reactome_analyze_identifiers

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

No annotations are provided, so the description bears the burden. It discloses the output (over-represented pathways sorted by p-value) and implies a read-only analysis, but does not discuss error handling, invalid identifiers, or other behavioral traits. It provides some context but lacks depth for a no-annotation tool.

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 two sentences, front-loaded with the main purpose and then the output. Every word earns its place, with no filler or redundancy.

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?

For a straightforward analysis tool with full schema coverage and no output schema, the description adequately states what it returns. It could mention the effect of p_value_threshold or how to interpret results, but it is sufficiently complete for basic use.

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 has 100% coverage with descriptions for all 5 parameters, so the baseline is 3. The description adds marginal value by clarifying that identifiers are gene/protein identifiers, but does not go beyond what the schema already provides for other parameters.

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 performs pathway enrichment analysis on a list of identifiers and returns over-represented pathways sorted by p-value. It uses a specific verb and resource, and distinguishes from the sibling reactome_analyze_identifier by specifying 'list of gene/protein identifiers'.

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 implies usage when you have a list of identifiers and want enrichment analysis, but it does not explicitly mention when to use this over alternatives like reactome_analyze_identifier or other analysis tools. There is no exclusion or alternative naming.

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