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

Annotations already declare read-only, non-destructive, open-world behavior, so the bar is lower; the description still adds real behavioral facts beyond them — a 10-turn history ceiling, 21 output languages, four selectable voices via persona, and a concrete pricing rule (5 credits with your own provider key vs. the endpoint price). It stops short of stating auth requirements or what happens when the history limit is exceeded. No contradiction with annotations.

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?

Three tight sentences: the differentiator first, capabilities second, pricing last, followed by a compact metadata block (group, endpoint, required param, tier cost). Every clause carries new information and nothing is repeated from the schema.

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 an output schema present the description needn't explain return values, and annotations cover the safety profile, so what remains — what the tool is for, its capability envelope, and its cost model — is covered. The main gap is that nothing tells an agent when this endpoint should be picked over the other AI/agent siblings.

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?

Top-level schema description coverage is only 43% (chart, fields and precision documented; message, persona, language and history not), so the description must compensate and partially does — it explains persona (four voices), history (~10 turns) and language (21 options). It says nothing about chart, fields compact-mode paths, or precision, though the nested chart schema does carry unusually rich self-documentation for those.

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 verb and resource — an AI chat answered from computed natal-chart positions rather than the model's prior knowledge of a sun sign — and quantifies scope (10 turns, 21 languages, 4 personas). It clearly implies a different product from sibling AI utilities such as astroway_mcp_ai_explain_aspect or astroway_mcp_ai_comparison_coach, but never names them, so the differentiation is by tone rather than explicit contrast.

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?

Usage context is implied rather than stated: the credit-price note ('send your own provider key and the turn costs 5 credits instead of the endpoint price') hints this is a paid, higher-tier call, and 'chart-grounded' hints the input needs birth data. There is no explicit when-to-use-it, when-not-to, or routing rule against the other chat/agent endpoints in the sibling list.

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