record_result

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds genuinely useful detail about the EISV measurement semantics (ranges, mixed-provenance estimates, EMA smoothing, interpretation of Valence), which explains what the tool computes. However, it does not disclose the write/side-effect behavior of recording (persistence, state mutation, reversibility) or any response-shape expectations beyond EISV fields.

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 compact, front-loaded with the purpose, and every part earns its place: the EISV field definitions are dense but precisely defined with ranges and provenance notes. The acronym density (EISV, EMA, E-I) is a minor readability cost, and the 'implemented by outcome_event()' clause is slightly implementation-flavored, but overall it is tight and information-efficient.

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?

For a complex 14-parameter tool with no output schema and no annotations, the description explains the core EISV return semantics well but omits the practical call flow: what effect recording has, what a 'lite' snapshot contains, and how prediction_id/verification_source fit into the workflow. The schema covers parameter fallbacks, so the main gap is the absence of an end-to-end behavioral overview and explicit side-effect disclosure.

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 baseline is 3 and the schema already documents all 14 parameters in detail. The description adds value mainly by explaining the EISV ontology, which clarifies the meaning of include_semantics and response_mode, but it does not add meaning to most individual input parameters. This is acceptable given the schema's thoroughness.

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 a specific verb and resource: 'recording outcomes', and labels the tool as the 'Primary workflow name' for that purpose, which signals it is the canonical entry point. It does not explicitly contrast itself with siblings like store_finding or update_finding, so it lacks the explicit sibling differentiation required for a 5.

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 phrase 'Primary workflow name for recording outcomes' gives an implied usage context: this is the go-to tool when an outcome needs to be recorded. However, there is no explicit when-to-use vs. when-not-to-use guidance, no named alternatives, and no prerequisites or exclusion criteria, so the guidance stops at implication.

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