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schedule-iii

Save significant accounting policies

save_accounting_policies
Destructive

Save the Significant Accounting Policies text (Note 2) your user has chosen, one policy per title. SEND THE COMPLETE SET EVERY TIME: this replaces all of Note 2, so any title you leave out of this call is removed — including one someone answered in the Datavrn app. Call list_statement_policy_choices first and send back every title. If your call would drop a saved policy, Datavrn saves nothing and returns an approval request naming how many would be dropped — show your user, and send the approval back only if they mean to drop them. A complete resend drops nothing and saves straight away. Use the exact policy headings this statement format carries; a heading Datavrn does not recognise is refused and nothing is saved. Resolving a bracketed template choice such as "[FIFO / weighted average]" is an ACCOUNTING POLICY DECISION SPECIFIC TO THIS ENTITY: get your user’s explicit choice, and never pick one because it is the common answer. If a policy was set this year and differs from last year’s answer, that is a CHANGE IN ACCOUNTING POLICY requiring disclosure under AS-5 / Ind AS 8 — tell your user before you save it. Check list_statement_policy_choices first: a row that differs from last year while its captured flag is false is NOT a change — last year’s wording has simply not been carried forward, and unless you send it again this note prints Datavrn’s generic template wording in its place. Saving here re-opens the disclosure review — after your last change, confirm the disclosure review again with confirm_capture_review before generating. Recorded as authorised by the member you name. Generate a fresh version after your last capture change — finalisation checks the version’s frozen capture state, not today’s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
policiesNo
client_idYesThe entity (client) id — from list_clients.
period_idYes
template_idYes
on_behalf_ofNoThe email address your user signs in to Datavrn with. This records who authorised the change alongside the connection that made it. REQUIRED on an API-key connection — ask your user for it, do not guess. On an OAuth connection leave it out: the change is recorded as authorised by the member who connected; if you do supply it, it must be that member.
removal_countNo
removal_tokenNo

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses that the call replaces all of Note 2, that omitted titles are removed, that dropping policies triggers an approval request, that unrecognized headings are refused, and that saving re-opens the disclosure review. This fully informs the agent of the tool's behavior.

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 sentence adds critical operational detail. However, it is a single dense paragraph; breaking it into bullets or numbered steps would improve scannability without loss of content.

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 complex, destructive write tool with no output schema, the description covers prerequisites, destructive consequences, approval mechanics, policy change disclosure, authorisation record, and follow-up confirmation steps. It is fully complete for an agent 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?

The schema only describes client_id and on_behalf_of (29% coverage). The description compensates by explaining that policies should be a complete map of titles, warns about exact headings, and refers to the removal_count/removal_token flow via the approval request. It doesn't explicitly name each parameter, but it gives the semantic context needed to populate them correctly.

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 that the tool saves the Significant Accounting Policies text (Note 2), one policy per title, making the verb and resource explicit. This distinguishes it from sibling save_* tools like save_disclosures or save_adjustments by naming the exact statement note.

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 gives explicit step-by-step guidance: call list_statement_policy_choices first, send the complete set every time, follow up with confirm_capture_review, and generate a fresh version after last capture change. It also explains when a difference from last year is not a change, preventing misuse.

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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