mark_decision_outcome

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

With no annotations, the description carries full burden. It explains the outcome constraint and return format, but lacks details on side effects, idempotency, or permissions.

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?

Purpose is front-loaded, and the description uses clear structure with a list of outcomes and a rule. Some formatting could be streamlined, but it is efficient overall.

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 7 parameters with no schema descriptions and no annotations, the description only partially covers the tool's usage. Optional parameters are unexplained, making it incomplete for an agent to use correctly without prior knowledge.

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 0%, so description must compensate. It explains 'outcome' values and mentions 'evidence_refs' in a rule, but does not describe other parameters like reason, severity, applies_to, corrected_rule.

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 records the real-world outcome of a past decision, listing valid outcome values. It distinguishes from sibling tools focused on findings or reads.

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?

Provides usage context by explaining the required evidence_refs for certain outcomes. However, it does not explicitly state when to use this tool vs. alternatives or when not to use it.

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