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generate_counterpoint

Generate a counterpoint line following species rules. Provide a cantus firmus, choose species (1-5), and set if counterpoint is above or below.

Instructions

Generate a counterpoint line for a cantus firmus.

Creates a counterpoint melody following species rules.

Args: cantus_firmus: List of pitches (e.g., ["C4", "D4", "E4", "F4", "E4", "D4", "C4"]) species: Species number (1-5) above: If True, generate counterpoint above CF; if False, below

Returns: Generated counterpoint with validation results

Examples: - Above CF: generate_counterpoint(["C4", "D4", "E4", "D4", "C4"], species=1, above=True) - Below CF: generate_counterpoint(["C4", "D4", "E4", "D4", "C4"], species=1, above=False)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cantus_firmusYes
speciesNo
aboveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns generated counterpoint with validation results, but does not mention side effects, permissions, or state modification. The behavior is partially transparent but could be more explicit.

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 structured sections (Args, Returns, Examples). It front-loads the core action in the first sentence. Every sentence serves a purpose, though the examples could be slightly condensed.

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 tool has an output schema (though not detailed), the description adequately covers return values. However, it misses prerequisites (e.g., need for a score), error handling, or constraints like species-rule adherence details. It is functional but could benefit from more context.

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

Parameters4/5

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

The input schema has 0% description coverage, but the description compensates well by explaining each parameter: cantus_firmus as a list of pitches in a specific format, species as integer 1-5, and above as boolean. The examples illustrate usage. It adds meaningful context beyond schema types.

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

Purpose5/5

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

The description clearly states the tool generates a counterpoint line for a cantus firmus following species rules. It specifies the resource and action, and the examples help clarify. It is distinct from sibling tools like check_species_rules, which validates rather than generates.

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

Usage Guidelines3/5

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

The description explains what the tool does but provides no guidance on when to use it versus alternatives (e.g., check_species_rules, analyze_chord). It does not include when-not-to-use or prerequisite conditions. The examples hint at usage but lack explicit context.

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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