit validation checkpoints — back-testing against last quarter's wins/losses, the five-check messaging validation, and prospect testing — plus checklists for complex processes.

3 / 3

Progressive Disclosure

The body is largely a monolithic inline wall of text with only a single reference (`references/quick-reference.md`, which exists) weakly signaled near the end ('read … when you need detailed reference'); content that could live in separate reference files (detailed scoring models, frameworks) is inline, fitting the 'some structure but content that should be separate is inline' anchor.

2 / 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, clearly stating both what the skill does and when to use it with a negative boundary. It is among the strongest examples and needs no changes.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('define their ideal customer profile, position an AI product, build messaging architecture, or validate product-market fit') rather than vague language; voice stays third-person ('the user wants to'), consistent with the good examples, so no voice penalty applies.

3 / 3

Completeness

Explicitly answers what ('This skill covers market positioning, ICP definition, messaging architecture, and PMF validation for AI-native products') and when ('When the user wants to… Also use when the user mentions…'), plus a negative boundary ('Do NOT use for technical implementation, code review, or software architecture').

3 / 3

Trigger Term Quality

Includes a broad set of natural terms a user would say — 'ICP,' 'ideal customer profile,' 'positioning,' 'PMF,' 'product-market fit,' 'messaging,' 'buyer persona,' 'enrichment signals,' 'market positioning,' 'competitive positioning' — giving strong coverage.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear AI-GTM niche with distinct trigger terms and an explicit exclusion clause, making it unlikely to fire for unrelated 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.

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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