generate

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

Annotations (readOnlyHint=false) indicate mutation; the description reinforces that it rebuilds the graph and reuses a parse cache. It adds detail about cloning from git URLs and incremental behavior. No contradictions.

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?

The description is tightly written (around 80 words), front-loaded with the main purpose, and efficiently covers key details without excess.

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 tool with 2 parameters and existing output schema, the description is comprehensive: it explains what it does, when to use, parameters, and behavioral details. No gaps evident.

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?

Schema coverage is 100% with parameter descriptions. The description adds extra context: repo_path defaults to the server's repo and accepts git URLs, and incremental defaults to true. This adds meaning beyond the schema.

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 clearly states the tool scans and rebuilds a structural graph using tree-sitter AST parsing, auto-detects languages/frameworks, and runs cross-stack resolvers. It distinguishes from siblings like graph_view and flow which likely use the generated graph.

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?

The description says 'Call on first use or after major refactors,' providing clear usage context. It also explains incremental mode and when to force full reparse, but does not explicitly state when to avoid using it in favor of alternatives.

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