schedule-iii

Create upload link

create_upload_link

Mint a single-use, login-free upload link so a file reaches Datavrn WITHOUT passing through your context, where it cannot truncate or corrupt. Use this whenever a human has the file (a trial balance export, etc.) — and also whenever YOU hold the file and it is larger than about 10 KB. This is the RELIABLE path at that size: inlined base64 mutates often enough that the damage arrives as a plausible-looking trial balance rather than an obvious error, while the link delivers the bytes byte-perfect. Two ways to deliver the file: a HUMAN opens upload_url in their browser and chooses the file; a PROGRAMMATIC caller that already holds the file on disk POSTs it to the SEPARATE upload_post_url as a multipart form with a single file field (upload_url is the human page and will not accept a POST). The POST reply carries received_file_hash — compare it to your local sha256 before confirming the mapping. The link stages the file for ONE entity and expires in about 15 minutes; nothing is ingested until the column mapping is confirmed.

Input Schema

TableJSON Schema

Name	Required	Description
`format`	No	Leave unset — the assistant handles Trial Balances only; any other format is refused (use the Datavrn web app).
`source`	No	Set 'tally_file' when the file is a Tally xlsx export; omit otherwise.
`client_id`	Yes	The entity (client) id — from list_clients.
`file_name`	Yes	The file the user is expected to upload, e.g. 'tb-2026-03.xlsx' (shown on the upload page).

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, openWorldHint=false), so the description carries the full transparency burden. It discloses the link's 15-minute expiry, single-entity staging, and that nothing is ingested until column mapping is confirmed. It also explains the separate URLs and the hash-comparison step for the POST reply, giving the agent a complete behavioral model.

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 dense with critical operating details, front-loaded with the core purpose and then the two delivery paths. While longer than average, every sentence serves a purpose—no filler. It could be tightened slightly, but the complexity of the workflow justifies the length.

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 (mutating, two delivery URLs, expiration, hash verification), the description covers the main usage correct. A minor gap: it doesn't explicitly state the tool's response contains upload_url and upload_post_url, though it alludes to them. Lacking an output schema, a direct mention of the returned fields would make it fully complete, but the description still enables correct usage.

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 description coverage is 100%, so the baseline is 3. The description adds meaning: it explains that 'format' should be left unset (only trial balance accepted), 'source' is set to 'tally_file' for Tally exports, and elaborates on the purpose of 'file_name' and 'client_id' (from list_clients). This goes beyond mere schema text with concrete usage context.

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 mints a single-use, login-free upload link to get a file to Datavrn, and explicitly contrasts it with inlined base64 in context. It specifies the verb (mint), resource (upload link), and distinguishes itself from sibling upload tools like upload_trial_balance by focusing on the link mechanism rather than direct upload.

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 when-to-use instructions: use when a human has the file, or when the agent holds a file larger than ~10 KB. It also details the two delivery methods (human opens upload_url, or programmatic POST to upload_post_url) and warns against using context for large files. It even covers edge cases like refusing non-trial-balance formats, directing to the web app instead.

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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