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product_review_plan

Read-onlyIdempotent

Get Lenny Zeltser's expert criteria for reviewing an existing product strategy plan. Returns focused guidance for constructive critique—what to check in each section, strategic coherence issues, and how to frame feedback collaboratively. Includes rating-sheet items (the lens taxonomy: structure, words, tone) as concrete reference points for grounded feedback on the plan's writing. This server never requests your plan and instructs your AI to keep it local. Use market_segment: "smb" to include SMB-specific review criteria. Use product_focus: "endpoint" to include endpoint viability assessment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoWhat aspects to focus on. 'completeness': is everything covered? 'strategy': are decisions coherent? 'feasibility': can this team execute?
sectionsNoSpecific sections to get review criteria for. Omit or use 'all' for complete review criteria.
review_typeNo'internal': reviewing your own plan (default). 'external-analysis': reviewing an analysis of another company. Adjusts criteria to focus on evidence tiering, source attribution, and marketing language.
product_focusNoInclude vertical-specific review criteria. 'endpoint': endpoint viability. 'ai_security': AI security market assessment.
market_segmentNoInclude SMB-specific review criteria.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / sections / items / enum
      Previous value: -[
-  "market_segmentation",
-  "product_capabilities",
-  "sales_gtm",
-  "pricing",
-  "delivery",
-  "trust",
-  "platform",
-  "team",
-  "competitive_landscape",
-  "integration_priorities",
-  "all"
-]New value: +[
+  "market_segmentation",
+  "product_capabilities",
+  "sales_gtm",
+  "pricing",
+  "delivery",
+  "trust",
+  "platform",
+  "team",
+  "competitive_landscape",
+  "defensibility_rubric",
+  "integration_priorities",
+  "all"
+]
  2. Changed1 schema field changed
    • addedInput schema / properties / review_type
      Added value: +{
+  "description": "'internal': reviewing your own plan (default). 'external-analysis': reviewing an analysis of another company. Adjusts criteria to focus on evidence tiering, source attribution, and marketing language.",
+  "enum": [
+    "internal",
+    "external-analysis"
+  ],
+  "type": "string"
+}
  3. Changed2 schema fields changed
    • changedInput schema / properties / product_focus / description
      Previous value: -"Include endpoint viability assessment."New value: +"Include vertical-specific review criteria. 'endpoint': endpoint viability. 'ai_security': AI security market assessment."
    • changedInput schema / properties / product_focus / enum
      Previous value: -[
-  "endpoint"
-]New value: +[
+  "endpoint",
+  "ai_security"
+]
  4. Added

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context beyond that: output contents (section checks, coherence issues, collaborative framing, rating-sheet taxonomy) and a privacy guarantee ('never requests your plan'), which enriches transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then covers behavioral details and parameter usage. It's slightly verbose with redundant parameter guidance, but each sentence serves a distinct function and the structure is logical.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description explains the nature of the returned guidance, the privacy behavior, and key parameter effects. It doesn't enumerate all output fields but gives enough context for an agent to invoke it appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with descriptive enum values, so the description adds little beyond the schema. It repeats the SMB/endpoint parameter hints but doesn't clarify the focus or sections arrays further; this is adequate given the schema's completeness.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description opens with a specific verb+resource: 'Get Lenny Zeltser's expert criteria for reviewing an existing product strategy plan.' This clearly states what the tool does and distinguishes it from siblings like product_get_guidelines or rating_get_sheet by focusing on plan review criteria.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for use (reviewing existing product strategy plans) and explicit parameter usage hints for market_segment and product_focus. It doesn't name alternatives or exclusions, but the context is sufficient to guide selection among sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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