read_log_paginated

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

Without annotations, the description carries the burden. It discloses key behaviors: token-based pagination, change tracking via expected_size and expected_mtime. This goes beyond simple read into operational details. No contradiction with missing annotations. However, it does not mention error states or side effects, slightly lowering the score.

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?

Three sentences, each dense with information. No fluff. Front-loaded with the primary action. Every sentence earns its place.

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?

With no output schema, the description should explain return values. It implies change tracking results but not explicitly. The parameter richness (6 params) is well-covered by schema, so overall adequate but lacks output format clarity. Still, it's reasonably complete for an agent.

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 baseline is 3. The description adds no per-parameter semantics beyond what the schema already provides. It mentions overall behaviors (pagination, change tracking) but not parameter-specific meaning.

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 it reads a paginated portion of a log file, which distinguishes it from siblings like head_log, tail_log, and read_log_range. The mention of 'paginated' and 'large log files' makes its purpose specific and differentiated.

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 explicitly says 'Useful for large log files' and mentions 'token-based pagination to respect AI context limits', providing clear guidance on when to use. However, it does not explicitly state when not to use or name alternatives, though the sibling context implies when other tools might be preferred.

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