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Is a chain halal?

is_chain_halal
Read-onlyIdempotent

Whether a restaurant chain serves halal food: how many of its locations are listed and the halal evidence at each one.

Input Schema

NameRequiredDescriptionDefault
chainYesThe chain's name, e.g. "Halal Guys", "Popeyes".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and a closed-world scope, so the safety profile needs no restatement. The description does add return-shape context (location count and halal evidence per location), but it never explains what counts as "evidence" or how a chain is resolved when names are ambiguous.

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?

A single sentence with zero padding, front-loaded with the core question and followed by the shape of the answer. Nothing could be cut without losing information.

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?

For a one-parameter, read-only lookup with no output schema, the description covers both the decision it makes and the evidence it returns. What is missing is minor: how match ambiguity on chain names is handled and what the possible verdicts are.

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?

Only one parameter exists and schema description coverage is 100%, including a maxLength and two concrete examples, so the schema does the heavy lifting. The description adds no matching behavior or normalization guidance beyond what the schema already says.

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 determination (whether a chain serves halal food) plus what the answer includes: location count and per-location halal evidence. The word "chain" implicitly separates it from the location-level halal_food sibling, but it never names that sibling, so the differentiation is left to inference.

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?

There is no explicit when-to-use, when-not, or alternative routing. The chain-level framing implies this is for brand-wide questions rather than a single address, but an agent must guess that halal_food is the alternative for one specific restaurant.

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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