Natal Chart Interpretation

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

Beyond the annotations (which already declare readOnly/openWorld/non-destructive), the description adds genuinely useful operational facts: a 100-credit Tier 4 cost, multi-language output, and token caching for repeat calls. It does not describe latency or output volume, but the cost disclosure is the most important missing piece an annotation cannot carry. Minor tension: 'token-cached for repeats' sits oddly next to idempotentHint=false, though caching is an optimization rather than a guarantee of deterministic output.

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 sentence is front-loaded and waste-free; the bracketed group/endpoint/cost lines are compact metadata that earn their place, especially the cost. Slight structural noise from three bracketed lines, but nothing is redundant.

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 a full output schema, rich annotations, and 100% schema coverage, the description only needs to sell purpose, cost, and caching — all present. The remaining gap is sibling disambiguation against the natal narrative/report tools, which matters given how many near-neighbours exist in this API.

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 deeply documented body schema (date/time/latitude/longitude, timezone vs timezoneOffset, houseSystem letters, ayanamsa) does all the parameter work. The description contributes only the word 'multi-language', which hints at the language field but adds no format or default detail. Baseline 3 is appropriate when the schema carries the load.

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 description gives a specific verb+resource ('Generate AI interpretation of a natal chart') and enumerates the output content (personality traits, life themes, strongest archetypes), so the agent knows exactly what it produces. It does not, however, distinguish itself from close siblings such as astroway_reports_ai_natal_narrative or astroway_reports_natal, which appear to cover overlapping ground.

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 no when-to-use / when-not-to-use guidance and no named alternative. The '[Group: AI Interpretations]' tag only implies the family; an agent choosing between this, astroway_ai_interpret_placement, and astroway_reports_ai_natal_narrative gets no routing signal.

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