MonsiTools Calculators

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

With readOnlyHint=true and openWorldHint=false already declared, the description still adds genuinely useful operational context: a 10-calculations-per-day-per-IP anonymous limit and the exact Authorization header format for a Premium key. It does not explain error behavior or what the result object looks like.

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?

Three tight sentences with the core action front-loaded, followed by auth/limit details. Every sentence carries information; only the redundant restatement of 'returns the result' is marginal.

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 read-only, nested-input tool with no output schema, the description covers action, cost/rate limits, and auth. The only gap is the shape of the returned result, which 'returns the result' leaves unspecified, though a calculator's output is largely predictable.

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%, so both parameters (slug, inputs) are already documented in the schema, including the nested number map. The description adds no parameter-level detail, which is the correct baseline when the schema does the heavy lifting.

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 ('Runs a MonsiTools calculator') plus the immediate effect ('returns the result'). This is clearly distinguishable from describe_calculator and search_calculators, which are discovery tools, though the description never names those siblings explicitly.

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?

Usage is implied rather than stated: an agent can infer it should call search_calculators first to obtain a slug, but only because the schema says so, not the description. There is no explicit when-to-use/when-not guidance or routing to alternatives.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered and the description's enumerated return fields add genuine value about what comes back. However, it says nothing about behavior for an unknown or malformed slug (error vs empty), which is the main behavioral question left open for a lookup tool.

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?

One sentence, zero waste, with the return payload front-loaded and the required input placed in its natural trailing slot.

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 compensates well by enumerating the returned fields, and the read-only lookup shape is fully covered by annotations. The only material omission is failure behavior for a nonexistent slug.

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 a single 'slug' parameter with 100% schema description coverage, including an example value, so the schema carries the parameter burden. The description's phrase 'given its slug' matches the schema rather than adding format or validation detail beyond it, which is the baseline case.

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 states a specific verb ('Returns') and resource ('a calculator's'), then enumerates exactly what is returned (name, category, formula, input names, page URL) and the key it is looked up by (slug). This clearly separates a metadata lookup from the sibling 'calculate' (which would compute) and 'search_calculators' (which would query), though it never names those alternatives explicitly.

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 statement of when to use this tool versus 'calculate' or 'search_calculators', and no preconditions or exclusions are given. An agent must infer from the verb 'Returns' that this is a lookup rather than a computation.

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context the annotations lack: it discloses the return shape (slug, name, category, input names) and that matching spans names, categories, and input names, which matters since no output schema exists.

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, zero waste, front-loaded with purpose followed by the workflow hand-off. Each clause carries information.

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 3-param read-only search with no output schema, the description supplies the missing return-shape information and the downstream pipeline, so an agent has everything needed to call it and use the result.

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%, so the schema already documents query, limit, and category. The description's example keywords illustrate query semantics but add no syntax or constraints beyond what the schema provides, so 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+resource ('Find MonsiTools calculators by keyword') and gives concrete example keywords. It also names the sibling tools it is not, so an agent can place it in the workflow without opening a schema.

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?

Explicitly routes the agent: use describe_calculator for details, then calculate to run one. This names the alternatives and the condition that selects them, which is exactly what usage guidance should do.

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