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schedule-iii

by com.datavrn

Save prior-year comparatives

save_py_values
Destructive

Override the prior-year comparative for one or more statement lines with an audited figure. The prior-year column fills itself automatically from the previous year's Trial Balance read through the current groupings, so use this only when the audited financial statements differ from that figure (for example appropriations booked outside the ledger), or when there is no previous-year Trial Balance to derive from — ask your user for the audited figures in those cases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valuesYes
client_idYesThe entity (client) id — from list_clients.
period_idYes
template_idYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already flag destructiveHint=true, and the description adds valuable behavioral context: the prior-year column auto-fills from the previous year's Trial Balance, so this tool is an exception override. It doesn't detail side effects beyond 'Override', but the annotation and verb together convey the destructive nature.

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 compact: two sentences, the first stating purpose and the second providing usage conditions. Every sentence adds essential information with no redundant filler.

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?

Given the tool's complexity (4 parameters, no output schema) and the presence of annotations, the description covers purpose, usage conditions, and user interaction. However, it lacks explicit instructions on constructing the values array and what to expect after the save operation, leaving some gaps for the agent.

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

Parameters2/5

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

Schema description coverage is only 25% (only client_id has a description), and the description does not explain leaf_code, amount, period_id, or template_id semantics. The phrase 'audited figure' hints at the values parameter but does not clarify how leaf_code maps to statement lines or how amounts should be formatted.

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 uses the specific verb 'Override' and clearly identifies the resource as 'prior-year comparative for statement lines'. It also mentions the automatic fill behavior, which distinguishes this tool from siblings like save_adjustments or save_disclosures.

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 explicitly states 'use this only when' and lists two precise conditions (audited financial statements differ, or no previous-year Trial Balance). It also instructs the agent to ask the user for audited figures in those cases, providing clear decision guidance.

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.

Resources