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

With no annotations provided, the description carries the disclosure burden. It clearly states determinism, pure computation, no LLM involvement, and classical-text citations for yogas, which signals reproducibility and trustworthiness. It does not discuss edge cases or error behavior, but for a pure read-only computation the key behavioral traits are disclosed.

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 description is two sentences with no filler. The first sentence front-loads scope and enumerates the output types; the second adds the crucial no-LLM determinism guarantee and endpoint equivalence. Every clause earns its place.

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?

The tool is complex and has no output schema, but the description compensates by listing the major returned categories: lagna, nakshatra, dasha, house placements, dignities, combustions, D9/D10 ascendants, Sade Sati, yogas with citations, and dasha timeline. It lacks mention of ayanamsa/house-system defaults or error scenarios, but an agent has enough context to invoke and interpret the result correctly.

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 all five parameters are already documented with formats and ranges. The description only groups them under 'birth data' and does not add semantic detail beyond the schema, so the baseline score of 3 applies.

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 uses a specific verb and resource: 'Deterministic Vedic chart facts for birth data' followed by a concrete enumeration of outputs such as lagna, dasha, house lords, and Sade Sati standing. It also distinguishes itself from likely LLM-based siblings with 'Pure computation, no LLM.'

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?

The description implies clear usage: use when deterministic, reproducible chart facts are needed rather than interpretive LLM answers. 'Pure computation, no LLM' provides an implicit when-not, and 'Same output as POST /api/b2b/chart-facts' gives an integration reference, though it does not explicitly name sibling tools.

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