analyze_config_impact

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

There are no annotations, so the description bears full responsibility for behavioral transparency. It clearly frames the tool as an analysis operation ('Analyze what code is affected'), and its Returns section implies no side effects, but it does not explicitly state that the tool is read-only or mention any requirements (e.g., git history availability) or limitations. It does disclose that it can trace conditional logic and examine git history, which is useful, but it leaves the safety profile implicit.

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 well-organized with clear sections (Purpose, Use Cases, Args, Returns) and the core purpose is front-loaded in the first sentence. The use-case bullet list is helpful but slightly redundant with the subsequent 'Critical for...' sentence, adding minor verbosity. The Args section is necessary given the 0% schema coverage, so the length is justified.

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?

The description covers the tool's purpose, use cases, parameters, and a high-level return description, which is good given no output schema. However, it omits prerequisites (e.g., the repository must be a valid Git repository for historical changes), potential failure modes (e.g., unknown config key), and the structure of the returned analysis (e.g., whether it includes file paths, line numbers, or severity ratings). For a tool with six parameters and no output schema, this leaves some contextual ambiguity.

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?

The description includes a dedicated 'Args:' section that explains each of the six parameters, including the required config_key with examples ('DEBUG', 'DATABASE_URL'), the boolean flags' purposes (trace dependent logic, default handling, historical changes), and path semantics. This fully compensates for the 0% schema coverage, giving the agent a clear understanding of what each parameter controls.

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 statement: 'Analyze what code is affected by specific configuration values,' which clearly identifies the verb (analyze), resource (code affected by config values), and scope (config-specific). This differentiates it from sibling tools like trace_dependency_impact or analyze_execution_paths, which are not config-specific. The Returns section further clarifies the output is an analysis with affected code paths and 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?

The description provides a bulleted list of use cases ('Use this tool when you need to understand: what code will behave differently...'), which gives explicit when-to-use guidance. However, it does not mention when not to use the tool or contrast it with sibling alternatives, so it stops short of a 5.

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