zipexplore-mcp

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

No annotations, so description carries full burden. States it returns the same profile shape as get_zip_profile, which is useful. Does not mention side effects or auth, but these are unlikely for a read-only comparison tool.

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 sentences, front-loaded with purpose, 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 simple tool with one parameter, the description covers purpose, usage context, and return shape. No output schema, but the reference to get_zip_profile's shape is sufficient.

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 has one parameter 'zips' (array of strings) with 0% description coverage. The description adds the constraint '2–5 ZIP codes', which is valuable and not present in 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 verb 'compare', resource 'ZIP codes', and scope '2–5'. Distinguishes from sibling tools like get_zip_profile which returns a single profile.

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 says 'Use when the user has finalists and needs to choose between them', providing clear context. Could explicitly mention not to use for single ZIP queries, but get_zip_profile is a sibling.

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 lists the included data types (EPA AQS pollutant levels and AQI summary), which gives a good idea of the output. However, with no annotations provided, it omits important behavioral details such as data freshness, rate limits, or authentication requirements. The description is adequate but not thorough.

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 extremely concise: two sentences that front-load the purpose followed by usage guidance. Every word earns its place without unnecessary elaboration.

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 data retrieval tool with one parameter and no output schema, the description covers purpose, usage context, and high-level contents. It could mention output format or any prerequisites, but overall it provides sufficient context for an AI agent.

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 only parameter 'zip' is a ZIP code, which is self-explanatory. Despite 0% schema description coverage, the parameter is obvious and the description does not need to add further meaning. The baseline of 4 is appropriate given the parameter's clarity.

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 purpose: providing detailed air quality data for a single ZIP code. It uses a specific verb ('get') and resource ('air quality profile'), and distinguishes from the sibling 'get_zip_profile' tool by noting that this tool offers deeper air quality information.

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 states when to use this tool: when 'get_zip_profile' air quality section is insufficient. This provides clear context for selection, though it does not mention scenarios where the tool should not be used or suggest other alternatives.

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 full burden. It discloses that the tool returns 'all body sections and methodology notes exactly as published', indicating a read-only, non-destructive operation. No contradictions. Could add more on availability or permissions, but sufficient given simplicity.

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?

Four sentences, front-loaded with purpose. Every sentence adds value: purpose, usage context, valid slugs, content details. No wasted words 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 tool with one parameter and no output schema, the description covers purpose, usage context, parameter enumeration, and what the output contains. No gaps given the tool's complexity.

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?

Only one parameter 'slug' with 0% schema coverage. The description adds meaning by listing the four valid slugs ('disappearing-towns, hazard-premium, snap-economy, wealthy-retirees'), which is critical for correct invocation.

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 the full prose of a specific ZipExplore research article', specifying the action (returns), resource (full prose), and scope (specific article). It distinguishes itself from the sibling tool get_research by mentioning 'when get_research summaries aren't enough'.

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?

Description provides explicit context for when to use this tool ('for editing, fact-checking, detailed analysis, or when get_research summaries aren't enough') and lists valid slugs. However, it does not explicitly state when not to use it or mention alternatives beyond get_research.

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 full burden. It discloses data sources (Census BDS/CBP) and lists included data types, but does not mention behavioral aspects such as read-only nature, potential errors for invalid ZIP codes, or data freshness. Adequate but could be more 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 highly concise: three sentences covering purpose, usage context, and content list. No redundant or irrelevant information, every sentence earns its place.

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 tool with one parameter and no output schema, the description adequately covers purpose and data contents. However, it lacks details on output format, data granularity, or temporal coverage. Mostly complete but could be more informative.

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 has only one parameter 'zip' with 0% description coverage. The description merely implies it is a ZIP code string via 'one ZIP code', but does not specify format (e.g., 5-digit) or any constraints. This adds minimal value beyond the schema, and given low coverage, compensation is insufficient.

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 specifies the tool's purpose: providing detailed business and employment data for one ZIP code. It distinguishes itself from the sibling tool 'get_zip_profile' by stating it offers deeper business data when that tool's business section is insufficient.

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 states when to use this tool ('Use when get_zip_profile's business section isn't sufficient depth'), offering clear context. However, it does not provide any negative use cases or alternative tools beyond that one comparison, missing some guidelines.

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?

Without annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation through the verb 'get' and lists data contents, but does not explicitly state non-destructiveness, auth requirements, or error handling. Given the tool's simplicity, this is adequate but slightly lacking explicit safety statements.

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 long, with the first sentence stating the core purpose and the second providing usage guidance. Every word is necessary and front-loaded for quick comprehension.

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 tool with one parameter and no output schema, the description covers purpose, usage guidance, and data categories (population, housing, etc.). However, it does not mention error handling (e.g., invalid ZIP) or the return structure, which would be helpful for full completeness.

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 has one parameter 'zip' with 0% description coverage; the description mentions 'ZIP code' but does not specify format (e.g., 5-digit), constraints, or examples. While the meaning is clear, additional details would improve parameter understanding.

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 provides 'Detailed Census / demographics data for one ZIP code', specifying the resource (Census/demographics) and scope (one ZIP code). It also distinguishes from sibling tool get_zip_profile by noting it offers greater depth, effectively differentiating its purpose.

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 to 'Use when get_zip_profile's demographics section isn't sufficient depth', providing direct guidance on when to prefer this tool over a specific alternative. This is clear and actionable.

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 provided, so description fully informs behavior. It details included data (fair market rents, housing cost burden, etc.) and implies a read-only operation, but does not disclose any limitations or side effects.

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 sentences, front-loaded with purpose and usage guidance, no wasted words. Efficiently conveys key information.

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 only one parameter and no output schema, the description provides sufficient context about the tool's data scope and relationship to siblings. Could add detail on return format but not critical.

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 has one parameter 'zip' with 0% description coverage. Description mentions 'one ZIP code' but does not explicitly define the parameter's format, constraints, or example values beyond the tool's purpose.

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 it provides detailed cost of living data for one ZIP code and distinguishes itself from sibling tool get_zip_profile by specifying when to use it instead.

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 advises using this tool when get_zip_profile's cost section is insufficient, providing clear context. However, it does not mention other 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.

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

No annotations are provided, so the description must convey behavioral traits. It lists the returned data fields, which implies a read-only operation, but does not explicitly state safety (no side effects), error handling (e.g., invalid ZIP), or performance considerations. The description provides some transparency but lacks details that would fully inform the agent about expectations.

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-loading the purpose and use case. Every sentence provides value: the first states the action and scope, the second adds depth and differentiation. No unnecessary 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 the tool's simplicity (one parameter, no output schema) and the presence of many sibling tools, the description covers the essential context: what it does, when to use it, and what it returns. It lacks error behavior or rate limits, but for a data retrieval tool, the coverage is adequate.

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%, so the description must supplement. It clarifies that the tool accepts 'one ZIP code,' implying a single string identifier. However, it does not specify the expected format (e.g., 5-digit, numeric string) or provide constraints beyond the schema's title 'Zip.' This adds some meaning but not comprehensive guidance.

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 provides detailed crime data for one ZIP code, with specific components (violent crime rate, property crime rate, data quality flags). It explicitly distinguishes from the sibling 'get_zip_profile' by indicating when to use this tool (when the crime section of the sibling is insufficient). This is a specific verb+resource with clear differentiation.

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 guidance: 'Use when get_zip_profile's crime section isn't sufficient depth.' This tells the agent when to select this tool over the sibling. While it doesn't list other alternatives or negative cases, the guidance is direct and actionable.

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 provided, so description carries full burden. It lists what data is included (FEMA NRI score, hazard scores, annual loss estimates) but does not disclose any behavioral traits like rate limits, authentication, or whether the tool is read-only. Assumed safe but not explicit.

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 states purpose and scope, second provides usage guidance and content overview. No redundancy, each sentence adds value.

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 tool with one parameter and no output schema, the description covers what it does, when to use it, and data content. However, it lacks details on the return structure or data format, which would help the agent process the output. Adequate but not 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 0%, meaning description does not detail the single parameter (zip) beyond stating 'one ZIP code.' While the schema already defines it as a required string, the description adds minimal context that it expects a single ZIP code, but no format details (e.g., 5-digit format). Baseline 3 due to low coverage with slight added meaning.

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 the tool provides 'detailed natural disaster risk data for one ZIP code' and distinguishes from sibling get_zip_profile by specifying when to use this tool over that alternative.

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?

Explicit guidance given: 'Use when get_zip_profile's disaster risk section isn't sufficient depth.' This tells the agent when to choose this tool over the sibling, but no other alternatives or exclusions are mentioned.

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 present, so the description must disclose all behavioral traits. It notes that data may come from the nearest ZIP if no schools exist in the given ZIP, which adds useful transparency. However, it does not mention read-only nature, response format, or any authentication/rate limit implications.

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 concise sentences: first states purpose, second provides usage guidance, third lists data fields and a caveat. Information is front-loaded and every sentence earns its place 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?

Given the simple input (single param) and no output schema, the description covers main purpose, usage guidance, and key data fields. It lacks full details of all possible return fields but includes enough for most use cases.

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% (only param 'zip' has no description). The description says 'for one ZIP code' but does not specify format (e.g., 5-digit string) or constraints, adding minimal value 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?

The description clearly states the tool retrieves detailed school data for one ZIP code, lists specific data points (school counts, ratios, rates, spending, etc.), and distinguishes it from sibling tool get_zip_profile by specifying when to use this tool for deeper education data.

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 directs to use this tool when get_zip_profile's education section is insufficient, providing a clear alternative. However, it does not explicitly state when not to use it or outline prerequisites.

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 provided, so description carries full burden. It describes the returned data comprehensively, but does not explicitly state it is a read-only operation or mention any auth or rate limit constraints. However, the 'get' verb implies non-destructive behavior, and data listing is sufficient for 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 very concise (about 3 lines), front-loaded with purpose, and every sentence provides value. 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 the tool has only one parameter and no output schema, the description fully covers the expected return data (hospitals, nursing homes, beds, shortage areas, pharmacies, urgent cares). It is complete for a data retrieval 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 0% (no description in input schema). The description only says 'one ZIP code' but does not explain the format, validation, or constraints of the zip parameter. This does not add adequate meaning beyond the field name.

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 provides 'detailed healthcare data for one ZIP code' and lists specific data points (hospital count, ratings, nursing homes, etc.), distinguishing it from sibling get_zip_profile's healthcare section.

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 says 'Use when get_zip_profile's healthcare section isn't sufficient depth', providing clear when-to-use guidance and naming the alternative sibling 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?

No annotations are provided, so the description carries full burden. It details what the tool returns but does not explicitly state behavioral traits like read-only, no side effects, or performance characteristics. For a simple documentation retrieval tool, this is adequate but not exceptional.

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 paragraph that front-loads the main purpose and then provides a bullet-like list of contents. It is informative and reasonably concise, though slightly verbose with the list of items.

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, no output schema, and the tool's nature as a documentation guide, the description fully explains what the tool returns. It answers potential questions a user might have about the tool's output.

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 no parameters, and schema description coverage is 100%. According to guidelines, 0 params gives a baseline of 4. The description does not need to add param info.

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 'Returns' and the resource 'ZipExplore's data interpretation guide', and lists specific contents (reasoning guardrails, quality flag definitions, etc.). This immediately distinguishes it from sibling tools that return specific data profiles.

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 states: 'Call this when you have questions about data quality, what a quality_flag code means, why a ZIP has no data, or how to reason carefully about scores and correlations.' This provides clear guidance on when to use this tool versus others.

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 of behavioral disclosure. It explains that each entry includes a key finding, quantitative results, caveats, and a URL. This gives a transparent view of the tool's output, though it does not address potential limitations or rate limits.

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 appropriately sized, front-loaded with core functionality, and efficiently conveys purpose, examples, output details, and usage guidance without unnecessary information.

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 that there are no parameters, no output schema, and no annotations, the description adequately covers the tool's purpose and output structure. It is sufficient for an agent to understand when and how to invoke the 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 input schema has zero parameters, and schema description coverage is 100%. The description adds value by explaining the content and structure of the returned data, which is meaningful beyond 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 that the tool returns ZipExplore's published research articles, listing example topics. It distinguishes the tool as a collection of articles but does not explicitly differentiate from the sibling tool 'get_article', which may fetch a single article. Thus, purpose clarity is high but not fully differentiated.

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 provides usage guidance: 'Call this when a user asks about these topics or when published findings would add context to a live data lookup.' This is clear context for when to use the tool, though it does not mention when not to use it or alternatives.

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 must carry the full burden. It describes the read-only behavior (listing fields) and the context (schema for search criteria). While it doesn't explicitly state side effects or authentication needs, the behavior is inherently non-destructive and straightforward.

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 sentences with no wasted words. The first sentence states the action, the second provides usage guidance. It is front-loaded and 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?

With no parameters, no output schema, and a simple purpose, the description fully covers what the tool does and when to use it. The sibling tools list confirms it is a metadata tool distinct from data-retrieval 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, and schema coverage is 100% (none needed). The description adds no parameter information because none is needed. Baseline 4 for 0 parameters 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 clearly states the tool 'lists every field name, type, and description available for search criteria.' It uses a specific verb ('lists') and resource ('field names, types, descriptions'), and distinguishes itself from sibling tools like 'search_zips' by being a metadata discovery tool.

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 says: 'Call this when you're unsure what field names to pass to search_zips, or when the user asks what data ZipExplore has.' This provides clear context for when to use the tool and implies when not to (when you need actual data, use search_zips).

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 provided, and description focuses only on data content (tax types) without disclosing behavioral traits like read-only nature, error handling, or limitations.

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, front-loaded with purpose, 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?

Lists included data types but doesn't describe output structure, error behavior, or complete behavioral context, given no output schema.

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 0%, so description must add meaning. It clarifies that 'zip' is a single ZIP code but lacks format or constraint 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 clearly states it retrieves detailed tax data for one ZIP code, distinguishes from get_zip_profile's tax section, and lists specific tax types included.

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 says use when get_zip_profile's tax section isn't sufficient depth, providing clear context and an alternative.

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 provided. Description lists included data fields but does not disclose behavioral traits such as read-only nature, rate limits, or authentication needs. For a simple read tool, this is acceptable but 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?

Extremely concise: one sentence for purpose, one for usage guidance, and a list of specific data fields. No waste, front-loaded with key information.

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 one parameter, no output schema, and low complexity, the description lists 9 specific data fields, providing sufficient completeness for a data retrieval tool. Minor gaps like output format or distance units prevent a perfect score.

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 has one parameter 'zip' with 0% description coverage. Description only mentions 'one ZIP code' without specifying format, valid range, or examples, failing to compensate for lack of schema 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?

Clearly states it provides 'detailed public transit data for one ZIP code' and explicitly distinguishes from sibling 'get_zip_profile' by noting usage when its transit section is insufficient.

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 'Use when get_zip_profile's transit section isn't sufficient depth', providing clear when-to-use and direct alternative.

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 present, so the description carries full burden. It lists the types of data returned (presidential election results, partisan lean, districts, officials) but does not mention side effects or authorization requirements. Since the tool appears to be read-only, this is adequate.

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 with three sentences. It is front-loaded with the purpose and includes only necessary information, 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 simple parameter set and no output schema, the description covers the data included. It could mention whether results are current or historical, but otherwise it is complete enough for an agent.

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%. The description only implies the 'zip' parameter is a ZIP code but provides no format, validation, or examples. It adds minimal additional meaning 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?

The description specifies the verb 'get' and the resource 'voting and political data for one ZIP code'. It clearly distinguishes from sibling 'get_zip_profile' by indicating this tool provides more depth on voting data.

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 this tool: 'Use when get_zip_profile's voting section isn't sufficient depth.' This provides a clear usage condition and hints at an alternative tool for lighter needs.

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 provided, so the description carries full burden. It describes the data returned but does not disclose behavioral traits like rate limits, authentication, data freshness, or side effects. For a read-only tool, this is adequate but not thorough.

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: the first states the purpose, the second provides usage guidance and lists included data. It is front-loaded, efficient, and contains no extraneous 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?

With no output schema, the description lists the data types included (temperature averages, precipitation, humidity, nearest weather station), which is reasonably complete. However, it does not mention limitations like geographic scope or time periods, which could be useful.

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 0%, meaning the schema provides no parameter descriptions. The description adds meaning by stating the input is 'one ZIP code' and implies the format. This compensates for the schema gap, though it doesn't provide validation rules or examples.

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 provides detailed climate data for one ZIP code, and distinguishes it from get_zip_profile by specifying it offers deeper depth. The verb 'get' and resource 'weather profile' are explicit.

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 states when to use this tool: 'Use when get_zip_profile's climate section isn't sufficient depth.' This guides the agent to prefer the sibling tool for basic needs and this one for deeper data, providing clear context and alternative.

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 full burden. It mentions the maximum of 200 ZIP codes, a useful constraint, but does not disclose behavior for invalid ZIPs, error handling, or the exact structure of the response.

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 concise sentences. The first states the operation, the second gives usage guidance. Every word is necessary with 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?

For a simple tool with one parameter and no output schema, the description covers the essential purpose, input constraints, and usage scenario. It could mention the output format (e.g., returns lat/lng pairs), but is largely 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?

With 0% schema description coverage, the description adds meaning by specifying the parameter accepts ZIP codes and has a maximum count of 200. This compensates well for the lack of schema detail.

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 'Get' and the resource 'latitude/longitude centroid for ZIP codes', and specifies the scope 'one or more ZIP codes (max 200)'. It distinguishes from siblings like get_zip_profile (which returns more data) and reverse_geocode (which maps coordinates to ZIPs).

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 a clear usage context: 'Use when you need map coordinates for a set of ZIPs.' While it doesn't explicitly exclude other tools, this guidance effectively directs the agent to this tool for centroid retrieval.

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 must fully disclose behavioral traits. It mentions it provides a 'full location profile' but does not discuss rate limits, authentication, data freshness, error handling for invalid ZIPs, or what happens if data is unavailable. The scope is clear, but behavioral constraints are absent.

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 at two sentences, with the main purpose front-loaded. Every sentence adds value, and there is no redundant or vague language. It is well-structured for quick parsing.

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 tool returns a complex profile across 12 domains, but no output schema is provided, and the description does not explain what each domain contains or the structure of the response. It lacks context on potential errors or empty results for invalid ZIPs. Given the complexity, more detail is needed.

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 0%—the parameter 'zip' has no description in the input schema. The tool description does not add meaning beyond 'ZIP code,' failing to specify format, length, or accepted values. This leaves the agent without guidance on how to properly fill the parameter.

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 'Full location profile for one ZIP code across all 12 data domains' using a specific verb ('get') and resource ('ZIP profile'). It lists all 12 domains, making the purpose explicit. It also distinguishes itself from sibling tools by noting that for deeper data on a domain, domain-specific tools should be used.

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 states when to use this tool: 'after search, or when the user asks about a specific ZIP.' It also provides an alternative: 'For deeper data on one domain, use the domain-specific tools.' This guides the agent on when to select this tool versus its 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?

With no annotations, the description carries the full burden. It mentions the return type (status and counts) but lacks details like response format or latency. For a simple ping, this is adequate but not exhaustive.

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 short sentences, front-loaded with purpose, no redundant information. Every word serves a function.

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 zero parameters, no output schema, and minimal complexity, the description is fully sufficient for a ping tool. No additional context is needed.

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 no parameters, so schema coverage is 100%. Description adds no parameter info, which is appropriate. Baseline for zero-parameter tools is 4.

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 server status and tool/resource counts, and explicitly states its use for verifying the ZipExplore MCP connection. This distinguishes it from sibling tools which focus on data 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 explicitly says 'Use this to verify the ZipExplore MCP connection is live,' providing clear context for when to use it. No alternative tools are needed for this simple health check.

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 provided, and description lacks details on return format, error handling, or precision requirements, though conversion behavior 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?

Two sentences with no wasted words; purpose and usage guidance are 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?

Adequately covers purpose and usage for a simple tool with 2 params and no output schema, but lacks explanation of return value structure.

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 0% and description adds no additional meaning beyond parameter names ('lat', 'lon'), missing valid ranges or formatting 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?

Description clearly states 'Convert a latitude/longitude coordinate to a ZIP code', using a specific verb and resource, and distinguishes from siblings like search_zips.

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 says 'Use when the user provides an address or map coordinates rather than a ZIP code', providing clear when-to-use 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?

No annotations are provided, so the description carries the full burden. It discloses the return behavior (ranked list with scores) and the criteria format. However, it does not mention authorization, rate limits, or potential side effects, which are not critical for a read-only search tool. The description is transparent enough for an agent to understand what the tool does.

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 and uses bullet points to list key parameters, making it easy to scan. It is front-loaded with the purpose. However, it repeats parameter names that are already in the schema, which adds some 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?

With 6 parameters and no output schema, the description provides adequate context for the main use case but does not fully document all parameters or the complete return structure. It covers usage for recommendations but omits details on default behavior for limit and min_completeness.

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%, but the description adds meaning for criteria, area_types, and regions by explaining their formats and allowed values. However, it does not describe limit, states, or minimum_completeness, leaving gaps in parameter understanding.

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 'Find ZIP codes matching one or more criteria. Returns a ranked list with scores.' This specific verb and resource, combined with the ranking aspect, distinguishes it from sibling tools like compare_zips and the various profile tools.

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?

Explicit guidance is given: 'Use this first when the user wants recommendations...' and 'Call get_search_fields first if you're unsure what field names to use.' This provides clear context for when to use this tool versus alternatives.

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