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ai_invoice_scan_pending

Retrieve vendor-bill drafts with attachments that have not been successfully extracted, prioritizing oldest entries. Use requested_only=true to return only bills queued for extraction by the attachment auto-trigger.

Instructions

List vendor-bill drafts that have an attachment and no successful extraction yet. Oldest first (FIFO). Feeds batch processing. Set requested_only=true to return only moves explicitly queued by the l10n_bg_ai_invoice_glue attachment auto-trigger (ai_pipeline_requested=True) — recommended for cron drivers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionNodefault
tenant_codeNo
limitNo
requested_onlyNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the filtering criteria, ordering, and parameter behavior, but does not explicitly state that the tool is read-only or has no side effects. Given the lack of annotations, the description is adequate but could be more transparent about safety.

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?

The description is two sentences long, front-loaded with the core purpose, and then provides the key parameter detail. Every sentence is informative without any redundant or vague phrasing.

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 tool has 4 parameters, no output schema, and no nested objects. The description explains the core functionality and one parameter well, but lacks details on the return format, expected output fields, and the meaning of 'Feeds batch processing'. This leaves some gaps for an AI agent needing full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must add meaning. It explains 'requested_only' in detail, but does not describe 'connection', 'tenant_code', or 'limit' (though limit is somewhat self-explanatory). This partial coverage means the description adds value but not fully compensates for the schema 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 clearly states the verb 'list', the resource 'vendor-bill drafts that have an attachment and no successful extraction yet', and the ordering 'Oldest first (FIFO)'. It also mentions its role in batch processing and cron drivers, distinguishing it from sibling tools like ai_invoice_extract or generic list 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 specific guidance on using the 'requested_only' parameter for cron drivers. However, it does not explicitly state when not to use this tool versus alternatives, such as ai_list_documents or ai_invoice_extract, leaving some ambiguity for the agent.

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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