get_selection

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

The description discloses the tool's core behavior: it reads a specific file, returns a summary, and optionally includes the full JSON payload. Since no annotations are provided, the description carries the burden of explaining the operation. It doesn't cover error scenarios, but for a simple read-only tool this is adequate.

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 two sentences, with the first sentence front-loading the core purpose and the second explaining parameter usage. There is 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?

The description covers the tool's purpose, return value, and parameter behavior. It lacks explicit error handling or file path details, but given the tool's simplicity and the presence of no output schema, it is sufficiently complete for an agent to invoke it 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?

The input schema already describes fullJson as a boolean, but the description adds that passing fullJson=true returns the raw payload, clarifying the exact effect and intended use. This adds value beyond the schema's minimal definition.

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 identifies the tool as reading the Obsidian selection bridge file and returning a summary of selected elements (ids, type, text, bounds) plus optional instruction. This distinguishes it from sibling tools like get_element or query_elements, which operate directly on the canvas.

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 provides clear context for when to use this tool: after the 'AI Edit Selected' EA script writes the .ai-selection.json file. However, it does not explicitly mention alternatives or exclusion cases, so it stops short of a 5.

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