530A Model calculator

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

Annotations indicate readOnlyHint=true and openWorldHint=false. The description adds useful behavioral context: it returns 'verified rules' with primary-source URLs and flags for unverifiable items, which goes beyond the annotation signals. However, it doesn't clarify the closed-world nature implied by openWorldHint=false.

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 key information. Every part is relevant: 'returns verified rules', specifics, URLs, and flags. 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?

Given no parameters, presence of output schema, and annotations, the description is complete. It covers the scope, output format (verified, URLs, flags), and behavioral traits. No additional information seems necessary for an agent to invoke this tool correctly.

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?

No parameters in the input schema, so schema description coverage is 100% trivially. The description compensates by explaining what the tool returns, making the purpose clear. With zero parameters, a baseline of 4 is appropriate and the description meets that.

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 returns 'verified rules of 530A accounts' with specific details like seed, caps, tax treatment, withdrawal ages. It distinguishes from siblings by focusing on legal facts with primary-source URLs and explicit flags for unverifiable items.

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?

No explicit guidance on when to use this tool versus alternatives. Sibling tools (fetch, project_530a, search) are listed but without any context or exclusion criteria. The description implies it's for factual queries, but lacks explicit 'when to use' or 'when not to use' directives.

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?

The description aligns with the readOnlyHint annotation by stating 'retrieve.' It does not cover error behavior or other traits, but the annotation already signals safety, so minimal additional disclosure 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?

A single, front-loaded sentence with no wasted words. All information is essential and efficiently presented.

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 simple retrieval tool with one parameter and an output schema, the description covers the essential use case. It could mention return format details, but the output schema likely handles that.

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 coverage is 100% with a description for 'id.' The description reiterates the source of the id, adding marginal value beyond the schema. Baseline 3 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?

The description specifies the verb 'retrieve,' the resource '530A knowledge document,' and the source of the identifier ('id returned from search'). This clearly distinguishes it from sibling tools like 'explain_530a' and 'project_530a'.

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 indicates the tool should be used after a search, providing clear context. It does not explicitly mention alternatives or when not to use it, but the context is sufficient.

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?

The description adds significant behavioral context beyond the readOnlyHint annotation: the tool is deterministic, uses Monte-Carlo simulation to produce percentile ranges, money is represented as integer cents strings, and cites sourceUrl when quoting. No contradictions with annotations.

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 concise (4 sentences) and front-loaded with the main purpose. Every sentence adds value: core function, data format, determinism, and citation instruction. 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 complex tool with 12 parameters and nested sources, the description covers the core behavior, result format (percentile ranges), and deterministic nature. The presence of an output schema reduces the need to explain return values. However, it omits the alternative share-link input format mentioned in the input schema description, and could provide more on the meaning of percentiles.

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 0%, meaning no individual parameter descriptions. The tool description provides only high-level behavior ('Money is integer cents as strings') without explaining the 12 parameters, their roles, or relationships. This is insufficient given the tool's complexity.

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 deterministically models a 530A account value with Monte-Carlo percentile ranges. The verb 'model' and resource '530A account' are specific, and the output percentiles are listed. This distinguishes it from siblings like 'explain_530a' (explanation) and 'fetch' (retrieval).

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 when to use this tool: for deterministic modeling of a 530A account with Monte-Carlo simulations. It mentions determinism ('same inputs always return identical results') and citation requirement ('cite sourceUrl when quoting'). However, it lacks explicit guidance on when not to use or alternatives, but the context is clear enough.

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 description adds domain context. No additional behavioral traits like rate limits or auth needs disclosed, which is acceptable given readOnlyHint covers safety.

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 concise sentences: first covers purpose and scope, second explains output and usage. No waste.

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 output schema present, description need not detail return values. It covers domain, output purpose, and integration with fetch. Missing details on search behavior (e.g., exact match, result limits) but acceptable for a simple 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 coverage is 100%, so baseline is 3. Description adds context about knowledge domains but does not extend parameter meaning beyond the schema's 'Keywords' example.

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?

Description clearly states verb 'Search', specific resource 'verified 530A knowledge from 530amodel.com', and lists knowledge types. It distinguishes from sibling fetch by mentioning 'Returns result ids to pass to fetch'.

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 by describing output (returning IDs for fetch). Provides context that it covers specific knowledge topics, but lacks explicit when-to-use vs alternatives or when-not-to-use.

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