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Get Certified SEC Valuation Pack

valuation_inputs
Read-only

Access certified SEC valuation inputs from 12 packs, including DCF and quality of earnings, by company ticker.

Instructions

Certified SEC/EDGAR valuation inputs pack (12 packs including dcf_valuation_inputs historical FCF). Not market EV, P/E, trading DCF, or macro gauges (Buffett Indicator / CAPE).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packYesCertified SEC valuation pack ID (equity_screen, ev_bridge, quality_of_earnings, segment_mix, returns_screen, leverage_screen, piotroski_f, altman_z_prime, beneish_m_score, dupont_5step, working_capital_efficiency, dcf_valuation_inputs)
periodNoOptional reporting period, e.g. FY2023, Q3 FY2023. Defaults to FY2023 if omitted.
companyYesCompany ticker or name, e.g. AAPL, TSLA, MSFT
low_tokensNoOptional. When true, returns compact JSON schema.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesList of MCP output blocks containing verified SEC fact payload or SAFE_REFUSAL
Behavior4/5

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

Annotations already provide readOnlyHint=true, so the tool is known as a read operation. The description adds valuable context about the source (SEC/EDGAR certified) and the content structure ('12 packs including dcf_valuation_inputs'), which goes beyond annotations. No contradictions.

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?

Two concise sentences with front-loaded purpose and clear exclusions. No superfluous words; every sentence adds 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?

With an output schema present, return values are handled. The description covers tool scope, source, exclusions, and content structure. A minor gap is that it doesn't explain why one would choose between the 12 packs, but that is managed by the pack parameter's enum values in the schema.

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 the schema already documents all parameters well. The description does not add additional parameter-level meaning beyond the schema, but that is acceptable given full coverage. Baseline 3 is appropriate.

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 returns a 'Certified SEC/EDGAR valuation inputs pack' with specific scope ('12 packs including dcf_valuation_inputs historical FCF'), distinguishing it from market-based alternatives. The verb is implicit but clear from context ('Get'), and resource is precisely specified.

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?

The description explicitly tells when NOT to use this tool by listing exclusions: 'Not market EV, P/E, trading DCF, or macro gauges (Buffett Indicator / CAPE).' This provides clear boundaries and helps the agent select alternatives among siblings like query_financial_sec or vln_capabilities_overview.

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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