fear_greed_monthly

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

With no annotations provided, the description carries the full burden of disclosure — and it delivers richly: never deleted/grows indefinitely, months with fewer than 20 daily records excluded, no authentication required, 60 req/min rate limit, 5-min cache, and the aggregation-from-purged-snapshots behavior. This goes well beyond a minimal description.

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?

Well front-loaded: the purpose label opens the description, followed by the precise definition, then retention, field list, filtering rule, and operational constraints. Every sentence carries distinct information — the field list with value ranges, the exclusion threshold, rate limit, and cache all earn their place.

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 annotations and no output schema, the description fully substitutes for the missing structured data: it enumerates every returned field, the dominantClassification enum, the 20-record exclusion rule, and operational limits. Nothing an agent needs to call and interpret this tool correctly is missing.

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 takes zero parameters, so the schema leaves nothing undocumented and the description has no input semantics to clarify; baseline 4 applies. The field enumeration (avgScore, minScore, maxScore, dominantClassification, fearDays, etc.) actually adds value by previewing what the tool returns despite not being input-related.

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?

States a specific verb and resource: 'Returns the permanent monthly archive of the Fear & Greed index — one row per calendar month.' The 'permanent monthly archive' and monthly-granularity phrasing clearly distinguish it from siblings like fear_greed (current state) and fear_greed_history (historical series), so an agent can tell them apart from the description alone.

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 clear use-case context: 'providing AI agents with macro sentiment context across months and years' and explains the aggregation rationale ('aggregated from daily snapshots before they are purged'), which signals this is the long-term archive tool rather than a live/daily one. However, it never names alternatives explicitly or states when-not-to-use, leaving sibling routing partially to inference.

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