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Estimate the percentile of an AP score

estimate_ap_percentile
Read-onlyIdempotent

For an AP exam, year and score from 1 to 5, returns the percent of test takers who scored lower, the same and higher, and the midpoint percentile rank, from the official College Board distribution. Uses exact counts for 2024 and 2025 and the published whole percents for 2026.

Input Schema

NameRequiredDescriptionDefault
examYesAP exam name or common short name, e.g. "AP Biology", "APUSH", "Calc BC", "Lang", "Physics 1", "APES".
yearNoExam year (May administration). Available: 2024, 2025, 2026. Default 2026, the latest College Board release.
scoreYesAP score, 1 to 5.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, closed-world), so the description's added value is the provenance and precision disclosure: exact counts for 2024/2025 but whole published percents for 2026, which tells the agent the 2026 figures are coarser. That is genuine behavioral context a caller needs in order to interpret results correctly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no filler: the first gives inputs and outputs, the second gives year-specific data provenance. Front-loaded with the resource and return values, so the agent gets the essentials first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by enumerating the returned fields and their meaning. Combined with annotations, an agent has what it needs; only failure behavior for an unrecognized exam name is left unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the field descriptions already document exam aliases, the year range with its default of 2026, and the 1-5 score bound. The description mostly restates those bounds ('score from 1 to 5') rather than adding new syntax or edge-case meaning, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (estimate) plus the resource (percentile of an AP score) and enumerates exactly what comes back: percent lower/same/higher and midpoint percentile rank. It is clear enough to separate from list_ap_exams and compare_ap_exams, though it never explicitly contrasts itself with the closest sibling, get_ap_score_distribution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The framing 'For an AP exam, year and score from 1 to 5' implies the usage context, and the year note signals which years are valid. But there is no explicit when-to-use guidance and no naming of the alternative (get_ap_score_distribution) for callers who want raw counts rather than rankings.

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

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