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

Annotations already declare readOnlyHint=true, openWorldHint=false, idempotent, and non-destructive. The description adds the non-obvious behavioral fact that the tool 'opens nothing by itself' and returns procedural guidance instead of data, which annotations cannot convey. It stops short of describing the format or extent of the returned instructions (e.g., verbosity, whether it varies by conversation).

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 useful information (returns instructions, does nothing itself, follow up with browser tools) is front-loaded and clear. But 'from ChatGPT, Claude or any AI agent' is filler, and the closing sentence about Trengo's REST API and lack of an official MCP server is tangential metadata that does not help an agent invoke this tool.

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 zero parameters, no output schema, and strong annotation coverage, the definition supplies what an agent needs: what comes back, that nothing is mutated, and what to call next. The remaining gap is that it never clarifies its relationship to the similarly-scoped cotlet_app_guide sibling, which could cause a wrong selection.

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 tool takes zero parameters, so there is no parameter meaning to add and the schema is trivially complete. Baseline 4 applies; nothing in the description needed to compensate for parameter ambiguity.

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 first sentence names a specific verb and resource (read a conversation in Trengo) and the second clarifies the crucial twist: it returns step-by-step instructions rather than conversation data. The follow-up pointer to cotlet_browser_* tools distinguishes it from the browser siblings. It loses a point because the name 'read a conversation' still reads like it fetches content, requiring the agent to read past the title to learn otherwise.

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 gives an explicit two-step workflow: call this to get the screens/buttons/fields, then execute with cotlet_browser_* in the Trengo Cloud Browser. That is clear when-to-use context. It does not, however, say when to prefer this over trengo_list_conversations, trengo_search_conversations, or cotlet_app_guide, so sibling disambiguation is incomplete.

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