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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Search Published Reports

search_reports
Read-onlyIdempotent

Search the catalog of published research reports. All listings are free to read. Filters: free-text (matches title + abstract), ticker, report_type. Sort: newest (default) or oldest. Tier-gated: callers only see reports their plan tier can read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNonewest
limitNo
queryNoFree-text query over title + abstract (case-insensitive).
cursorNo
tickerNoFilter to a single subject ticker.
report_typeNoFilter by report type.
price_max_centsNoReserved for future paid listings; currently ignored (all reports are free).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
reportsYes
next_cursorYes

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety. The description adds context about free listings, tier-gating, and available filters, which is useful beyond annotations. However, it does not explain pagination behavior (cursor) or result limits.

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

Conciseness5/5

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

The description is three sentences with no wasted words. The first sentence immediately states the purpose, followed by a key fact (free) and then a concise list of features. It is front-loaded and efficient.

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

Completeness4/5

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

Given the tool's complexity (7 parameters) and the presence of an output schema, the description covers the essential aspects: purpose, filters, sort, and access control. It omits details about pagination and the ignored price_max_cents parameter, but overall it is reasonably complete.

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?

Schema description coverage is 57%, and the description adds meaning by summarizing filters (free-text, ticker, report_type) and sort options. It reinforces the schema's query parameter description and adds context about tier-gating but does not cover all parameters (e.g., limit, cursor) in detail.

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 description clearly states the tool searches the catalog of published research reports, with a specific verb and resource. It distinguishes from siblings like get_report (single report) and list_my_reports (personal), providing unique value.

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

Usage Guidelines4/5

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

The description gives clear context on when to use this tool—for searching reports with filters and sort—but does not explicitly exclude alternatives or note when not to use it. It implies usage through filter descriptions.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool has a distinct purpose with detailed descriptions that clarify differences. Overlaps like get_peer_comparables vs screen_universe are well-differentiated by scope (single company vs cross-sectional). Similarly, get_insider_sentiment vs get_smart_money_flow are clearly distinguished by data sources and methodology.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., create_report, get_financial_ratios, delete_alert). No mixing of conventions or inconsistent verbs.

Tool Count2/5

With 69 tools, the count far exceeds the 25+ threshold for 'too many'. While the domain is broad, the sheer volume likely overwhelms agents and increases selection complexity.

Completeness4/5

The tool set covers a wide range of SEC filings, ratios, smart-money data, alerts, reports, and more. Minor gaps exist (e.g., no options or detailed debt data), but most analyst workflows are supported.