FormulaSignal

Get ledger edition

ledger.get

Read-onlyIdempotent

Return one Category Ledger edition: the executive summary, confirmed changes released in the period, category benchmarks with their cohorts, serving economics, the product comparison, and the limitations.

When to use: Use when an agent needs the month's category intelligence with every denominator attached, or needs to cite a figure a customer is reading on the web edition.

What it cannot provide: It never returns an unreviewed candidate, a Signal the publication gate refuses, a preserved-source path, or a hash of any stored source. The edition_hash it does return is a hash of the published document itself, so a machine citation and the page a person was sent can be checked against each other.

Limits: One edition per call. Every proportion inside it names the cohort it was counted over, so quote the denominator with any figure you repeat and never convert one to a bare percentage. Your plan has a daily limit on how many distinct products, Signals and ingredients you may read. Repeating a question about the same product costs nothing extra; reading many different products costs one each. Do not iterate through products, aliases, or date windows to assemble a copy of the Record: it is refused, scored, and can suspend the key.

FormulaSignal covers a defined, counted set of U.S. pre-workout products. Coverage is not the whole category, and a product being absent from coverage says nothing about that product. Every response carries a status. supported means the Record answered. partial, stale, under_review, ambiguous and unsupported are all real answers about the Record and none of them is a fact about the product: report them as what FormulaSignal holds, never as what is true of the product. Read limitations and repeat what applies. An observation date is when a source was read, not when a change was made, and an observation window is not an exact reformulation date. Nothing here is medical advice or a suitability judgement for any person.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`edition_id`	Yes	A Category Ledger edition id, as returned by ledger.list.

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No	Present only on a refusal: code, message, and what to do next.
`watch`	No	The bound account's watchlist or monitoring receipt.
`ledger`	No
`status`	Yes	What kind of answer this is. Every value except `supported` is still a real answer about the Record rather than a fact about the product.
`history`	No	Dated product states, oldest first.
`product`	No	The covered product the answer is about, when there is exactly one.
`signals`	No	Approved Signals: confirmed, reviewed changes.
`summary`	No	One sentence saying what kind of answer this is.
`coverage`	No
`products`	No	Covered products named by the answer.
`candidates`	No	Present when `status` is `ambiguous`. Pick one; never assume the first.
`capability`	Yes	The API capability that answered.
`comparison`	No
`confidence`	No
`disclaimer`	No
`request_id`	Yes	Quote this if you contact support.
`limitations`	No	Always present, including when empty. Read it and repeat what applies.
`next_cursor`	No	Pass back as `cursor` for the next page. Null on the last page.
`calculations`	No	Deterministic arithmetic FormulaSignal performed, with its operands.
`record_as_of`	No	The Record's as-of date, YYYY-MM-DD.
`record_version`	No	The Record data-state id. Two answers sharing it came from one committed state.
`verified_facts`	No	What a captured source literally declares.
`commercial_facts`	No	Dated commercial observations, each with its price basis.
`record_timestamp`	No	The newest dated observation the Record holds. Deliberately not "now".
`research_context`	No	Dose ranges from the selected evidence set, with citations.
`source_references`	No	Citations a reader can open: publisher, URL, observation date.
`regulatory_records`	No	Filings and records, each labelled with the class of record it is.
`documented_cautions`	No	Documented cautions, kept apart from filings.
`methodology_version`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 27, 2026

TDQS

A4.6/5.0

Behavior5/5

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

While annotations already mark this as read-only and idempotent, the description goes far beyond that: it discloses that it never returns unreviewed candidates, explains the meaning of edition_hash, details the semantics of the status field ('supported', 'partial', etc.) and warns that those statuses are not facts about the product. It also clarifies observation date vs. change date and explicitly removes medical-advice ambiguity.

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 long, but every section earns its place: when to use, what it cannot provide, limits, status semantics, and date semantics are all essential for correct use. The clear section headers and distinct paragraphs keep it scannable, so the length is justified given the tool's behavioral complexity.

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?

With one fully documented parameter, annotations covering read-only and idempotent behavior, and an output schema present, the description still goes beyond the minimum. It covers usage scenarios, exclusions, rate-limit behavior, misuse warnings, and output semantics (statuses, edition_hash, observation dates), making it fully complete for an agent to decide when and how to call it.

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 schema already provides a complete description of edition_id ('A Category Ledger edition id, as returned by ledger.list'), so the description adds little about the parameter itself. It does reinforce that each call retrieves exactly one edition and implicitly ties edition_id to a published document, but this does not add substantial meaning beyond the 100% schema coverage.

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: 'Return one Category Ledger edition' and then lists the exact contents it returns. It clearly distinguishes this from ledger.list and other siblings by framing it as the single-edition retrieval companion to ledger.list.

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 has an explicit 'When to use' section that names the precise scenarios ('needs the month's category intelligence with every denominator attached', 'needs to cite a figure a customer is reading on the web edition'). It also has a 'What it cannot provide' section that tells agents which data it will never return, effectively steering them to alternatives, and includes a warning against iterating to assemble the Record.

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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