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BoxLab-Ltd

yandex-metrica-mcp

by BoxLab-Ltd

Download Metrica raw logs

logs_download
Read-only

Download processed log data from Yandex Metrica by request ID. Sample mode returns rows inline; file mode streams the full export to a file.

Instructions

Download prepared log data for a request_id (must be status="processed"; check logs_status). Default mode "sample" returns up to maxRows parsed rows inline — cheap and bounded. Mode "file" streams the FULL export to a file and returns its path plus a small preview; the raw content (potentially millions of rows) is never loaded into context. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNosample (default): return up to maxRows parsed rows inline — cheap, bounded, no file. file: stream the FULL export to a file and return its path plus a small preview.
maxRowsNosample mode only: max rows to return inline (default 100, max 1000).
counterIdNoYandex Metrica counter id. Optional if YANDEX_METRIKA_COUNTER_ID is configured.
requestIdYesLog request id returned by logs_request.
outputPathNofile mode only: absolute path to write the export to. Defaults to a file in the configured logs directory.
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses mode-specific behavior: sample mode is cheap and bounded, while file mode streams the full export to a file and never loads raw content into context. It also reiterates the read-only nature, adding safety context without contradicting annotations.

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 four short, information-dense sentences, front-loaded with the primary purpose. Every sentence contributes valuable context (modes, boundedness, output behavior, read-only), with no fluff or redundancy.

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

Completeness5/5

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

For a tool with moderate complexity (5 params, no output schema) and annotations providing read-only behavior, the description covers purpose, prerequisites, output behavior for both modes, and memory safety. It gives an agent sufficient context to select and invoke the tool correctly within the workflow.

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 each parameter is already documented. The description adds contextual trade-offs between modes but does not provide significant per-parameter detail beyond what the schema states. Baseline of 3 is appropriate when the schema carries the semantic load.

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 uses the specific verb 'Download' and identifies the resource 'prepared log data' for a request_id, clearly distinguishing this tool from siblings like logs_request and logs_status. It also specifies the required status condition, making the tool's function unambiguous.

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 explicitly states the prerequisite that request_id must have status 'processed' and points to logs_status for verification, providing clear when-to-use context. It also explains the two modes (sample vs. file) to guide selection based on need, though it does not explicitly mention when not to use the tool relative to other siblings.

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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