Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Save Figure Review

save_figure_review

Idempotent

Record (or update) the review state of ONE figure inside a report — the durable answer to 'has a human traced this number back to its filing?' Upsert keyed on (report_id, figure_key): re-reviewing a figure REPLACES its prior mark, it never appends, so this is always the figure's current state, never a history. figure_key is an opaque id you mint yourself for one figure — for a dataset-backed figure use fact:{fact_id}#{figure}, where {figure} is the number as the report writes it, lowercased and whitespace-collapsed (e.g. fact:f_rev#$402.83b). The value matters: one fact can back two numbers in one sentence, and a key carrying only the fact_id makes one verdict cover both. Reuse the exact same key to update that figure's review later. state: verified (traced and correct) | corrected (wrong — supply corrected_value) | external (legitimately not from Valuein data) | rejected (unsupported, should be removed). corrected_value is REQUIRED when state='corrected' and must be omitted otherwise. Owner-scoped — your reviews never leak to or from another user. Tier: sp500+ (sample rejected).

Input Schema

TableJSON Schema

Name	Required	Description
`note`	No	Optional free-text reviewer note (e.g. what was checked, or why it was rejected).
`state`	Yes	verified = traced to its filing and correct. corrected = wrong (supply corrected_value). external = legitimately not from Valuein data (analyst's own source). rejected = unsupported, should be removed from the report.
`report_id`	Yes	Identifier of the report the figure belongs to, as returned by create_report / list_my_reports / save_freeform_report.
`figure_key`	Yes	Opaque id you mint for one figure inside the report. Never parsed or validated beyond length — use the exact same key to update this figure's review later. Shape for a dataset-backed figure: 'fact:{fact_id}#{figure}', the figure lowercased and whitespace-collapsed as the report writes it ('fact:f_rev#$402.83b'); the Workspace mints 'raw:{hash}' for a figure with no fact, which only it can compute.
`corrected_value`	No	The correct value. REQUIRED when state='corrected'; must be omitted for every other state (a corrected_value on a non-corrected review is rejected).

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`review`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 18, 2026

changedOutput schema / properties / _meta / properties / fundamentals_as_of / description

Previous value: -"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to."New value: +"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt in bulk. Use THIS — not `last_updated` — when telling a user how current the cross-sectional fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to. It is a floor for a single filer, not a ceiling: a filer with a live partition receives its filing, facts and ratios intraday (minutes after EDGAR dissemination), so an entity-scoped read may carry a filing newer than this; cross-sectional ranks (factor scores, earnings signals) refresh with the weekly bulk export."

Changed1 schema field changedSep 16, 2026

changedInput schema / properties / figure_key / description

Previous value: -"Opaque id you mint for one figure inside the report. Never parsed or validated beyond length — use the exact same key to update this figure's review later. Common shapes: 'fact:{fact_id}' for a dataset-backed figure, 'raw:{hash}' for free-text prose."New value: +"Opaque id you mint for one figure inside the report. Never parsed or validated beyond length — use the exact same key to update this figure's review later. Shape for a dataset-backed figure: 'fact:{fact_id}#{figure}', the figure lowercased and whitespace-collapsed as the report writes it ('fact:f_rev#$402.83b'); the Workspace mints 'raw:{hash}' for a figure with no fact, which only it can compute."

AddedAug 2, 2026

TDQS

A4.8/5.0

Behavior5/5

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

The description adds significant behavioral context beyond the annotations: re-reviewing replaces the prior mark, never appends, so no history is kept; reviews are owner-scoped; and the tool rejects sample accounts. These behaviors are not visible in the annotations and materially affect how an agent should call the tool.

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 long but every sentence carries necessary information: core behavior, key semantics, state values, conditional requirements, and access constraints. The most important use-case is front-loaded, and there is no filler.

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?

For a tool with five parameters, an enum state, conditional requirements, and an upsert model, the description is complete. It covers figure_key design, state meaning, corrected_value rules, owner isolation, and tier restrictions. An output schema exists, so return-value details are not needed here.

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?

Although schema coverage is 100%, the description substantially enriches parameter understanding. It explains how to mint figure_key, gives concrete examples (e.g. 'fact:f_rev#$402.83b'), explains why key granularity matters, and clarifies the conditional requirement for corrected_value. This guidance exceeds what the schema alone provides.

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 and resource: 'Record (or update) the review state of ONE figure inside a report.' It also names the durable question this tool answers, distinguishing it from related read/verification tools. This goes well beyond the title.

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: use this to save or update the current review state of a figure, with explicit notes on upsert behavior and owner-scoping. It does not explicitly name alternatives or state when not to use this tool, but the intended context is unambiguous.

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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