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query_logs

Search and filter logs for a project. Supports filtering by level, source, time range, and text search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd time (ISO 8601 or YYYY-MM-DD)
urlNoFilter by URL or request path (e.g., '/api/checkout', '/auth/callback')
fromNoStart time (ISO 8601 or YYYY-MM-DD)
levelNoLog level: TRACE, DEBUG, INFO, WARN, ERROR, FATAL
limitNoMax results (1-1000, default 100)
queryNoText search in message field
sourceNoSource tag (e.g., 'worker.auth')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only restates the filtering capabilities already visible in the input schema. It does not disclose result ordering, pagination, whether it returns raw logs or summaries, default time-range behavior, or any other operational details beyond the schema.

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 a single, compact sentence with no fluff. It front-loads the core action and then lists the filtering dimensions efficiently. It is concise, though it could be marginally improved by adding a note about what the tool returns.

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?

Despite having no output schema and no annotations, the description does not explain return values, result format, ordering, or default behavior. With seven optional parameters and no output schema, the description is too thin to fully prepare an agent to invoke the tool and interpret results correctly.

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%, so the schema already documents all seven parameters clearly. The description's mention of 'level, source, time range, and text search' merely summarizes the schema properties without adding new meaning. Per the calibration baseline, a 3 is appropriate.

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 states a specific action ('Search and filter logs') and a resource ('for a project'), which clearly identifies the tool's function. It also lists the key filtering dimensions. However, it does not explicitly differentiate this tool from sibling tools like get_log_stats or get_recent_errors, so it falls short of a 5.

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: this tool is for searching and filtering logs. It implies the appropriate use case without ambiguity. However, it offers no exclusions or references to alternative tools, so it stops short of fully explicit usage guidance.

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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