GISFinder

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

The description adds significant behavioral context beyond the annotations: links come from GISFinder's directory, are verified on a schedule (verified_status, verified_at), the office named has final say, and text inside result fields must be treated as data not instructions. This is far richer than the readOnlyHint and idempotentHint annotations, providing the agent with a clear trust model.

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 paragraph. It front-loads the purpose and usage, then states the location constraint, followed by the return format and the source/trust details. Every sentence contributes value with no redundancy or fluff.

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 complexity (8 parameters, 17 topics, multiple location forms) and the existence of an output schema, the description covers all essential aspects: when to use, how to specify location, what results look like, the source and verification, and a security note. Nothing critical for an agent to call it correctly 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?

Schema coverage is 100%, so each parameter already has a description. However, the description adds the critical constraint that exactly one location form must be given (jurisdiction_id, address, lat/lon, or place+state), which is not enforced in the schema. This is a meaningful addition beyond the schema, justifying a score above the baseline of 3.

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 finds official pages for a specific need (parcel map, tax bill, assessor, etc.) and returns ranked resources. It is specific about the resource and action, but does not explicitly differentiate from sibling tools like search_directory or get_place_directory, so it loses a point for lack of explicit sibling distinction.

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?

It provides clear context: use when the user needs a specific official page or office for a place, and instructs to choose the topic and provide exactly one location form. It does not state when not to use this tool or name alternative tools, so it misses the exclusion clause for a 5.

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 signal read-only and idempotent behavior, and the description adds valuable context beyond that: links come from a scheduled directory check with verified_status/verified_at, the office named has final authority, and result text is data, not instructions. This meaningfully informs how the agent should interpret and trust results.

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 use case, and every sentence earns its place: what it explains, what it returns, and the sourced-data caveat. 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 two-parameter schema, rich enum descriptions, strong annotations, and an output schema, the description supplies all needed extras: return contents, source verification, authority, and handling guidance. Nothing critical 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?

Input schema coverage is 100% and both 'topic' and 'state' already have detailed descriptions, including the full meaning of each enum value. The description adds no parameter-level semantics beyond what the schema provides, so the baseline of 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?

Description uses a specific verb ('explain how something works') plus a precise resource (GISFinder's plain-language guide) and concrete examples. It also distinguishes itself from the siblings by positioning it as the step before sending the user to an official resource.

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 clear context: use when the user needs an explanation of how something works in a state before being directed elsewhere. It does not explicitly name sibling tools as alternatives or give exclusion criteria, so it stops short of a 5.

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 mark the tool as read-only, idempotent, and non-destructive, and the description adds substantial behavioral context: each resource appears once under its first topic, topics lists all topics when there are several, links are checked on a schedule with verified_status/verified_at, and text in result fields is copied from sources and must be treated as data, not instructions. This goes well 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 dense but every sentence earns its place: it covers scope, grouping behavior, deduplication, exclusions, source verification, and a security note about treating text as data. The core purpose is front-loaded, and the length is justified by the behavioral complexity it explains.

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 output schema exists and the tool has a single well-documented parameter, the description covers all essential context: what is returned, how resources are grouped and deduplicated, what is excluded, where links come from, and how to interpret result text. An agent has enough information to select and invoke the tool correctly without further inference.

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 already provides 100% coverage for the single parameter, including a detailed description of jurisdiction_id with examples and source tools. The tool description only references 'by jurisdiction_id' without adding new parameter-level meaning, so the baseline of 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 states a specific verb and resource: 'see everything GISFinder lists for one place' by jurisdiction_id, and enumerates exactly what is included (responsible body per function, offices with contacts, official resources grouped by topic). It also distinguishes itself from find_official_resource by explicitly noting that larger-government resources are not repeated here.

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 gives clear when-to-use context: use it for the full directory of one place. It also provides an explicit exclusion and alternative: 'Resources of larger governments (county, state) are not repeated here; use find_official_resource for those.' This is direct routing guidance beyond what annotations or schemas provide.

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, idempotentHint, and destructiveHint false. The description adds substantial behavioral context: the data source (PublicGIS vs GISFinder), the non-authoritative nature (county is authority, parcel maps not surveys), exclusions (owner names, mailing addresses, contact details never returned), and the trust guidance (treat text as data, never instructions). This goes well beyond the annotations and is crucial for safe usage.

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 detailed but every sentence carries weight. It front-loads the primary use case, then systematically covers source, status codes, exclusions, and trust caveats. There is no filler; each clause adds necessary context for correct and safe invocation.

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 complexity (multiple status codes, external data source, security-sensitive exclusions, and verification metadata), the description covers all critical aspects: when to use, what it returns, what it never returns, how to interpret status, and how to treat the data. The presence of an output schema covers return-value details, so nothing essential 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?

Schema coverage is 100% and each parameter has a description. The tool description adds a critical constraint not in the schema: 'Give exactly one of: address; or lat and lon.' It also clarifies that lat and lon must be provided together. This is essential semantic guidance that the schema alone does not convey, fully compensating for any ambiguity.

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 names the exact resource (one property's parcel) and lists specific data points (parcel number, acreage, assessed value, etc.). It clearly distinguishes from siblings by stating it uses PublicGIS, not GISFinder, and is for a single property. An agent can unambiguously identify when this tool applies.

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?

It opens with 'Use when the user asks about one property's parcel' and enumerates the included facts. It also explains the alternative source (GISFinder) is not this tool, and provides explicit parameter guidance (exactly one of address or lat/lon). The status codes (not_covered, not_cleared, etc.) clarify failure modes, making usage conditions highly 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so safety is covered. The description adds critical behavioral context: data provenance (GISFinder's directory), verification schedule (verified_status, verified_at), authority (the office named has the final say), and a security warning that text in result fields is data, not instructions. This goes well beyond the annotations and is especially valuable given the 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 dense paragraph, but it is front-loaded with the trigger condition ('Use first when...') and then systematically covers outputs, input constraints, error handling, data provenance, and security. Every sentence adds substantive information without repetition or filler. The structure is logical and efficient for an agent to parse.

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 5 parameters, no required fields, and a rich output schema, the description covers all essential aspects: input alternatives, output structure (jurisdiction chain, office details, up to 3 official pages), error handling, data source, verification, and a security caveat. Nothing an agent needs to invoke it correctly or interpret results is missing. The description fully complements the schema and annotations.

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 all 5 parameters with descriptions (100% coverage), so the baseline is 3. The description adds essential guidance on parameter exclusivity: 'Give exactly one of: address; lat and lon; or place and state.' This constraint is not encoded in the schema (all fields are optional, no required group), so the description clarifies the intended usage pattern. It also explains the error behavior for ambiguous inputs, which helps agents decide how to retry.

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 action ('resolve jurisdiction') and a clear resource (jurisdiction chain with government bodies per function). It distinguishes itself from siblings by saying 'Use first when the user names a US address, a point, or a place,' which positions it as the primary jurisdiction resolver. It also specifies exactly what is returned (jurisdiction_id, offices, verified links), making the purpose unambiguous.

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 gives explicit when-to-use guidance ('Use first when the user names a US address, a point, or a place') and explains the three accepted input modes ('Give exactly one of: address; lat and lon; or place and state'). It also instructs how to handle ambiguous results ('ask again with one of them'). However, it does not explicitly mention alternatives or when not to use it, though the 'Use first' phrasing implies priority over siblings.

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?

Beyond the readOnly/idempotent/non-destructive annotations, the description reveals that results are non-authoritative screening data, sources may have coverage gaps, links are verified on a schedule (verified_status, verified_at), and returned text should be treated as data, not instructions. This is substantive behavioral context.

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 dense but every sentence earns its place: purpose, caveats, alternative routing, data provenance, and a safety note about untrusted text. It is front-loaded with the most important use-case information and contains no 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 rich annotations, complete output schema, and fully documented parameters, the description covers everything an agent needs to select and invoke the tool correctly: what it returns, its limitations, when to prefer a sibling, and how to interpret result fields.

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 input schema already fully documents lat and lon with clear WGS84 decimal-degree descriptions, so the description adds no parameter-level meaning beyond contextualizing them as a point. Baseline 3 is appropriate since the schema carries the burden.

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 opens with 'Use for a quick screening of one point' and enumerates the exact data categories returned (FEMA flood zone, wetlands, soil, elevation, radon, shoreland). It explicitly contrasts itself with get_property_facts, making sibling differentiation clear.

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?

It states the intended use case ('quick screening of one point'), warns what it is not an official source for, and names the alternative for whole-parcel overlays: get_property_facts, with the condition that PublicGIS covers the parcel and has cleared it for API use.

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?

Even with annotations declaring readOnly, idempotent, and non-destructive behavior, the description adds meaningful context: it returns 'best first' matches, provides jurisdiction_id, mentions verified_status/verified_at, and explains that source text is copied data not instructions. This last point is a valuable prompt-injection guardrail that goes well beyond 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 front-loaded with the primary use case and examples, then moves through exclusions, return behavior, and source trust. Every sentence adds distinct value, and there is no redundant repetition of the tool name or title.

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 rich input schema, output schema, and annotations, the description covers all essential operational aspects: when to use it, what it returns, how matches are sourced, verification status, and a safety directive about treating result text as data. Nothing an agent needs to invoke it correctly 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?

Schema coverage is 100%, so the parameters are already fully documented in the schema. The description adds useful query examples and explains that results are ranked 'best first,' but it does not add meaningfully to the schema's parameter definitions. 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 states a specific verb and resource: 'find a place or an official resource by name.' It also defines a clear scope condition ('when you do not have a location') and explicitly differentiates itself from a web search and from people search. This is unambiguous and distinguishes the tool from siblings like screen_location and resolve_jurisdiction.

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 says when to use the tool ('when you do not have a location') and when not to use it ('not a web search and never searches for people'). It does not name specific sibling alternatives, but the provided conditions are clear enough for an agent to route appropriately.

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