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search_prompt_log

Search AI prompt logs from medical document processing to track calls by type, document, status, date, or text content.

Instructions

Search prompt logs — all AI calls made during document processing.

Returns a list of prompt log entries (without full prompts for brevity). Use get_prompt_log_entry to see full prompts and responses for a specific entry.

Args: call_type: Filter by type: 'ocr', 'summary_tags', 'structured_metadata', 'filename_description'. document_id: Filter by document ID. status: Filter by status ('ok' or 'error'). date_from: Filter from date (YYYY-MM-DD). date_to: Filter to date (YYYY-MM-DD). text: Search in prompts and responses. limit: Max results (1-200, default 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
call_typeNo
document_idNo
statusNo
date_fromNo
date_toNo
textNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It describes what the tool returns ('list of prompt log entries without full prompts') and mentions a default limit behavior ('default 50'), which adds useful context beyond the input schema. However, it doesn't disclose other important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or error handling. For a search tool with 7 parameters, this leaves significant gaps in behavioral understanding.

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 perfectly structured and concise. It begins with a clear purpose statement, then describes the return value and relationship to sibling tool, followed by a well-organized parameter section. Every sentence earns its place: the first sentence defines the tool, the second describes returns, the third provides usage guidance, and the parameter explanations are essential given the schema's 0% description coverage. No wasted words or redundant information.

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 (7 parameters, no annotations, but with output schema), the description is mostly complete. The parameter semantics are thoroughly covered, and the relationship to the sibling tool is clear. The presence of an output schema means the description doesn't need to explain return values. However, for a search tool with no annotations, it could benefit from more behavioral context about read-only nature, performance characteristics, or error scenarios to be fully complete.

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

Parameters5/5

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

The description provides excellent parameter semantics beyond the input schema. With 0% schema description coverage and 7 parameters, the schema only shows types and defaults. The description adds crucial semantic information: it explains what each parameter filters by (e.g., 'Filter by type', 'Filter by document ID', 'Search in prompts and responses'), provides allowed values for 'call_type' and 'status', specifies date format ('YYYY-MM-DD'), and gives range/constraint information for 'limit' ('1-200, default 50'). This fully compensates for the schema's lack of descriptions.

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 tool searches 'prompt logs — all AI calls made during document processing' and returns 'a list of prompt log entries', providing specific verb ('search') and resource ('prompt logs'). It distinguishes from sibling 'get_prompt_log_entry' by noting this returns entries 'without full prompts for brevity' while the sibling shows full details. However, it doesn't explicitly differentiate from other search tools like 'search_documents' or 'search_activity_log' beyond the resource type.

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 for when to use this tool versus alternatives: it explicitly states 'Use get_prompt_log_entry to see full prompts and responses for a specific entry,' giving a direct alternative for detailed viewing. However, it doesn't mention when NOT to use this tool (e.g., for non-prompt-log searches) or compare it to other search tools in the sibling list, leaving some usage boundaries implicit rather than explicit.

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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