DoorProfit Crime & Neighborhood Data

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it explicitly states 'Takes no arguments — it always describes the calling key, never another account' and 'This is the only tool that never consumes quota,' two non-obvious behavioral traits an agent would otherwise not know. This is a strong addition; a 5 would require even richer detail on output structure or rate-limit nuances.

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 sentences, each earning its place: the first states the report contents and scope, the second gives concrete usage triggers, the third adds the unique no-quota-consumption trait. No filler, no repetition of schema information, front-loaded with purpose.

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?

The output schema exists, so return-value details are handled structurally. The description covers what the tool reports (plan, usage, quota, resets, limits, overage), when to call it, its zero-argument nature, and its unique non-consuming property. For a 0-parameter read-only tool with strong annotations, this is complete.

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 are 0 parameters, so the description's job is to confirm the no-argument contract, which it does explicitly ('Takes no arguments'). The baseline for 0 params is 4, and the description earns the extra point by explicitly stating the no-arguments contract and clarifying that it always operates on the calling key, removing ambiguity about what 'no arguments' might default to.

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 ('Report') with a clear resource ('the plan, monthly and daily call usage, remaining quota, reset times, rate limit and overage status') and explicitly scopes it to 'the DoorProfit API key authenticating this session,' distinguishing it from any other-account tool. It clearly differentiates from siblings like get_crime_data and get_neighborhood_data, which handle different domains entirely.

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 explicit when-to-use guidance: 'Call it when the user asks how many calls they have left, or after any other tool returns QUOTA_EXCEEDED or DAILY_LIMIT_EXCEEDED.' It also adds a concrete workflow suggestion ('before suggesting an upgrade'), giving the agent actionable context beyond the schema.

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, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the safe-read profile is well covered. The description adds meaningful context beyond annotations: quota consumption (1 call per key), a free test address exception, and data scope (rolling 90-day window, 1000ft radius). Doesn't describe pagination/limits on incident lists, but covers key behavioral traits.

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?

Reasonably compact single paragraph covering purpose, exclusions, alternatives, and constraints. Every sentence earns its place, though it is denser than strictly necessary and could be broken into shorter sentences for scanability. It is front-loaded with the core purpose then fills in usage nuance.

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?

An output schema exists so return-value explanation is not the description's job. For a moderate-complexity query tool with rich annotations, the description covers purpose, scope, constraints, quota cost, free test address, exclusions, and alternatives. Fully adequate for an agent to select and correctly invoke this 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 description coverage is 100%, so the schema already documents all three parameters well (lat, lng, address with mutual exclusivity). The description reinforces that address OR lat+lng should be passed, not both, and notes US-only locations. This aligns with the baseline-3 for high schema coverage; the description adds minimal supplementary meaning beyond reinforcing exclusivity.

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?

Purpose is explicit and specific: returns a crime safety grade (A+ through F), per-crime-type breakdown versus national average, and incidents within 1000ft over 90 days. It names the exact resource (crime data & safety score) and clearly distinguishes from siblings by spelling out exclusions.

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?

States when to use ('is this address/neighborhood safe?' questions) and explicitly names alternatives for excluded topics: get_neighborhood_data for demographics/income/rent/schools and search_offenders for registered offenders. Also warns against passing both address and lat+lng, and specifies US-only and API key/quota requirements.

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, destructiveHint=false, and idempotentHint=true, so the safety profile is established. The description adds valuable behavioral context beyond annotations: quota consumption (1 call), requires an API key, the neighborhood field can be null when no data exists, and a free test address exception. This is strong supplementary transparency.

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 information-dense but organized logically: what's returned, when to use, when not to use, input rules, edge case (null neighborhood), and constraints (US only, API key, quota). Front-loaded with the data profile. Slightly long but every sentence carries distinct value with 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?

For a read-only, idempotent, open-world tool with an output schema and 100% schema coverage, the description covers purpose, boundaries, input constraints, edge cases, and operational requirements. There's an output schema present, so return-value documentation is handled structurally. Nothing essential is missing for this moderate-complexity 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% (all 3 parameters documented in schema), so baseline is 3. The description adds the mutually-exclusive constraint between address and lat+lng and specifies address format with an example, going slightly beyond schema. However, it doesn't describe lat/lng ranges or precision requirements beyond what schema provides.

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 verb+resource (Profile of the neighborhood/census block group) and enumerates the specific data dimensions returned: demographics, income, home values, rent, education, cost-of-living, climate/disaster risk. It also explicitly distinguishes itself from get_crime_data, a sibling tool, by stating what it does NOT return.

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 explicit when-to-use guidance ('Use this when the question is about who lives in an area or what it costs to live there'), explicit when-not-to-use with the named alternative ('Do NOT use it for crime or safety scores (use get_crime_data)'), and input constraints ('Pass either address or lat+lng, not both', 'US locations only'). This is exemplary 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is safe. The description adds valuable behavioral context beyond annotations: results include distance from search point, radius default/cap, pagination details (page, limit, max 100), and importantly that each page request requires a DoorProfit API key and consumes 1 call. This is meaningful disclosure beyond the structured 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 densely informative with no wasted sentences, covering modes, parameter grouping, precedence rules, exclusions, and API-usage implications in a compact form. It could be split into clearer sub-sections for readability, but every sentence earns its place and the critical information (mode selection, API key cost) is front-loaded.

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 12 parameters and no required fields, the description fully explains mode selection, parameter constraints, precedence, pagination, and API call costs. The output schema exists so return-value documentation is handled structurally. For a complex multi-mode tool, this is remarkably complete.

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 the schema fully documents all 12 parameters. The description adds value by explaining parameter relationships and constraints beyond what the schema states: which params belong to which mode, the 'three filters alone not accepted' rule for city/state/zipcode, radius default/cap semantics, and pagination defaults. This exceeds the baseline 3 for full coverage documents.

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 verb (search) and resource (US registered offenders), and explicitly defines two operation modes (location and name) with their respective parameter requirements. It distinguishes itself from the sibling get_crime_data by specifying this tool is only for registered-offender questions.

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 provides explicit when-to-use guidance and names the alternative (get_crime_data for safety grades). It also specifies mode-specific requirements — location needs address or lat+lng, name needs at least one of first_name/last_name/dob — and states that location takes precedence when both are supplied. This is model guidance.

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