Curagent Title Risk

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

No annotations provided, so description carries full burden. It discloses the credit cost, scope limitation to Florida, prerequisite calls, and the output structure (composite score, findings, cure guidance). It does not mention failure modes or timeout behavior but provides substantial context beyond minimal.

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 compact, front-loaded with the core purpose, and every sentence adds useful information (scope, prerequisites, cost, document types). No filler or 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?

Even without an output schema, the description explains the return value structure (composite score, findings, AI cure guidance). It also covers prerequisites, cost, and scope, making it fully sufficient for an agent to invoke 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?

Schema coverage is 100% with a single parameter described, but the description adds significant value by enumerating acceptable document types (deed, title commitment, mortgage, closing disclosure, etc.) and clarifying base64 encoding, which goes beyond the schema's 'base64-encoded string'.

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 analyzes Florida real estate title documents and returns a structured risk report with a composite score, findings, and AI cure guidance. This specific verb+resource+output distinguishes it from siblings like check_coverage and get_credit_balance.

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 states when to use (for Florida properties only), prerequisites (call check_coverage first, get_credit_balance to confirm credits), and cost implications (uses one analysis from monthly allowance or 1 credit). This is strong usage guidance.

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 provided, the description carries the burden. It transparently notes that the tool returns information and highlights a critical limitation (Florida only), which goes beyond a generic read-only hint. It does not explicitly state side effects, but as a pure query tool, the absence of side effects is implied.

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 three sentences that are front-loaded with the primary purpose, followed by a direct usage instruction and a key scope detail. Every sentence 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?

Despite having no output schema and zero parameters, the description fully explains what the tool returns, when to call it, and the current geographic limitation. This is sufficient for an agent to select and invoke the tool correctly within the context of the sibling tools.

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. There are no parameter details needed; the description focuses on the output contents, which aligns with the empty 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?

The description clearly states it returns supported US states, document types, and pricing, which is a specific verb+resource. It is distinct from the sibling tools analyze_title_documents and get_credit_balance, as it answers coverage questions rather than performing analysis or checking credits.

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 instructs to 'Call this before analyzing to confirm the property's state is in scope,' providing a clear when-to-use directive. It also gives a concrete example of current Florida-only support, helping the agent decide if this tool applies.

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 provided, the description carries the transparency burden. It clarifies the tier-based credit system (sandbox free allowance, paid tiers consume credits) and implies this is a read-only operation by stating it 'returns' balance. It does not explicitly state that the check itself consumes no credits, but the context is sufficient 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?

The description is two sentences, front-loaded with the primary purpose, and every sentence adds value. The first states what it returns, the second explains when to use it and clarifies the credit model. No fluff or 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?

For a simple, zero-parameter getter with no output schema, the description is complete. It covers what the tool returns (balance and tier), when to use it, and relevant business rules about tiers and credits. No critical information is missing.

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, and the schema is trivially complete with 100% coverage. The description adds no parameter-specific details because none are needed; the baseline of 4 for no-parameter tools 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?

The description clearly states the tool returns the caller's remaining credit balance and tier, using specific verb and resource (get_credit_balance). It distinguishes from siblings like analyze_title_documents and check_coverage by focusing on credit status rather than analysis or coverage.

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 explicitly advises calling this tool before analyzing to confirm available usage, providing clear context. It does not mention alternatives or when not to use it, but the 'before analyzing' instruction gives a strong usage cue.

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