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Kabuken

by io.github.Intellics-ai
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Get filing text

get_filing_text
Read-only

If a call is not available for this account, get_account_quota shows what this account can access. Return narrative sections of a Japanese annual securities report (有価証券報告書) as filed, in Japanese and without AI processing: business_risks (事業等のリスク) and md_and_a (経営者による財政状態、経営成績及びキャッシュ・フローの状況の分析). Pass entity_code for the newest annual report that has XBRL data, or doc_id for a specific filing. Long text is paged by characters; send next_cursor to continue. Sections not stored for the filing are listed in missing_sections. Text is reproduced verbatim from the filing; the filing company holds the rights to its text. Takedown requests: https://kabuken.intellics.ai/support Source: EDINET (https://disclosure2.edinet-fsa.go.jp/), PDL 1.0 (https://www.digital.go.jp/resources/open_data/public_data_license_v1.0). Data is processed by Kabuken, not raw unprocessed FSA data. Not investment advice.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_filing_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
cursorNoOpaque next_cursor from the previous response; send it with the same entity_code or doc_id and sections to get the next page
doc_idNoEDINET document id of a filing, e.g. S100TR7I. Provide this or entity_code.
sectionsNoSections to return, in order. Default ["business_risks"].
max_charsNoMaximum characters of text per page (1-30000, default 12000)
entity_codeNoEDINET entity code of the company, e.g. E02144. Uses its newest annual report that has XBRL data. Provide this or doc_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive), so the description adds real behavioral value: text is verbatim, paging is character-based with a next_cursor, sections absent from a filing are surfaced in missing_sections, and licensing/takedown terms are noted. No contradictions with annotations; the quota cross-reference sentence is somewhat extraneous but harmless.

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

Conciseness3/5

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

The core mechanics are front-loaded well, but the opening sentence about get_account_quota is a disjointed preamble, and the closing block of source URLs, license names, and 'not investment advice' boilerplate consumes substantial space for little invocation value.

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?

For a read-only retrieval tool with no output schema, the description covers paging, the missing_sections behavior, parameter defaults, and licensing constraints. It does not describe the response envelope (e.g. the field holding the text or the next_cursor), which is the main remaining gap.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter already carries its own documentation. The description restates the entity_code/doc_id selection and cursor continuation, adding little beyond what the schema says, so it lands at the baseline for a fully documented schema.

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?

States a specific verb and resource: returns narrative sections (business_risks, md_and_a) of a Japanese annual securities report verbatim, in Japanese, unprocessed. The 'without AI processing' phrasing implicitly separates it from get_document_summary and get_financial_facts, so an agent can tell what it uniquely produces.

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?

Gives clear selection guidance between the two input modes (entity_code for the newest annual report with XBRL, doc_id for a specific filing) and explains the paging continuation condition. It stops short of naming which sibling to use when the agent wants an AI-summarized or numeric view, leaving that contrast implicit.

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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