get_species_production_contributors

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

No annotations are provided, so the description must convey behavioral traits. It states the tool identifies production/consumption reactions but does not mention side effects, permissions, or constraints beyond the limit parameter. The description is adequate but not exhaustive.

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 three sentences: purpose, examples, and prerequisite. It is concise, front-loaded with the core action, and contains no superfluous 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 that an output schema exists (per context signals), the description does not need to detail return values. It covers the tool's purpose, usage context, and a key prerequisite, making it sufficiently complete for an agent.

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?

The input schema provides detailed descriptions for all parameters, covering name, species, and limit. The description adds valuable context by linking the 'name' parameter to a mixture created via create_lab_mixture, enhancing 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 clearly identifies the tool's function: identifying reactions that create or consume a specific species. The examples ('Where is the NO coming from?') provide concrete use cases, and the tool is distinct from siblings like get_species_properties.

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 states a critical prerequisite ('mixture must first be created using create_lab_mixture') and frames usage for pathway analysis with example questions. It does not explicitly exclude scenarios, but the context is clear.

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