social_summary

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

With no annotations, the description carries the full behavioral burden and covers it well: no auth/non-gated access, served from cache, no per-request AI cost, and ~5min caching. It also discloses that AI insight text is excluded unless a subscription is held. It does not mention response envelope or rate limits, but for a simple cached public summary the key operational traits are present.

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 front-loaded and informative, but it contains redundancy: 'Non-gated social sentiment summary: the aggregate market-mood score/label plus the top 5 tokens' largely repeats the first clause, and 'Cached ~5min' reiterates 'served from cache.' The content is valuable, but the structure is slightly bloated and could be tightened.

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 zero-parameter tool with no output schema, the description is practically complete: it states the returned data (sentiment score/label plus top 5 tokens), what is excluded (AI insight text), access requirements (non-gated), caching behavior, and the sibling tool for time-series needs. An agent has enough context to select and call this tool correctly.

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 tool has zero parameters and an empty input schema, so the description has no parameter burden to carry; the baseline of 4 applies. It still clarifies what the output contains and that no authentication is needed, which is sufficient context for invocation.

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?

Description opens with a specific verb and resource: 'Get aggregate market mood — overall sentiment score/label + top 5 tokens.' It clearly distinguishes itself from sentiment_history by stating that per-token time-series belongs there, and explicitly notes that AI insight text is excluded. The purpose is unambiguous even without reading the schema.

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 explicitly names sentiment_history as the alternative for per-token time-series, giving a clear when-to-use condition. It also notes that full per-token AI insights require a Max Alpha subscription, which tells agents when this free, cached summary is the appropriate choice. Access and cost expectations are clearly stated.

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