IndieStack

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

Annotations only declare readOnlyHint=true. The description adds valuable behavioral context by detailing what data is returned (maintenance status, stars, issues) and explaining the tool's logic (flags stale/archived tools, suggests alternatives). No contradiction with annotations.

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

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

Excellently structured with clear sections: purpose, return values/behavior, usage scenarios, and arguments. Information is front-loaded and every sentence serves a specific function. The bullet points for usage scenarios are efficient and scannable.

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

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

Complete given the tool's moderate complexity and rich ecosystem context. It references the output schema implicitly by summarizing returned fields, and explicitly links to sibling tool find_tools() to complete the usage workflow. No gaps remain for an agent to invoke this tool correctly.

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

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

With 0% schema description coverage, the description fully compensates by documenting the 'slugs' parameter format (comma-separated), providing concrete examples ('hanko,plausible,polar'), and specifying provenance ('Get slugs from find_tools() search results'), which is critical for successful invocation.

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

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

The description opens with a specific verb ('Check') and resource ('maintenance health of indie tools'), distinguishing it from sibling tools like find_tools (discovery) or compare_tools (comparison). It further clarifies scope by listing specific outputs (last commit date, GitHub stars, open issues) and actions (flags stale tools, suggests alternatives).

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

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

Provides an explicit 'Use this when:' section with four specific scenarios (reviewing tech stack, pre-commitment evaluation, dependency checks, auditing). This offers clear positive guidance, though it stops short of explicitly naming alternative tools for different use cases (e.g., 'use analyze_dependencies for code-level analysis instead').

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