report_feedback

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

Annotations indicate idempotentHint and non-destructive. The description adds that reports land in 'Graham's inbox' and feed the roadmap, but doesn't clarify idempotency implications (e.g., duplicate submissions) or other behaviors like rate limits, leaving some gaps beyond annotations.

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 concise and well-structured: a purpose sentence, usage guidance, then an Args list. All sentences are relevant and front-loaded. No unnecessary words.

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 the tool's simplicity and presence of an output schema, the description covers the feedback destination and parameter roles. It lacks details on validation (e.g., endpoint format) or repeat submission handling, but is largely sufficient.

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?

With 0% schema coverage, the description's Args section fully explains each parameter: message (required, free-text), endpoint (optional API endpoint), symbol (ticker), and severity with explicit enum values. This adds essential meaning beyond the schema's bare titles.

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's purpose: 'File an error or improvement suggestion to Chart Library.' It contrasts with sibling analytical tools by being specifically for feedback, making it easy for an agent to distinguish.

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?

Provides explicit usage cues: 'Use this when something looks wrong... or when you spot a missing capability.' While it doesn't list alternatives or exclusions, the context and sibling names imply it's not for data queries, which is adequate for guidance.

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