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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the burden is light. The description still adds meaningful context beyond them: the underlying openFDA US-label data source, the specific substances flagged, and the deliberate 'ruling on necessity' framing that prevents users from abandoning prescribed medicine. Only the result format details (e.g. pagination, error behavior) remain unstated.

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 first two sentences ('Halal or Not. Is this medicine halal?.') merely restate the title and tool name and could be dropped. The remaining sentence is dense and front-loaded with the important material, but the redundant lead costs it.

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?

With no output schema, the description reasonably covers returns by naming ingredient_headline and verdict and describing the headline/say line ordering. For a single-parameter, closed-world read tool with full annotations, the agent has enough to call it correctly, though the response shape is only partially sketched.

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% and the single 'name' parameter is documented in-schema as 'Brand or generic name.' The description adds no format, casing, or disambiguation guidance beyond that, so the baseline 3 for a fully-covered single parameter is appropriate.

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 and resource ('Reads a medicine's active and inactive ingredients from its US label (openFDA) and flags gelatine, alcohol, pig-derived enzymes and heparin'), which cleanly separates it from siblings like check_ingredients, explain_ingredient, and check_product_by_barcode. The data source (openFDA US label) further pins down scope for an agent choosing among halalornot tools.

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?

There is no explicit when-to-use, when-not-to-use, or named alternative among the halalornot siblings. The reader can infer the tool applies to medicines, but nothing routes the agent between this and check_ingredients or explain_ingredient when a query is ambiguous.

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