TypoSafe AI — Jef

Ask Jef to rank things

jef_rank

Read-onlyIdempotent

Put 2 to 5 options in order, best first. Use this when the user wants a priority order decided for them, such as which chore to do first or which of several tasks to start with. Returns every option you passed, reordered, never a subset.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`options`	Yes	The things to order. All of them come back, reordered.

Output Schema

TableJSON Schema

Name	Required	Description
`kind`	No	Which decision shape was used.
`answer`	Yes	The options joined with " > ", best first.
`blocked`	Yes	True when the input contained profanity, slurs or sexual content. Nothing was stored or echoed. Do not retry.
`ranking`	No	The options in order, best first. Null unless the shape was order.
`cost_usd`	No	Always 0. There is no billing.
`thoughts`	No	Always 0.
`escalated`	Yes	True when the input touched health, harm, money, law or safety. Tell the person to ask a human. Do not rephrase and retry.
`confidence`	Yes	0.84 to 0.99 normally, exactly 0 when escalated or blocked. It is not calibrated and means nothing.
`latency_ms`	No	Negative. Jef answers before you ask.
`tokens_read`	No	Always 0. The input is hashed, not read.
`probabilities`	No	One entry per option, percentages summing to 100. Null unless the shape was pick.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 19, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral context beyond annotations: the output preserves all inputs, is reordered, and is never a subset.

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?

Three dense sentences with no filler. The core constraint is front-loaded, the usage context follows, and the invariant return behavior is stated clearly.

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

Completeness5/5

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

For a single-parameter, well-annotated tool with an output schema, the description covers what the tool does, when to use it, and key behavior. Nothing essential for correct invocation is missing.

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%, and the schema already documents options with min/max constraints and the 'all come back, reordered' behavior. The tool description restates this but does not add new parameter-specific meaning beyond 'best first,' which is more of an output ordering rule.

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

Purpose5/5

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

The description states a specific verb and resource: 'Put 2 to 5 options in order, best first.' It clearly distinguishes ranking from the sibling tools by emphasizing that every passed option is returned reordered, never a subset.

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

Usage Guidelines4/5

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

It gives clear context: 'Use this when the user wants a priority order decided for them' with concrete examples. It does not explicitly name sibling tools or state when not to use it, but the use case is specific enough.

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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