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sec_report_list

Read-only

Use to discover which SEC filings exist for a ticker before searching content. For the actual content use sec_report_search instead.

List indexed SEC filings for a given ticker with a summary header.

Returns: summary (period coverage, per-type counts) + table of up to 50 filings (fiscal_year, fiscal_quarter, filing_type, filing_date, period_start, period_end).

filing_types filter: omit for main reports only (US 10-K/10-Q/20-F/S-1/DEF 14A

  • /A amendments; JP 120/140/160; HK/A-share annual_report / quarterly_report / q1_report; KR A001/A002/A003 + C001/C005; excludes ad-hoc 8-K/6-K); pass [] for all indexed types; pass explicit allowlist to override.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker, e.g. NVDA, 6758.T, 00700.HK, 600519.SH
filing_typesNoFilter by filing type. Omit for default (periodic reports + IPO/shelf registrations + amendments; excludes ad-hoc disclosures). Pass [] for all indexed types. Pass an explicit allowlist to override — use values from the `filing_type` column of a prior unfiltered call.

TDQS

A5/5.0
Behavior5/5

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

The description discloses return structure (summary + up to 50 filings with fields), the default filtering behavior, and what types are included/excluded. This goes well beyond the annotations (readOnlyHint true, destructiveHint false) and provides meaningful context about operational behavior and output 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 well-structured: purpose first, then return format, then filter semantics. It is slightly lengthy, but every sentence carries necessary information—no fluff or redundancy. The clear bullet-like layout of returned fields and filter options improves scannability.

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?

Given there is no output schema, the description fully compensates by listing the exact fields returned and the summary content. It covers purpose, usage, output, and filter semantics, making it complete for an agent to select and invoke the tool correctly in most cases.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant semantics beyond the schema: it explains the default filing_types behavior, how to override with [], and the explicit allowlist option. It also specifies ticker examples in the schema, and the description reinforces the role of the ticker parameter in context.

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's function: 'List indexed SEC filings for a given ticker with a summary header.' It uses a specific verb ('List') and identifies the resource (SEC filings for a ticker), and explicitly distinguishes it from the sibling tool sec_report_search ('For the actual content use sec_report_search instead').

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 provides explicit guidance on when to use this tool ('before searching content') and names the alternative for content search. It also explains the filing_types filter behavior with clear options (omit, [], explicit allowlist), which is practical usage guidance beyond simple when-to-use.

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

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: company_search is qualitative discovery, run_sql is quantitative querying, news_search covers news, sec_report_list/search handle filings, ticker_lookup resolves identifiers, and list_tables/get_table_schema/fiscal_utility support exploration. Cross-references between tools (e.g., company_search explicitly defers to run_sql) prevent confusion.

Naming Consistency4/5

Most tools follow a predictable noun_verb or noun_noun pattern (company_search, news_search, ticker_lookup, run_sql, list_tables, get_table_schema). sec_report_list and sec_report_search are clearly related with descriptive suffixes. Minor deviation: fiscal_utility is vaguer than its siblings, but the pattern is otherwise consistent.

Tool Count5/5

9 tools is right-sized for a financial data platform — enough for comprehensive coverage (search, query, schema, news, filings) without redundancy. Each tool serves a distinct purpose and the count fits the domain well.

Completeness5/5

The tool set forms a coherent workflow: ticker_lookup → company_search/run_sql for fundamentals, news_search for events, sec_report_list/search for filings, and list_tables/get_table_schema for schema discovery. The only minor gap is the absence of a direct 'company profiles' tool separate from company_search, but run_sql covers quantitative needs adequately. The surface is complete for a read-only financial analysis MCP.