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

Goes well beyond the readOnly/openWorld/idempotent annotations by disclosing public-posts-only scope, the official public API with no login, and — critically — the payment model (x402 USDC on Base at $0.001 per successful call, and that an unpaid call returns a PaymentRequired object). That pricing/error behavior is exactly the kind of operational context an agent cannot infer elsewhere.

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?

Two sentences, front-loaded with the use-case and result shape, then operational caveats. The field enumeration is dense but earns its place given there is no output schema; no filler sentences.

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 no output schema, the description compensates by enumerating returned fields (plain text, author handle, createdAt, language, reblog/favourite/reply counts, tags, URLs) and covers auth-free access plus the payment/handshake flow. An agent has everything needed to call this correctly and interpret the response.

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?

Schema description coverage is 100%, so the baseline is 3. The description restates the instance default (mastodon.social, or any public instance via instance=) and the 40-post cap, but adds little beyond what the schema already documents; it does not clarify max_id pagination semantics in prose.

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?

States a specific resource (Mastodon hashtag timeline) and scope (up to 40 recent public posts tagged #tag), with the platform named explicitly. The fediverse/Mastodon framing cleanly separates it from the bluesky_*, hn_*, lobsters_* and telegram_* siblings without needing to name them.

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?

"Use for fediverse social listening on a topic or brand hashtag" gives a clear positive use context. There are no explicit exclusions or named alternatives (e.g. when to prefer bluesky_search), so it stops short of a full when/when-not rubric.

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