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generate_derivation_report

Create a Markdown derivation report from a problem statement, given parameters, steps, and results, with optional verification.

Instructions

    Generate a complete derivation report in Markdown.

    Args:
        problem: Problem description
        given: Given parameters {"symbol": "value with unit"}
        steps: Derivation steps
        results: Final results {"symbol": "expression"}
        verification: Optional verification status

    Returns:
        Markdown report
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
givenYes
stepsYes
problemYes
resultsYes
verificationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the burden of behavioral disclosure. It only states the tool generates a report and lists arguments, without mentioning side effects, read-only nature, or any constraints. This is insufficient for an agent to understand operational implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the purpose and return value clearly front-loaded. The parameter listing is efficient, though the docstring format uses minimal elaboration. No redundant information is present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of 5 parameters including nested objects, the description provides basic coverage. The existence of an output schema partially compensates for missing return details. However, optional verification semantics and step format are not fully explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description's parameter summaries add value. For example, 'Given parameters {"symbol": "value with unit"}' provides semantic context beyond the schema's generic object type. However, details like step structure or verification semantics remain vague.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a derivation report in Markdown. It specifies the verb 'generate' and the resource type. However, it does not explicitly differentiate from sibling generation tools like generate_latex_derivation, relying on the Markdown output format for distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as generate_latex_derivation or session_get_steps. There are no prerequisites, context hints, or exclusions mentioned, leaving the agent without decision support.

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

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