schedule-iii

Read budget

get_budget

Read-only

MANAGEMENT data class. Read one versioned budget: identity-free header, its pinned P&L tree, and filtered/paginated cells with entered-versus-inferred truth. Amounts and locked FX rate are decimal strings. Filter months, lines, centres, or inference before paging; the signed page_token is source-pinned, so restart at page 1 if source_changed. Cells across different P&L lines are not one meaningful grand total, so no cross-line grand total is exposed. No people, ownership, editability, or approval identities are returned.

Input Schema

TableJSON Schema

Name	Required	Description
`month`	No	Optional budget month in YYYY-MM.
`budget_id`	Yes	Budget id from list_budgets.
`client_id`	Yes	The entity (client) id — from list_clients.
`inference`	No	Cell inference state (default all).
`page_size`	No	Cells per source-pinned page (default 100, max 200).
`line_codes`	No	Up to 25 P&L line codes.
`page_token`	No	Signed continuation from the prior page; restart without it if source_changed.
`cost_centre_ids`	No	Up to 25 cost-centre ids.

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 discloses substantive behavioral traits: amounts and FX rate are decimal strings, page_token is source-pinned and requires restart on source_changed, no cross-line grand total is exposed, and identity-related fields are omitted. This goes well beyond what annotations provide.

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 information-dense but well-structured: it opens with the core purpose, then covers data types, pagination/filtering, a caveat about grand totals, and exclusions. Every sentence contributes unique value, and the text is front-loaded with the primary action.

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 8 parameters and no output schema, this description is notably complete. It explains the return contents (header, P&L tree, cells), pagination/filtering semantics, and important limitations (no grand total, no identity fields), giving an agent enough context to invoke the tool correctly.

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?

All 8 parameters have schema descriptions (100% coverage), setting a baseline of 3. The description adds extra meaning by mentioning filter dimensions ('months, lines, centres, or inference') and the source-pinned page_token behavior, which clarifies how parameters interact beyond the schema's individual property 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?

The description clearly states the tool's purpose with a specific verb ('Read') and a distinct resource ('one versioned budget'), and it enumerates the returned components (identity-free header, pinned P&L tree, filtered/paginated cells). It differentiates itself from sibling get_* tools by focusing on budget data and including a data-class qualifier ('MANAGEMENT').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context about what the tool returns and notes exclusions (no people/ownership/approval identities), but it does not explicitly indicate when to use this tool versus alternatives like list_budgets or get_tb_rows. Usage guidance is implied by the tool name and the first sentence, but no explicit alternatives or exclusions are given.

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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