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bitrix24_search_crm

Search CRM data for contacts, companies, deals, or leads using email, phone, or name queries to find relevant business information.

Instructions

Search across CRM entities (contacts, companies, deals, leads)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (email, phone, name)
entityTypesNoEntity types to search
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the tool searches across entities but doesn't disclose behavioral traits such as search scope (e.g., partial vs. exact matches), permissions required, rate limits, or what the output looks like (e.g., list of results with fields). For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 a single, efficient sentence with zero waste. It front-loads the core purpose ('Search across CRM entities') and specifies the entity types concisely. Every word earns its place without redundancy.

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

Completeness2/5

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

Given the complexity of a search tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., search behavior, permissions), output format, and usage context. While the schema covers parameters well, the overall context for an AI agent to invoke the tool effectively is insufficient.

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 100%, with clear descriptions for both parameters ('query' and 'entityTypes'), including default values and enums. The description adds minimal value beyond the schema by listing entity types, but doesn't provide additional context like search syntax or performance implications. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search across') and target resources ('CRM entities'), specifying the entity types (contacts, companies, deals, leads). It distinguishes from sibling tools like 'bitrix24_list_contacts' or 'bitrix24_get_contact' by indicating a cross-entity search. However, it doesn't explicitly contrast with 'bitrix24_filter_deals_by_budget' or other filtering tools, missing full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like broad searches vs. specific entity lookups, or compare to sibling tools like 'bitrix24_list_contacts' for listing all contacts without a query. There's no explicit when/when-not or alternative tool references.

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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