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deals_list_all_auto

Fetch all Pipedrive deals in a single response, with automatic pagination handling. Use filters to limit results, suitable for exports, reports, or comprehensive analysis.

Instructions

Automatically fetch ALL deals with pagination handling.

This tool automatically handles pagination and fetches all deals matching the filters. Unlike deals/list, this returns ALL results in a single response.

WARNING: This can return large datasets. Use filters to limit results.

Workflow tips:

  • Same filters as deals/list (status, stage_id, user_id, person_id, org_id, etc.)

  • Specify max_items to limit total results if needed

  • No need to manage start/limit - pagination is automatic

  • Best for exports, reports, or comprehensive analysis

Common use cases:

  • Get all open deals: { "status": "open" }

  • Export all deals for a pipeline: { "pipeline_id": 1 }

  • Get all deals for analysis: { "max_items": 1000 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by deal status
stage_idNoFilter by stage ID
user_idNoFilter by user (owner) ID
person_idNoFilter by person ID
org_idNoFilter by organization ID
pipeline_idNoFilter by pipeline ID
filter_idNoID of the filter to use
sortNoField to sort by
sort_byNoSort direction
owned_by_youNoFilter deals owned by the authorized user
max_itemsNoMaximum number of items to return
Behavior3/5

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

Since no annotations are provided, the description carries full burden. It discloses automatic pagination, large data potential, and the max_items parameter to limit results. However, it does not explicitly state that the tool is read-only or that it does not modify data, leaving some ambiguity.

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 concise and well-structured with a main statement, warning, workflow tips, and common use cases. It is front-loaded and every sentence adds value without redundancy.

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 (11 optional parameters, no output schema), the description covers the key aspects: automatic pagination, large data warning, filter usage, and max_items. It could mention response format but is not required as per instructions.

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 coverage is 100%, but the description adds value by grouping filters and explaining max_items usage. It provides context on how to use parameters together, e.g., specifying filters and max_items, which goes beyond the schema descriptions.

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 automatically fetches all deals with pagination handling, and explicitly distinguishes itself from deals/list by noting it returns all results in a single response. The verb 'fetch' and resource 'deals' are specific.

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: it's best for exports, reports, or comprehensive analysis, and warns about large datasets. It gives workflow tips and common use cases. However, it does not explicitly state when to use alternatives like deals/list for smaller queries.

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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