Request Metrica raw logs

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

The description discloses important behavioral traits beyond the annotations: 'Not read-only: preparing data consumes the counter storage quota' and 'Checks feasibility, then queues preparation (takes minutes).' It also explains the async nature and the request_id polling mechanism, adding significant context on top of readOnlyHint=false and openWorldHint=true.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a compact paragraph of four sentences, each adding value: raw/un-sampled distinction, sources, check/queue behavior, workflow, field discovery, and storage quota warning. It is front-loaded with the main purpose and contains no filler.

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

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 output schema), the description is complete: it explains the return value (request_id), the full follow-up workflow (logs_status, logs_download, logs_clean), prerequisites (date constraints, field discovery), and a key side effect (storage quota). It adequately informs the agent on how to invoke and use the tool correctly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not significantly add parameter-level meaning beyond the schema; it reinforces that fields must match the source prefix and that date2 must be earlier than today, but those are already in the schema. No extra parameter details are provided, so a 3 is appropriate.

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

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

The description clearly states the tool's function: 'Create a Yandex Metrica Logs API request for RAW, un-sampled rows' with specific sources (visits/hits) and date range. It distinguishes from sibling tools by describing the full workflow (request → status → download → clean) and mentioning related tools like get_metadata.

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

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

The description provides explicit workflow guidance: 'Returns a request_id to poll with logs_status; then logs_download, then logs_clean.' It also tells users to discover field ids with get_metadata. However, it does not explicitly contrast with aggregated report tools (e.g., run_report) or state when to choose this tool over them, though 'RAW, un-sampled rows' implies the distinction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.