source_read

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds substantial behavioral context beyond that. It discloses content length limits (default 10,000 chars), pagination via offset/max_chars, that char_count stays full length, content null when not ready, and that output_format markdown requires a server extra. No contradiction with annotations.

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 long but densely structured with bullet points and code blocks. Every sentence earns its place, delivering detailed parameter semantics and return shapes without redundancy. It is front-loaded with a clear purpose statement and then organized detail.

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 explains return values thoroughly, including both detail shapes and edge cases like truncated content and null content. It also covers the 'markdownify' dependency and refers to chat_ask for large sources, making the tool's behavior fully understandable in context.

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 0%, so the description fully compensates. It explains each parameter: detail chooses the return shape, offset/max_chars slice the content, output_format controls formatting, and provides the exact return keys for summary and full. This goes far beyond the schema's bare enum/type definitions.

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 states a specific verb and resource: 'Read a source at one of two detail levels.' It clearly differentiates from sibling tools like source_list, source_delete, and source_wait by focusing on reading the content/metadata at chosen detail levels. The two detail shapes (summary vs full) further clarify the tool's purpose.

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 usage guidance: 'summary' is recommended for low-token triage across many sources, 'full' for detailed content, and it explicitly says 'Prefer chat_ask for querying large sources rather than pulling the whole body.' This names an alternative and provides context on when to choose one approach over others.

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