list_received_logs

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

With no annotations provided, the description carries the behavioral transparency burden. It discloses output format (NDJSON) and data availability constraints (time range limited to 1 hour, data at least 5 minutes old). It does not discuss pagination, auth, or default values for count/sample, so it is adequate but not exhaustive.

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?

Four short sentences front-load the purpose, then add necessary constraints and a use case. No redundancy or 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 no output schema, the description covers the return format (NDJSON) and key constraints. It doesn't explain output fields or pagination, but those are partially addressed by sibling list_log_fields and schema parameters. Overall adequate for an agent to invoke 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 coverage is 100%, so all parameters are described in the schema. The description does not add parameter-specific semantics beyond the schema; it only mentions time range constraints. Baseline of 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?

The description clearly states the tool retrieves HTTP request logs for a Cloudflare zone within a time range and specifies the output format (NDJSON). It distinguishes from siblings like get_log_by_rayid and query_security_events by explicitly mentioning HTTP request logs and zone scope.

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?

It gives clear context: useful for investigating traffic patterns and anomalies, and records specific constraints (1-hour range, 5-minute delay). However, it does not name alternative tools or state when not to use this tool, so it stops short of being fully explicit.

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