schedule-iii

Withdraw a recorded capture answer

revoke_capture_declaration

Destructive

Withdraw a recorded capture answer or review confirmation. What happens next depends on what answers the section: withdrawing a “nothing to record”/“does not apply” answer or a review confirmation makes Statement readiness show the section as UNANSWERED again; withdrawing a leftover earlier note from a section that is answered by its saved rows removes the record and the section STAYS answered. A version you have already generated is NOT affected — if you do not want that version finalised, answer the section again and generate a fresh version. Nothing is deleted: the withdrawn answer stays on the record with who recorded it and who withdrew it, and recording a new answer afterwards creates a new entry rather than overwriting the old one. One thing on this connection is affected immediately: if you already called get_finalise_readiness and hold an approval for that version, withdrawing an answer invalidates it, and the next finalise_statement will refuse and ask you to review the current state again.

Input Schema

TableJSON Schema

Name	Required	Description
`client_id`	Yes	The entity (client) id — from list_clients.
`period_id`	Yes
`template_id`	Yes
`capture_kind`	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.

TDQS

A4.1/5.0

Behavior5/5

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

The description goes far beyond the annotations (readOnlyHint: false, destructiveHint: true). It reveals that "Nothing is deleted," clarifies the effect on existing versions, explains the creation of a new entry rather than overwriting, and discloses the side effect of invalidating approvals from get_finalise_readiness. This is rich behavioral context that an agent needs to predict side effects accurately.

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 front-loaded with the core purpose in the first sentence, then branches into consequences and edge cases. While it is verbose, each sentence adds distinct information (e.g., version impact, audit trail, approval invalidation). It is structured as a coherent narrative, though some sentences could be tightened. Overall, it is appropriately detailed for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description thoroughly covers the side effects and consequences of the withdrawal, which is essential for a destructive operation. However, it does not explain how the agent should specify which answer to withdraw (beyond implicitly via capture_kind and IDs), nor does it describe any return value or response format (no output schema exists). The request semantics are under-specified for a mutation tool, leaving gaps in what the agent needs to call it correctly.

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?

The input schema has only 40% coverage, with descriptions for client_id and on_behalf_of, but none for period_id, template_id, or capture_kind. The description does not explain how these parameters map to the answer being withdrawn, nor does it clarify which specific answer is targeted. The description focuses entirely on consequences and ignores the request parameters entirely, failing to compensate for the coverage gap.

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 opens with a specific verb–resource pair: "Withdraw a recorded capture answer or review confirmation." It distinguishes this from recording tools like confirm_capture_review and declare_capture_na by focusing on the act of withdrawal, and the title reinforces the purpose. The purpose is unambiguous and distinct from sibling tools.

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?

The description provides clear context on what happens after using the tool, such as readiness status changes and approval invalidation. It also suggests an alternative action: "answer the section again and generate a fresh version." However, it does not explicitly state when to use this tool versus alternatives like confirm_capture_review, nor does it give exclusions. The guidance is implied but not fully explicit.

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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