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

With only readOnlyHint=true in annotations, the description carries the behavioral burden well: it discloses the return verdict taxonomy, the edge-case verdicts (insufficient_13f_coverage / insufficient_history, 'never coerced to neutral'), that the output is derived with no per-fund rows, and the data source (SEC EDGAR 13F-HR + Form 4). It also notes FREE access with no tier gate or AI metering, which is meaningful operational context.

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?

Front-loads the purpose, then layers return shape, derivation semantics, sibling relationships, and access terms in dense, earning sentences. No repetition or filler, and the most important distinction (derived, not raw) appears early.

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?

With no output schema, the description fully compensates by enumerating the return fields (verdict, institutional, insider, cluster, coverage, summary) and the verdict values. For a one-param read tool, an agent has everything needed to decide and invoke 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?

There is a single required parameter (ticker) with 100% schema description coverage, so the schema already documents it. The phrase 'for one ticker' reaffirms the scope but adds no format or edge-case detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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+resource+scope: a quarter-aligned, derived institutional-confluence read for a single ticker fusing 13F accumulation, insider Form 4 net buying, and buy-cluster confirmation. It explicitly declares it is a DERIVED verdict rather than raw data ('no per-fund rows'), which cleanly separates it from siblings like get_institutional_holders and ol_insider_cluster_scan.

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?

Names the related tools it pairs with (get_institutional_holders, ol_insider_cluster_scan) and makes clear this is the fused/derived alternative to raw-data tools. However, it stops short of an explicit 'use this when... instead of...' rule; the selection logic is inferred from the derived-vs-raw distinction rather than spelled out.

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