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Signal Ledger Financial Intelligence

Financial Report Risk Analysis / 财报风险体检

analyze_financial_report_risk
Read-onlyIdempotent

Paid full audit ($0.25 USDC): analyze financial-statement risk, earnings quality, cash-flow anomalies, accounting red flags, debt pressure, governance issues and data quality. Supply report text, or provide a US stock symbol to retrieve an official SEC filing automatically. Returns evidence-linked, machine-readable risk findings. / 收费完整体检(0.25 USDC):识别财报风险、盈利质量、现金流异常、会计红旗、偿债压力、治理与数据质量问题;可提交原文,也可只提供美股代码自动获取 SEC 原始公告。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoOptional explicit mode. It is inferred from report_text or symbol when omitted.
periodNolatest, 2025/FY2025, 2025-Q4 or YYYY-MM-DD.latest
symbolNoUS-listed ticker symbol, for example AAPL or BRK.B. The service fetches an official filing.
companyNoOptional company name for text mode.
report_textNoPlain text from a financial statement, annual report, quarterly report, SEC 10-K, 10-Q or 8-K filing.
report_typeNoPreferred filing/report type for symbol mode.10-K
source_contextNoOptional provenance metadata for caller-supplied text.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
modeNo
toolNo
errorNo
analysisNo
scorecardNo
request_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context beyond this: the tool is paid ($0.25 USDC), it automatically fetches SEC filings for symbol input, and it returns evidence-linked, machine-readable risk findings. There is no contradiction with annotations.

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 the most critical information (paid cost, purpose) and then efficiently covers input modes and output characteristics. The bilingual content doubles the length but is a deliberate localization choice rather than filler; each sentence in both languages carries meaning without redundancy within a language.

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 rich schema with fully documented parameters and an explicit output schema, the description needs only to supply operational context. It covers cost, input options, automatic SEC retrieval, and the nature of the output (evidence-linked, machine-readable). No critical missing information prevents an agent from invoking the tool correctly.

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?

The input schema provides descriptions for all 7 parameters (100% coverage), so the baseline is 3. The description reaffirms the two key input options (report_text and symbol) but does not add significant meaning beyond the schema's own guidance, which already states these modes. Other parameters (period, report_type, source_context, etc.) are fully documented in the 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?

The description opens with a specific verb ('analyze') and a clear resource ('financial-statement risk'), then enumerates concrete risk dimensions (earnings quality, cash-flow anomalies, accounting red flags, debt pressure, governance, data quality). This leaves no ambiguity about what the tool does, and it is clearly distinct from the sibling get_author_track_record, which deals with author reputations rather than financial reports.

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 explicitly states the two valid input modes: supply report text, or provide a US stock symbol to trigger automatic SEC filing retrieval. It gives clear context for how to use the tool, though it does not explicitly discuss 'when not to use' or compare alternatives. Since the only sibling is unrelated, this is not a significant gap.

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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