get_system_rules

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds context about the content (what each system measures, consensus synthesis) and the typo-tolerant behavior, which goes beyond annotations. No contradiction exists.

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 well-structured, front-loaded with the main purpose, and each sentence adds value (what it returns, when to use it, parameter usage, authority). It's a bit long but not wasteful; the emphasis on 'GROUND' and 'Authoritative reference' is purposeful.

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 explaining the return content: what each system measures, the rules for reading, and how consensus is synthesised. It also covers the omit case (system overview). For a read-only reference tool with one optional parameter, nothing an agent needs to call it correctly is missing.

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 coverage is 100% – the schema already documents the optional system parameter and its omission behavior. The description adds a bit of context (the purpose of the parameter in grounding answers) but largely repeats the schema's description. This matches the baseline of 3 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 clearly states the tool returns Mythsensus's canonical interpretation rules, with a specific verb ('Return') and resource (the reference methodology). It distinguishes from siblings like list_26_systems and get_deep_reading by specifying that it provides the authoritative framework for reading systems and forming consensus, not just a list or a reading.

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 to use it: to GROUND a divination/astrology answer in Mythsensus's framework instead of improvising. It also gives parameter guidance: pass a system for that system's ruleset, omit for consensus methodology. However, it doesn't explicitly state when not to use it (e.g., for a specific reading, use get_deep_reading), though the purpose is clear enough.

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