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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals key behaviors: data is daily, comes from an alternative-data feed, has a default window of 60 days, and targets a single ticker. However, it does not disclose the output format, pagination, or any filtering constraints beyond scope, which leaves some behavioral ambiguity for a read operation without an output schema.

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 with no redundancy. The first sentence delivers the core function and key parameters, while the second provides targeted usage guidance and points to a complementary tool. Every clause earns its place, making it highly efficient and easy to parse.

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?

This is a simple two-parameter data query with no output schema and no annotations. The description covers the data source, metric, default window, single-ticker scope, and usage context, which is sufficient for a basic retrieval tool. It falls short only in not describing the exact return shape or any edge cases like holiday handling or data lag, which would be valuable given the absence of an output schema.

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 schema documents ticker (with a minimal path-parameter note) and limit (with default/min/max), but only 50% of parameters have meaningful descriptions. The tool description compensates by explaining 'default 60 days' for the limit parameter and 'for one ticker' for the ticker parameter, adding context beyond the bare schema. It does not, however, clarify ticker format or how limit translates to days beyond the default.

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 explicitly states the tool provides 'Daily r/wallstreetbets mention count and sentiment for one ticker from the alternative-data feed'. This clearly identifies the data source, the metric, the unit of analysis, and the time window. It also distinguishes itself from related tools by naming tengu_v3_intel_twitter as the complementary source, leaving no ambiguity about its purpose.

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 provides explicit when-to-use guidance: 'Call this when the user asks whether retail is piling into a name or how retail buzz is trending'. It also names a specific alternative/complement (tengu_v3_intel_twitter) and explains how to combine them. The 'for one ticker' constraint implies a boundary (not for multi-ticker or alternative sources), making the usage context clear.

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