agda_compute_in_goal

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

With no annotations, the description carries the full burden. It discloses that evaluation happens within a goal's context and mentions goal_id comes from agda_load output, but it does not explicitly state whether the operation is read-only or has side effects. It adds some behavioral context but is not a full safety/behavior profile.

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 concise and front-loaded, with a two-sentence explanation followed by a bulleted arg list. Every sentence adds value and there is no filler.

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 effectively covers the core purpose, the key distinction from agda_compute, and parameter semantics. Since an output schema exists, return values need no explanation. It is complete for an agent to select and invoke the tool, though it could mention error conditions or expression syntax.

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 description coverage is 0%, but the description fully compensates by explaining all parameters: file_path is an absolute path, goal_id is the goal/hole number from agda_load output, and expr is the expression to evaluate. This adds meaning beyond the bare schema property names.

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?

Description clearly states the tool normalizes/evaluates an expression in a specific goal's context. The verb 'Normalize (evaluate)' is specific and the resource is well-defined, with explicit contrast to agda_compute.

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 explicitly names agda_compute as the alternative and explains the scope difference: 'Unlike agda_compute which works at top level, this evaluates within a goal's local context.' This provides clear context for when to use this tool, though it does not list exclusions or when-not-to-use scenarios.

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