send_logs_to_loki

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

No annotations are provided, so the description carries the burden; it does disclose that this is a manual injection into an external aggregation system and implies an append-style write. It does not cover auth/permission requirements, whether ingestion is asynchronous or how failures surface, and it omits the label cap that only exists in the schema. The presence of an output schema reduces the need to describe return values.

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?

Two sentences with the core action front-loaded in the first. There is minor redundancy between "centralized log aggregation" and "Loki log aggregation system" in the second sentence, but nothing that wastes meaningful space.

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?

For a simple 3-parameter tool with full schema coverage and an output schema, the description covers the essentials of what it does. It leaves the main gaps around write semantics (sync vs async ingestion, permission needs) and when to prefer query_loki_logs or correlate_logs_and_metrics.

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% and all three parameters (level, labels, log_message) are documented in the schema, including the max-10 label rule, so the description can legitimately defer. It adds no format or convention guidance (e.g. label naming, level selection) beyond the structured fields, so the baseline 3 applies.

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?

States a specific verb+resource ("Send custom log entries to Loki") plus the outcome ("centralized log aggregation"), which distinguishes it from the read-side sibling query_loki_logs. It does not explicitly name that sibling, so differentiation is done only implicitly via the verb.

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 second sentence gives an implied use case ("manual log injection ... enabling correlation between custom events and system metrics"), which tells the agent roughly why to reach for this tool. However, it never states when NOT to use it, nor names query_loki_logs / correlate_logs_and_metrics as the alternative for the correlation goal.

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