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OptimistFi

search_filings

Read-only

Full-text search across every SEC filing since 2001 — which companies discuss something.

query: a phrase; wrap in double quotes for an exact match. forms: e.g. "10-K" or "8-K".
start/end: ISO dates. Cheap — metadata and a direct document URL, not the filing body; use
get_filing_text to read one.
Each hit is a SCHEMA §2 envelope whose entity carries the filer's TICKER and CIK, so a search
result feeds straight into get_fundamentals, get_filings(kind="events") or get_overview without a second
lookup — "who discusses X, and are any of them real businesses" is one chain.
Matching is EXACT-PHRASE and does not stem or synonymise, so a near-miss phrase returns
nothing; an empty result says which filters were applied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
formsNo
limitNo
queryYes
startNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that matching is EXACT-PHRASE and does not stem or synonymise, that it is cheap, that empty results indicate applied filters, and that each hit is a SCHEMA §2 envelope with TICKER and CIK. These are non-obvious behavioral traits an agent needs to interpret results correctly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose, followed by parameter guidance and key caveats. It is longer than strictly necessary, but the extra sentences about exact matching, cost, and downstream chaining all add useful operational context rather than filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers scope, exact matching behavior, result shape, downstream chaining, empty-result semantics, and cost. With the read-only annotation and an output schema present, there is no missing category an agent needs to select and invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description compensates by explaining query as a phrase that can be double-quoted for exact match, giving forms examples like '10-K' or '8-K', and specifying that start/end are ISO dates. It does not explicitly explain the limit parameter, but the default and intuitive meaning reduce the gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening line, 'Full-text search across every SEC filing since 2001 — which companies discuss something,' gives a specific verb, resource, and purpose. It clearly differentiates this from siblings like get_filings, get_filing_text, and search_trends.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly tells the agent this returns only metadata and a URL, 'not the filing body; use get_filing_text to read one.' It also explains exact-phrase matching and shows how results chain into get_fundamentals, get_filings(kind='events'), and get_overview, giving concrete when-to-use context.

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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