veroq_social_sentiment

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

No annotations are provided, so the description carries the full burden. It discloses the return structure ('Overall sentiment score, mention count, per-platform breakdown, trending topics, and top posts with URLs'), the data sources ('Reddit, Twitter/X, and other platforms'), and the cost ('30 credits'). However, it does not mention rate limits, error handling, or idempotency. For a simple read tool, this is sufficient.

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 structured with clear sections (WHEN TO USE, RETURNS, COST, EXAMPLE) and the main sentence is front-loaded. It is not overly verbose, though the sections could be condensed into a single paragraph without losing information. Each part adds value.

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 tool with one parameter and no output schema, the description provides a reasonable amount of context: it explains the return data (sentiment score, breakdown, top posts) and cost. It lacks details on possible errors, data freshness, or pagination, but given the simplicity, it is nearly complete.

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% description coverage for the only parameter 'symbol', with an example in the schema description. The tool description repeats the example but adds no new semantic information. Baseline is 3, and the description does not elevate beyond that.

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 function: 'Get social media sentiment for a stock or crypto ticker from Reddit, Twitter/X, and other platforms.' The verb 'get' combined with the specific resource 'social media sentiment' makes the purpose unambiguous. The tool is distinct from siblings like 'veroq_social_trending' which likely focuses on trending topics rather than sentiment.

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 includes a dedicated 'WHEN TO USE' section: 'To gauge retail investor sentiment and social buzz around a specific ticker.' This provides clear context for when the tool is appropriate, but it does not explicitly state when not to use it or mention alternatives (e.g., for earnings data). The guidance is strong but lacks negative cases.

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