create_evaluation_pipeline

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 adds context about Blockly compatibility, UI rendering, and the requirement that graders be committed beforehand. It does not mention potential side effects beyond creation, nor failure modes or return values, but for a create tool this is sufficient. The description is transparent about its purpose and constraints, warranting a 4.

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, front-loaded with the core purpose, and uses bullet points and code examples for patterns. Every sentence earns its place: it includes a prerequisite, alternatives, and multiple usage patterns without redundancy. Length is justified by the complexity of the tool.

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 full schema coverage and no output schema, the description is quite complete: it covers required prerequisites, alternatives, combinable options, and conditional gates. It lacks details on error handling or exact return values, but for a create operation this is acceptable. It provides enough context for an agent to use the tool correctly.

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% and each parameter already has a description, setting a baseline of 3. However, the description goes beyond the schema by providing concrete usage patterns (e.g., 'steps=[{grader_id: "abc"}]', combine='weighted_average', weights=[0.6,0.4], condition with check_grader_id and else_value) that illustrate how the parameters interact. This adds meaningful value, so a 4 is appropriate.

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 creates an evaluator pipeline, specifies it's V2 and Blockly-compatible, and explicitly differentiates it from create_workflow by stating 'Use this, NOT create_workflow, when wrapping graders into evaluators.' It names the resource and the exact action, leaving no ambiguity.

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?

Explicitly provides a usage sequence: 'Use this AFTER creating + committing a grader with create_evaluator + commit_evaluator.' It also gives clear exclusion guidance: 'Use this, NOT create_workflow' for wrapping graders, and includes examples for common patterns (single, average, weighted, condition), covering both when and when-not to use.

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