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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses the key non-obvious behavior: it performs no action itself ('opens nothing by itself') and returns instructions the agent must then execute via cotlet_browser_*. The note that Substack has only a limited API is useful framing, though the trailing 'API: ... (checked 11 Oct 2026)' sentence is a dangling fragment whose meaning is unclear.

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 most decision-relevant fact — that the tool returns step-by-step instructions rather than stats — is buried in the second sentence after a misleading lead, and 'from ChatGPT, Claude or any AI agent' is pure filler. The final sentence is a sentence fragment that adds ambiguity rather than clarity.

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 params, no output schema, and annotations already covering the safety profile, the description supplies the essentials: it is a browser-workflow guide, not a read. However it never says which metrics the post stats cover, nor how this differs from the sibling stats tools, so an agent still lacks enough to route confidently.

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 nothing for the description to disambiguate beyond what the empty schema already conveys. Baseline 4 applies; no parameter-level gaps exist.

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 opening verb phrase 'Get post stats' matches the tool name but immediately reverses into 'Returns how to do it in Substack step by step (screens, buttons, fields) and opens nothing by itself', so the tool is actually a guidance/instruction generator, not a data fetch. The description does state a specific resource (post stats) and scope ('user's own Substack account'), but the purpose is muddled by the contradiction between the leading verb and the actual output.

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 a follow-up workflow ('then do it with the cotlet_browser_* tools in the user's Substack Cloud Browser'), which is a sequencing hint rather than a when-to-use rule. It offers no guidance on when to pick this over the near-identical siblings get_post_engagement, get_post_traffic, get_daily_stats, or get_publication_stats, leaving the agent to guess among five overlapping stat tools.

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