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schedule-iii

by com.datavrn

Preview undoing an automatic sync

preview_replacement_restore

Show EXACTLY what undoing one automatic sync would do, counted at this moment, and get the approval restore_replacement needs. destroy_count is how many records undoing it would DESTROY — everything currently held for that period, whoever or whatever put it there, including data a colleague uploaded since. restore_count is how many records would be put back. READ BOTH NUMBERS TO YOUR USER IN THEIR OWN TERMS AND GET THEIR EXPLICIT GO-AHEAD BEFORE CALLING restore_replacement. Undoing a sync is itself a destructive act. If blocked_reason comes back non-null, the period is locked by a finalised statement or a sealed run: read that reason out, do not call restore_replacement, and no approval is issued. The approval is single-use, expires in 15 minutes, and is tied to this entity, this sync, this connection, the member you name AND the exact destroy_count returned here. Send that same number back as expected_destroy_count — never a number you adjusted. If the period’s data changes in between, the approval is spent and you start again from here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_idYesThe replacement’s id — the `id` field of a list_replacements row.
client_idYesThe entity (client) id — from list_clients.
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.
connection_idYesThe connected data source’s id — from list_replacements or get_pending_work.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations are minimal (readOnlyHint=false, destructiveHint=false) so the description carries the behavioral burden. It fully discloses that the tool is a preview that computes counts 'at this moment,' returns blocked_reason for locked periods, issues a single-use approval expiring in 15 minutes tied to specific parameters, and warns that undoing a sync is itself destructive. This exceeds what annotations convey and adds critical context about side effects and failure modes. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is approximately 250 words—long but not bloated for a safety-critical approval tool. However, it's a single paragraph without visual structure, and some phrases are repetitive (e.g., 'undoing a sync' appears twice). It is front-loaded with the main purpose, but could be tightened with bullet points or shorter sentences for easier scanning. Compared to the calibration examples, this is acceptable for complexity but not as crisp as ideal.

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?

The tool has no output schema, so the description must explain return values; it does: destroy_count, restore_count, and blocked_reason. It also covers timing (counted at this moment), approval mechanics (single-use, expiry, binding), and failure handling (blocked_reason non-null). All necessary steps for correct invocation and follow-up are present. Given its role in an approval chain, the description is complete and self-sufficient.

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?

Schema descriptions cover 100% of parameters, so baseline is 3. The tool description adds contextual meaning by linking parameters to the approval context: 'this entity, this sync, this connection, the member you name' maps to client_id, event_id, connection_id, and on_behalf_of. It also explains how to feed the output (destroy_count) into the expected_destroy_count parameter of the next tool. This goes beyond schema descriptions and clarifies the operational flow.

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: 'Show EXACTLY what undoing one automatic sync would do' and 'get the approval restore_replacement needs.' It uses a specific verb (preview) plus resource (undoing a sync) and explicitly differentiates from the sibling restore_replacement by framing this as the prerequisite step. An agent can immediately understand what this tool does and how it fits the workflow.

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 usage guidance: instructs the agent to read both destroy_count and restore_count to the user, get explicit go-ahead before calling restore_replacement, and handle blocked_reason by aborting. It also names the sibling tool restore_replacement as the follow-up and warns when not to proceed. This is direct, actionable guidance with clear conditions and alternatives.

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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