Every fund matching some filters, largest first, each with its net assets and the source and date that figure came from. Use for "find me all X" questions rather than repeated searches. Fees are percentages, not basis points. Funds with no published size are set aside from a size filter and counted in no_size_figure rather than treated as small.
| Name | Required | Description | Default |
|---|---|---|---|
| desk | No | ||
| limit | No | ||
| issuer | No | ||
| max_fee_pct | No | ||
| min_assets_usd | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses ordering ('largest first'), output provenance (source and date of the size figure), fee unit semantics, and the special handling of funds with no published size. Minor gaps remain around how limit interacts with 'every fund' and what desk filtering means.
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?
Three dense, front-loaded sentences: core behavior first, usage trigger second, then two critical data semantics. Every sentence earns its place and there is no filler.
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?
Given no output schema and no annotations, the description does substantial work: it covers output composition, ordering, units, and a tricky null-size edge case. The remaining ambiguity around limit and desk keeps it from being fully complete, but an agent can likely invoke it correctly with this information.
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 0%, and the description compensates for some parameters: 'Fees are percentages, not basis points' clarifies max_fee_pct, and the no_size_figure behavior clarifies min_assets_usd. However, desk, issuer, and limit are not addressed in the description, leaving a meaningful portion of the parameter semantics underspecified.
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 clearly states the tool returns 'every fund matching some filters, largest first' with net assets and source/date, which is a specific screening behavior. It contrasts with 'repeated searches' but doesn't name sibling tools like etf_search, so sibling differentiation is implicit rather than explicit.
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?
It explicitly tells agents to use this tool for 'find me all X' questions rather than repeated searches, which is a clear usage trigger. It doesn't enumerate when to prefer alternatives like etf_search or etf_holdings, so it stops short of a full when-to-use/when-not-to-use map.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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