get_symbol_complexity_trend

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds that it requires git and is read-only, aligning with annotations. It also details the return JSON structure, providing full behavioral transparency.

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?

Multiple sentences but each serves a purpose: identifies resource, lists metrics, notes git requirement, provides usage guidance, specifies read-only, and details return format. No filler; front-loaded with core purpose.

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?

Given no output schema, the description compensates by explicitly stating the return format. It covers all parameters, the tool's requirement (git), differentiation from sibling, and the exact context for use. Fully complete for an agent to invoke 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?

Input schema has full descriptions for all three parameters. The description adds value by explaining the return shape (snapshots with commit, date, metrics), helping agents understand how parameters influence results. Baseline 3, plus extra context from description.

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 analyzes a single symbol's complexity metrics over git history, specifying cyclomatic, nesting, params, and lines. It distinguishes itself from the sibling tool get_complexity_trend by focusing on per-symbol rather than file-level trends.

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?

Explicitly states when to use (track a specific function's complexity evolution) and when not (for file-level trends, use get_complexity_trend instead). Provides clear context without ambiguity.

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