evaluate_coding_plan

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says the tool 'evaluates' a plan, but does not reveal what the evaluation returns (score, feedback, pass/fail), whether it is read-only, has side effects, or requires any prerequisites. The naming of principles adds context but not behavioral clarity.

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 a single, front-loaded sentence that names the verb, resource, and the specific evaluation criteria without any redundant phrasing or fluff. It is extremely efficient and easy to parse.

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 tool has no output schema, so the description should hint at what the evaluation produces. It mentions the principles but does not explain how they are applied or what the outcome looks like. The optional task_scope parameter is not given extra context beyond the schema. Adequate for basic understanding, but an agent cannot fully predict the tool's output or behavior.

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%, meaning both parameters (task_scope, plan_description) have basic descriptions in the input schema. The tool description adds no additional meaning about these parameters beyond what the schema already provides. The baseline of 3 is appropriate since the schema handles parameter documentation adequately.

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 evaluates a proposed technical implementation plan against three named Karpathy principles (Simplicity, Surgical Scope, Goal Verification). This distinctly separates it from sibling tools like get_karpathy_rules (retrieves rules) and generate_verification_checklist (generates a checklist), making the intent unambiguous.

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 gives no guidance on when to use this tool versus alternatives such as get_karpathy_rules or generate_verification_checklist. It lacks any conditions, exclusions, or context that would help an agent decide between them. The agent must infer usage from the name alone, which is insufficient.

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