IQInsight – IQ Percentile & Score Guide

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

Annotations already establish that this is a safe, read-only, idempotent, non-destructive operation. The description adds meaningful behavioral context by stating the fixed normal-distribution assumptions and warning that the result is not a clinical interpretation or observed rank.

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 two concise sentences with no wasted language. The core purpose and the key caveat are both front-loaded.

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 simple one-parameter calculation tool with full schema coverage, annotations, and an output schema, the description provides enough context: it explains the statistical model and sets appropriate interpretation limits.

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?

There is only one parameter, and schema coverage is 100%, so the schema already documents the score range and fixed mean/SD assumptions. The description reinforces those assumptions but does not add syntax or meaning beyond the schema.

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 uses a specific verb and resource: it calculates a theoretical normal-distribution reference for a supplied score, with fixed mean 100 and SD 15. It is clear what the tool does, but it does not explicitly distinguish itself from the sibling explain_iq_score tool.

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 clarifies that this is a theoretical reference, not a clinical interpretation or observed participant rank, which implies when not to use it. However, it does not explicitly say when to use this tool versus explain_iq_score.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine context beyond them: the explanation is drawn only from published guides and carries stated limitations, and it explicitly excludes private/test data as a source.

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, no filler, and the core action plus its sourcing are front-loaded ahead of the privacy exclusion. Every clause earns its place.

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?

An output schema exists, so return values need no explanation, and annotations plus the single fully-described parameter leave little uncovered. The only real gap is the absent sibling differentiation from calculate_iq_percentile.

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% – the range, whole-number constraint, mean 100 and SD 15 are all documented in the schema. The description adds nothing about the single score parameter, so the baseline 3 applies.

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?

States a specific verb ('Explain') and resource ('a supplied score'), and names the knowledge source ('published IQInsight educational guides and limitations'). It never references the sibling calculate_iq_percentile, so an agent must infer the boundary between explaining a score and computing a percentile from it.

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 second sentence gives a clear negative boundary – it does not read test results, questions, private reports or personal data – which usefully tells an agent this is a public-reference-only tool. It stops short of stating when to pick this over calculate_iq_percentile.

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