read_context_data - vision & file context dumper

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses critical behaviors: fallback from API to local OCR, image resizing with sharp, truncation with a notice, automatic skipping of sensitive files, and a summary footer with error counts. This is rich behavioral context that annotations alone do not provide.

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 a single dense paragraph but every sentence adds value: input types, fallback behavior, filtering rules, output format, and limits. It is appropriately sized for the tool's complexity, though a more structured layout would improve scannability; still, it is not bloated.

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 the tool's complexity (10 params, no output schema), the description provides a complete operational picture: input handling, ordering preservation, automated exclusions, truncation, error reporting, and token usage estimation. It even includes example formatting for image analyses, making it sufficient 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?

With schema description coverage at 0%, the description compensates by explaining the primary `items` parameter (accepts paths, bare names, or in-memory objects), and indirectly addresses others like `maxOutputChars` and `includeFileTree` ('archives get a directory Tree', 'Output is capped at maxOutputChars'). It does not cover all 10 parameters in detail, but enough for effective use.

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 starts with a specific verb and resource: 'Extracts readable code/text from images, single files, or zip archives' and clearly defines the output as 'a strictly-ordered, LLM-ready text dump with a file tree for archives.' This distinguishes it from the sibling tool find_images by focusing on content extraction and reading rather than just locating images.

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 clear usage context, such as 'Pass an ordered items array' and mentions auto-detection of images from temp/clipboard folders for chat-attached screenshots. However, it does not explicitly state when to avoid this tool or compare it to alternatives like find_images, so it earns a 4 rather than 5.

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