extract_call_graph

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

No annotations are provided, so the description carries the burden. It indicates the operation is analytical ('Extract and analyze') and discloses output statistics, but does not state whether it modifies anything, requires a build step, or has side effects. The description is not misleading but lacks depth about potential limitations or read-only guarantees.

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?

Single sentence, front-loaded with the main purpose, followed by a compact list of return statistics. No wasted words or redundant repetition of the tool name.

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 two-parameter tool with no output schema, the description adequately covers the return contract. However, the unexplained 'backend' parameter is a notable gap given the absence of schema descriptions, preventing full completeness.

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 0%, and the description does not explain either parameter. It mentions 'of a Python project' which hints at workingDirectory but never maps it to the parameter. The 'backend' parameter is completely undocumented, leaving the agent without guidance on valid values or purpose.

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 uses a specific verb phrase 'Extract and analyze' with a clear resource ('call graph of a Python project') and lists concrete return values (node count, edge count, SCC count, etc.). This distinguishes it from sibling tools focused on testing, synthesis, and graph queries.

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?

It clearly implies when to use this tool (when analyzing a Python project's call graph structure) but does not explicitly mention alternatives or exclusions. The context is clear enough for an agent to select it for call-graph analysis, though it could benefit from stating that it is for static analysis and not for dynamic tracing.

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