IndieStack

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

Annotations only declare readOnlyHint=true. The description adds critical behavioral context: data provenance ('mined from real package.json / requirements.txt diffs across thousands of GitHub repos'), methodology ('verified package diff analysis'), and return structure ('momentum signal, adoption sources, departure destinations').

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?

Excellent structure with front-loaded value proposition, followed by methodology, bulleted usage scenarios, return value summary, and parameter details. No wasted words; every sentence provides actionable context.

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?

For a single-parameter tool with existing output schema, the description is comprehensive: covers data source, usage contexts, return values, and parameter semantics. No gaps remain for the agent to use the tool effectively.

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?

Despite 0% schema description coverage, the Args section fully compensates with concrete examples ('jest', 'express'), format constraints ('npm/pip package name, not IndieStack slug'), and explicit lookup instructions via get_tool_details() 'SDK Packages' field.

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 specific verb+resource ('Query real migration data from GitHub repos') and clearly distinguishes from siblings by emphasizing 'ground truth, not marketing' and migration-specific analysis (FROM/TO package flows) versus general tool info or recommendations.

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?

Includes explicit 'Use this when:' section with four specific scenarios (deciding between tools, validating migrations, checking momentum, industry direction). Also cross-references sibling tool get_tool_details() for package name resolution, providing clear workflow guidance.

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