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save_filing

Idempotent

Save a set of figures to the user's account, or update a saved one by passing its id from list_saved_filings. Figures in major units. The filing is saved even when validation finds problems, because a work in progress is worth keeping, and the problems come back in the response so you can raise them.

Input Schema

NameRequiredDescriptionDefault
idNoOmit to create. Pass an id from list_saved_filings to update that filing.
labelNoA name for the filing, e.g. "SparkGames year to 31 Dec 2025".
figuresYesThe figures behind a small-company balance sheet. ALL amounts in major units.
identifiersNoRegister identifiers, e.g. {"companyNumber": "15379140"}. Tax references (UTR, EIN, TFN) are never stored and are silently dropped.
jurisdictionYesGB
categoryTotalsNoWhere the figures came from, when a bank statement fed them: signed major-unit totals per category code from categorise_transactions.

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?

With readOnlyHint=false, destructiveHint=false and idempotentHint=true already supplied, the description still adds real behavioural value: validation problems do not block the save, and those problems are returned in the response rather than thrown. That persistence-of-invalid-data trait is exactly the kind of thing annotations cannot convey.

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?

Three sentences, front-loaded with what the tool does before the behavioural rationale. The closing clause ('because a work in progress is worth keeping, and the problems come back in the response so you can raise them') is slightly long but each clause carries distinct information.

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 mutation tool with no output schema, the description compensates by describing what comes back on validation failure, and the required parameters are well covered. Auth/account scoping is only implied ('the user's account') rather than spelled out, 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 83%, so the field-level semantics (including id, identifiers and categoryTotals) are already carried by the schema. The description's 'Figures in major units' constraint is valuable but is duplicated verbatim in the figures object description, so it adds little beyond structured data.

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 first sentence names a specific verb and resource ('Save a set of figures') and immediately disambiguates the create-vs-update semantics, pointing to list_saved_filings as the id source. An agent knows exactly what this tool does and which sibling supplies the input for the update path.

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?

It clearly states the condition for the update path ('passing its id from list_saved_filings') versus omitting the id to create. It gives no exclusion guidance against neighbours such as check_accounts or explain_accounts, so the routing story is good but not exhaustive.

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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