Журнал бота

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

Annotations already signal readOnly, idempotent, non-destructive behavior. The description adds meaningful behavioral context: entries are returned newest-first, the log is recent history rather than an archive because the panel removes old entries, and the response ends with a summary of encountered kinds and counts. This goes beyond the structured annotations without contradicting them.

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?

Every sentence adds distinct value: scope of entries, differentiation from audit_list, ordering and filtering, response summary, and retention behavior. The text is dense but not bloated, and the most important information is front-loaded.

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?

There is no output schema, but the description partially compensates by explaining ordering, filtering, the kind summary at the end, and the non-archival nature of the log. A more explicit list of per-entry fields would make it fully complete, but the provided context is sufficient for an agent to call the tool and interpret the high-level result.

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 schema already documents all six parameters. The description mentions the kind and level filters, particularly level=error, but does not add new semantic detail beyond what the schema provides. Baseline 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?

Description opens with a concrete statement of what the tool returns: bot actions such as starts/stops, incoming updates, model responses, script errors, and platform refusals. It also explicitly contrasts this with audit_list, making the resource and scope unmistakable and distinguishing it from a sibling tool.

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 explicitly names audit_list as the log of human actions and states that this journal answers 'why the bot is silent', giving a clear selection condition. It also explains how to narrow results by kind and level, which directly supports correct invocation.

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