analyze_karpathy_alignment

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states that it returns scores for five dimensions and detects First Principles indicators, with definitions for each dimension. This gives the agent an accurate understanding of what the tool computes and outputs, though it doesn't explicitly state that it's a read-only operation.

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-structured and front-loaded with the primary purpose, followed by a clear bulleted list of dimensions. It is slightly redundant in mentioning 'First Principles' indicators after already covering 'Building from Scratch' in the bullet list, but overall each sentence earns its place.

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 an output schema, so return values are covered separately. The description adds context about the scoring dimensions, making it clear what the analysis emphasizes. It is sufficiently complete for a non-destructive analysis tool, though it could mention potential limitations or data sources beyond GitHub.

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 100%, so the input schema already fully documents all four parameters. The description adds no additional parameter-specific details beyond the schema, which is acceptable given high schema coverage, but it does not enhance parameter understanding.

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 ('Analyze') and a well-defined resource ('GitHub contributions against the Andrej Karpathy Skills framework'). It clearly differentiates from sibling tools by covering all five skill dimensions at once, whereas siblings like scan_first_principles and detect_attention_to_detail focus on single dimensions.

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 clear context: it is for analyzing contributions against the full Karpathy framework, which implies when to use it. However, it does not explicitly mention when NOT to use it or point to alternative sibling tools, so it stops short of full guidance.

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