forms

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

No annotations provided, so the description carries the full burden. It discloses the return payload (description, regulatory citation, exact fields, print/Pass options) and the ID source, making the operation's behavior reasonably clear. It omits edge cases like invalid IDs or auth, but these are not critical for a simple getter.

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?

Single sentence, well-structured with action first and a list of returned content. No wasted words.

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 one-parameter get tool with no output schema or annotations, the description adequately covers purpose, input source, and return content. It is complete enough for an agent to decide when to use it and what to expect.

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 already documents the id parameter with an example. The description adds meaning by stating the id comes from search_forms and identifying the form as an actual form with fields and a regulatory citation, going beyond schema.

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?

Clear verb+resource: 'Get full details for one form by its id.' Explicitly lists the returned content (description, regulatory citation, exact fields, free print/Pass options) and references search_forms as the source of IDs, distinguishing it from siblings like get_form_maker_pass and search_forms.

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?

Implies usage: call this after search_forms to retrieve full details for a known form ID. It does not explicitly name alternatives or exclusions, but the 'from search_forms' hint provides a clear workflow context.

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?

No annotations are provided, so the description carries the burden of behavioral disclosure. It mentions 'pricing and checkout links' which implies a read-only retrieval, but it does not explicitly state that no purchase is made, nor does it describe the response format or any side effects. The product benefits are detailed, but the tool's own behavior remains somewhat implicit.

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 description is a single, well-structured sentence that front-loads the core purpose (pricing and checkout links) and then expands with relevant details about the pass's benefits. Every phrase adds value, with no redundant or filler content.

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?

Given the tool's simplicity (no parameters, no output schema), the description provides sufficient context for the agent to understand the tool's role and what it returns (pricing, checkout links). It could be improved by explicitly stating the response format, but it is otherwise complete for a basic informational tool.

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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific meaning because there are none, but it does clarify the context of the tool (pricing/checkout) which helps the agent understand what to expect without needing parameters.

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 clearly states the tool's function: providing pricing and checkout links for the Form Maker Pass. It uses a specific resource (the pass) and distinct purpose (pricing/checkout), setting it apart from sibling tools that deal with forms themselves.

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?

The description implies usage when a user needs pricing or purchase information for the Form Maker Pass, but it does not explicitly state when to use this over alternatives or provide any exclusion criteria. No direct comparison with sibling tools is given, making the guidance implicit rather than explicit.

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?

No annotations are provided, so the description carries the burden. It discloses that the tool returns categories, their coverage, and form counts, which is sufficient for a simple listing. However, it does not explicitly state whether it is read-only or if any side effects exist, though this is implicitly expected.

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 description is a single, well-structured sentence that leads with the primary action and then adds relevant details (examples, coverage, counts). Every word earns its place, and there is no redundancy.

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?

Given the simplicity of the tool (no parameters, no output schema), the description fully captures everything an agent needs to know: what it lists, what information it provides, and how it differs from sibling tools. No further details are required.

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?

The tool has zero parameters, so the description does not need to elaborate on parameter usage. The baseline for 0 params is 4, and the description appropriately focuses on the output content rather than input details.

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 uses a specific verb ('List') and identifies the resource ('form categories'), with examples of category types. This clearly distinguishes it from sibling tools like get_form or search_forms, which operate on individual forms rather than providing an overview.

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?

The description clearly implies when to use this tool (when needing an overview of categories with counts and coverage), and the sibling names suggest alternatives for form-level operations. However, it does not explicitly state exclusions or mention when to prefer another tool.

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?

With no annotations, the description discloses that the tool returns matching forms with citations and free fill-and-print URLs, which is key behavioral context. It doesn't mention rate limits or auth, but as a read-only search tool this is acceptable.

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 dense sentence that front-loads the tool's purpose, lists supported form types, and gives examples. No fluff, but it's a bit long; still efficient.

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?

Given no output schema, the description adequately states return content (citations and fill-and-print URLs). It covers the scope of forms and search capabilities, making it complete for a search tool.

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 fully describes query and limit. Description adds value by providing concrete alias examples ('FLHA', 'form 1.2', 'hot work'), enriching the meaning of the query parameter beyond the schema.

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?

Clearly states it searches Blue Crane's compendium of 126 Canadian contractor forms with specific scope (Ontario, Alberta, BC, Canada-wide). Uses specific verb 'Search' and resource 'compendium of contractor forms', distinguishing from sibling tools like get_form or list_categories.

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?

Provides clear context on what kinds of searches are supported (keyword, form number, alias) and gives examples, but does not explicitly contrast with siblings like get_form or which_form_do_i_need.

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?

With no annotations, the description carries the full behavioral burden. It discloses the input style, the output (matching forms with citations and free print links), and the 'guidance only, not legal advice' caveat. It doesn't cover edge cases like no matching forms, but for a simple one-parameter tool this is reasonably transparent.

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 description is a single well-structured sentence with illustrative examples and a disclaimer. Every part earns its place with no redundancy or filler.

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?

Given the low complexity, single parameter, and no output schema, the description is complete: it covers input, output, and important caveats. The agent knows how to invoke it and what to expect.

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?

The schema covers the sole 'situation' parameter at 100%, and the description enriches it with concrete examples and explicit 'plain language' instruction. This adds clear semantic meaning beyond the schema's minimal 'The situation, in plain language'.

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 clearly states what the tool does: users describe a jobsite or paperwork situation in plain language and receive forms that fit. The concrete examples and mention of citations/free print links distinguish it from sibling tools like get_form or search_forms, which are more direct retrieval/search operations.

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?

The description frames when to use the tool: when you have a situation in plain language and need form guidance. It provides clear context but does not explicitly contrast it with alternatives or state when not to use it, so it stops short of full exclusion guidance.

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