schedule-iii

Seal the permanent client copy of a version

finalise_statement

Destructive

Seal a statement version as Datavrn’s permanent client copy, recorded as authorised by the member you name. THIS IS NOT APPROVAL OR ADOPTION OF THE FINANCIAL STATEMENTS AND IT IS NOT A SIGNATURE. It does not discharge section 134(1) for a company or section 34(3) for an LLP. THERE IS NO UNDO. A change afterwards means generating a new version and finalising that one; the version you seal here stays sealed. Call get_finalise_readiness first, show your user every gate and every warning it returns, get their explicit go-ahead, and only then send the confirm_token it gave you together with the acknowledgements. Never acknowledge a warning your user has not seen, and never write the acceptance reason yourself — it is their professional judgment in their own words. Datavrn will refuse if anything about the statement changed after you read the state, and nothing will be finalised. If the response comes back with reused set to true, a finalisation of this same version was already under way: nothing new was done and your approval was not used. Do not call finalise_statement again — the status field says where that finalisation is (queued, running, or paused, which means it hit a temporary problem and Datavrn will retry it on its own). Poll get_job with the job_id and tell your user what it says.

Input Schema

TableJSON Schema

Name	Required	Description
`client_id`	Yes	The entity (client) id — from list_clients.
`snapshot_id`	Yes
`on_behalf_of`	No	The 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.
`confirm_token`	Yes
`acknowledgments`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses critical behaviors: 'THERE IS NO UNDO', the operation is not approval or adoption, and 'Datavrn will refuse if anything about the statement changed after you read the state.' It also explains the 'reused' response scenario and the paused/retry behavior, adding substantial context beyond the structured annotations.

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?

Though lengthy, the description is front-loaded with the core purpose and every sentence carries critical operational or safety information. It avoids redundancy by structuring warnings and prerequisites logically, and the complexity of the tool justifies the length.

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?

Given the tool's complexity, lack of output schema, and low schema description coverage, the description is exceptionally complete. It covers prerequisites, exact workflow, error handling (reused, refused), and post-finalisation verification via get_job, leaving no major contextual gaps 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 description adds important meaning for confirm_token and acknowledgments (e.g., 'send the confirm_token it gave you', 'Never write the acceptance reason yourself'), addressing low schema coverage (40%). However, it does not explicitly explain snapshot_id or client_id beyond what the schema states, leaving some inference required for the version-to-snapshot relationship.

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 states precisely what the tool does: 'Seal a statement version as Datavrn's permanent client copy, recorded as authorised by the member you name.' It clearly distinguishes from sibling tools like confirm_* or save_* by introducing the unique concept of a permanent, sealed copy and explicitly referencing finalise-specific prerequisites (e.g., get_finalise_readiness).

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 provides explicit when-to-use guidance: 'Call get_finalise_readiness first, show your user every gate and every warning...', and warns against re-calling: 'Do not call finalise_statement again.' It also directs follow-up via get_job, contrasting with alternative actions and clarifying the irreversible context.

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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