conservation_check

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

No annotations are present, so the description must carry full burden. It discloses the invariant checked and return fields but omits side effects (likely read-only), permissions, or error conditions. The behavioral footprint is partially clear but not comprehensive.

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?

Two sentences efficiently convey purpose, condition, and return fields. No filler or repetition. Every sentence adds value.

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 has moderate complexity (mathematical invariant) and no output schema. The description names return fields but not their types or meanings (e.g., what 'total' or 'delta' represent). It is adequate but lacks depth for an agent to fully predict behavior.

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% with basic descriptions for gamma and eta. The description adds meaningful semantics: gamma is 'compute invested', eta is 'entropy produced', and the inequality condition links them. This goes beyond the schema alone.

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's purpose: verifying SuperInstance conservation invariants with a specific inequality (γ + η ≤ C). It names return fields (validity, total, delta, message), distinguishing it from sibling tools like fleet_agents or ternary_validate.

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 usage context ('Verify that a code change or operation maintains...') but provides no explicit when-to-use, when-not-to-use, or alternatives. It does not differentiate from siblings like fleet_budget or ecosystem_stats, which may also involve checks.

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