schedule-iii

List budgets

list_budgets

Read-only

MANAGEMENT data class. Discover budget ids and versions without identity fields. Locked FX rate and all money-valued fields are decimal strings. Filter status or fiscal-year start before paging. The signed page_token is pinned to the complete filtered source; restart at page 1 if source_changed. This lists budget headers only, not cells, approvals identities, or a recalculated budget.

Input Schema

TableJSON Schema

Name	Required	Description
`status`	No	Optional budget status.
`client_id`	Yes	The entity (client) id — from list_clients.
`page_size`	No	Rows per source-pinned page (default 20, max 50).
`page_token`	No	Signed continuation from the prior page; restart without it if source_changed.
`fiscal_year_start`	No	Optional fiscal-year first-of-month date, e.g. 2026-04-01.

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description adds meaningful behavioral context: money-valued fields are decimal strings, page_token is pinned to the complete filtered source, and restart at page 1 if source_changed. These details are not present in annotations and enrich the agent's understanding.

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?

Four sentences, each carrying distinct information: data class, purpose, data format, pagination, and scope exclusions. The 'MANAGEMENT data class' phrase is somewhat cryptic, but the description is not bloated and front-loads the core purpose.

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 list tool with 5 parameters and no output schema, the description covers purpose, pagination behavior, data format, and exclusions, providing a solid mental model. It does not explicitly describe the full response structure but implies the return contains budget ids and versions, which is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description covers all parameters (100%), but the description adds usage semantics: 'Filter status or fiscal-year start before paging' and explains the page_token's pinning behavior. This goes beyond the schema's individual parameter descriptions.

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?

Description explicitly states 'Discover budget ids and versions' and 'lists budget headers only', clearly identifying the resource (budgets) and action (list/discover). It distinguishes itself from sibling tools like get_budget by scoping to headers only and excluding cells, approvals identities, and recalculated budgets.

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?

Provides clear usage context: filter status or fiscal-year start before paging, and explains page_token pinning with restart guidance if source_changed. It notes what the tool does NOT list, implying alternatives, but does not explicitly name sibling tools like get_budget.

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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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct resource or action — get_* reads, save_* writes, confirm_* approves, preview_* shows consequences before approval. Even the management-data trio (budgets, allocations, variance) is cleanly separated by surface. Two-step flows like preview_chart_rebaseline → confirm_complete_chart are clearly sequenced, so an agent won't confuse the stages.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun pattern: get_* for reads, list_* for discovery, save_* for section writes, confirm_* for approvals, create_* for new entities/centres, preview_* for pre-approval checks. The few one-offs (ingest_upload, upload_trial_balance, set_header_row) still fit the verb-first convention. No camelCase or style mixing.

Tool Count2/5

At 67 tools this is well past the 'too many' threshold. While the Schedule III domain genuinely is broad — statutorily mandated sections, two-phase approval flows, readiness checks, and a separate management-data area — the surface is heavy; an agent will spend real effort just surveying the tool list. Some consolidation of the save_reserves/provisions/assets movements or merging preview+confirm pairs is possible.

Completeness4/5

The surface covers the full lifecycle: upload → mapping/costing → grouping → capture (all statutory sections) → declarations → readiness → generate → finalise → download, plus entity setup and consolidated statements. Minor gaps: no tool directly exposes historical version diffing beyond list_snapshots, and the management-data section (budgets, allocations, variance) feels bolted on rather than integral to the core flow.

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