save_prediction_analysis_html

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

With no annotations provided, the description carries full burden. It discloses that the tool saves files to disk (implied by output_path/html_name), provides status updates through MCP context, and requires specific inputs. However, it doesn't mention error conditions, file overwrite behavior, permission requirements, or what happens if the request_id is invalid. For a file-writing tool with no annotations, this leaves important behavioral gaps.

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 with clear sections (purpose, when to use, how to use). It's appropriately sized at 4 paragraphs. While efficient, the 'How to use' section could be more concise by combining related points, but overall it's well-organized and front-loaded with key information.

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 8 required parameters, no annotations, and no output schema, the description provides good usage guidance but lacks important context. It doesn't explain what the HTML output looks like beyond mentioning plots and expert opinions, doesn't cover error handling, and doesn't specify file format requirements beyond '.html' extension. For a complex tool with many parameters, this leaves significant gaps.

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 schema already documents all 8 parameters thoroughly. The description mentions request_id, output_path, and html_name in the 'How to use' section, but doesn't add meaningful semantic context beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'saves an analysis of a BinaryPredictor prediction to HTML' and specifies what the analysis includes (plot of distributions and expert opinions). It distinguishes from sibling tools like 'save_forecast' by focusing specifically on BinaryPredictor predictions, though it doesn't explicitly contrast with all siblings.

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 includes explicit 'When to use this tool' and 'How to use this tool' sections. It provides clear context: 'when you need to save the BinaryPredictor estimates for the user' and gives specific prerequisites (request_id from previous prediction) and usage steps. This is comprehensive guidance.

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