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

Annotations already declare readOnlyHint=true and destructiveHint=false; the description reinforces this with the concrete statement that it 'opens nothing by itself', which is exactly the reassurance an agent needs before treating the call as a planning step. It also discloses the return shape at a high level (step-by-step screens, buttons, fields). It stops short of stating auth/permission needs or whether the guidance is model-specific.

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 core operative sentence about returning step-by-step instructions and not opening anything is well placed, but the lead-in naming ChatGPT, Claude and 'any AI agent' is filler, and the trailing 'Anaplan's official API: Yes' is cryptic and unearned. Roughly half the text does work; the rest could be cut without losing meaning.

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?

There is no output schema, so the description must convey what comes back; it does so only loosely (steps, screens, buttons, fields) without structure or length expectations. Given the tool takes no inputs and is read-only, this is adequate but leaves the agent guessing about how the guidance maps to a specific process.

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 zero parameters there is no schema semantics to add, which normally supports a high score, but the description never explains how the target process is identified at all (no model, workspace, or process selector), leaving a real ambiguity about what this call actually operates on. The 'Anaplan's official API: Yes' line adds no parameter or behavioral 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 second sentence states a specific behavior: it returns step-by-step Anaplan instructions (screens, buttons, fields) rather than performing the action, which corrects the misleading verb in the name 'run'. It also distinguishes itself from the cotlet_browser_* execution tools. The opening sentence ('Run process in the user's own Anaplan account from ChatGPT, Claude or any AI agent') is more marketing framing than purpose and briefly points the wrong way.

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?

There is useful sequencing guidance: this tool produces the plan, and 'then do it with the cotlet_browser_* tools', plus an explicit exclusion that it 'opens nothing by itself'. However, there is no guidance on when to pick this over the Anaplan action siblings (anaplan_run_export, anaplan_run_import, anaplan_list_actions), so the choice among the non-browser Anaplan tools is left to inference.

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