fahali_get_market_mood

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description still adds real behavioral detail: unreadable measures return null with a reason rather than a fabricated neutral 50, and each fact is ranked against its own history. It does not discuss the response envelope or pagination, which keeps it below a 5.

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 core definition is front-loaded in the first sentence, and the ranking/null semantics follow logically. The closing pair 'A description, not a forecast or a grade. Observation, not advice.' is somewhat redundant with itself, costing a little density but still serving as a disambiguation guard.

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?

An output schema exists, so return shape needn't be described, and the description still covers the one thing an agent could misread — that nulls mean unreadable, not neutral — plus the `ranked` companion field. What's missing is guidance on how detail/limit interact with the response, though the schema already covers that.

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?

Schema description coverage is 100%, so limit, since, detail, symbols, and include_withheld are already fully documented in the schema. The description mentions the `ranked` output field but says nothing about any of the five input parameters, so it adds no parameter-level meaning. Baseline 3 is correct.

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 opening clause states a specific resource (fear/greed score, 0-100) with scope (US stocks and crypto separately) and even lists the underlying measures. It implicitly differentiates from siblings via 'not a forecast or a grade,' which contrasts with fahali_get_forecast and fahali_get_market_verdict, but never names an alternative outright.

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?

'A description, not a forecast or a grade. Observation, not advice.' implies the tool is for descriptive sentiment context rather than predictive calls, but there is no explicit when-to-use statement, no prerequisites, and no named sibling to route to. The agent must infer the selection rule.

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