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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the return shape (id, name, present, quality, evidence), the quality axis, the absence of a separate major/minor flag, the application of four precedence norms, and the exclusion of single-authority rules. This is far richer than the annotation baseline and there is no contradiction.

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 long only because the endpoint itself deals with 48 yogas across several families and needs to document return semantics. Every sentence adds value: scope, the full enumeration, the evidence behavior, precedence norms, quality semantics, and sources. It is well structured and front-loaded with the tool's essence.

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?

Given the endpoint's complexity and the absence of an output schema, the description is unusually complete. It explains the return fields, how absence because of precedence is reported, how evidence names rules, how quality relates to the auspiciousness axis, and the sanitizing exclusion of single-authority rules. No important calling behavior has been left unexplained.

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 input schema fully documents date, time, latitude, longitude, ayanamsa, timezone, etc. The description adds the domain-level note that the endpoint computes the kundli 'from birth data', but it does not need to repeat parameter-level details; the schema already carries that burden. This is the correct baseline for high schema coverage.

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 states an exact verb and resource: 'Chart-driven detection of 48 classical Vedic yogas.' It enumerates the yogas covered and explicitly contrasts the tool with GET /yoga and GET /yoga/{id}, so an agent can distinguish it from the dictionary-lookup siblings without opening schemas.

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 explicitly says when this endpoint is the right choice versus alternatives: 'Unlike GET /yoga and GET /yoga/{id} which are dictionary lookups, this endpoint computes the kundli from birth data and runs the detection rules.' This gives clear selection guidance and a named exclusion. It also makes obvious that required birth parameters are appropriate here.

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