CDC Mortality (WONDER)
Server Details
Leading causes of death, mortality rates, infant mortality, and drug overdose data
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4/5 across 5 of 5 tools scored.
The tools are mostly distinct with clear purposes: drug overdoses, infant mortality, leading causes, state comparisons, and provisional data. However, 'get_leading_causes_of_death' and 'get_mortality_by_state' both use the same underlying dataset (NCHS Leading Causes of Death) and could cause confusion about which to use for state-level mortality analysis, creating minor overlap.
All tools follow a consistent 'get_[specific_data_type]' naming pattern using snake_case. This predictable structure makes it easy for agents to understand what each tool retrieves without ambiguity in naming conventions.
With 5 tools, this server is well-scoped for accessing CDC mortality data. Each tool covers a distinct aspect of mortality statistics (drug overdoses, infant mortality, leading causes, state comparisons, provisional data), providing comprehensive coverage without being overwhelming or too sparse.
The toolset provides excellent coverage of key mortality data domains with clear retrieval capabilities. Minor gaps exist in update/delete operations (which may not be applicable for read-only public health data) and potentially in demographic breakdowns beyond state and race/ethnicity, but agents can effectively work with the available data for most mortality analysis tasks.
Available Tools
5 toolsget_drug_overdose_deathsAInspect
Get provisional drug overdose death data by state.
Returns provisional counts and rates of drug overdose deaths from the
National Vital Statistics System (NVSS). Includes data on opioid,
synthetic opioid, and other drug-involved deaths. Updated monthly.
Args:
state: Filter by state name (e.g. 'West Virginia', 'Ohio').
Case-insensitive. Returns all states if not specified.
year: Filter by year. Returns all available years if not specified.
limit: Maximum number of records to return (default 25, max 1000).| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| limit | No | ||
| state | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behavioral traits absent from annotations: provisional nature of data, monthly update cadence, and specific drug categories included (opioid, synthetic opioid).
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?
Well-structured with front-loaded purpose statement followed by source details and structured Args section; no redundant or filler content.
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?
Comprehensive for a 3-parameter tool with output schema available; covers data source (NVSS), temporal scope, and filtering behavior without needing to detail return 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?
Excellent compensation for 0% schema description coverage by providing examples ('West Virginia'), case-sensitivity notes, default behaviors ('Returns all states'), and constraint bounds (max 1000).
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?
Opens with specific verb and resource ('Get provisional drug overdose death data'), clearly distinguishing from sibling general mortality tools (get_mortality_by_state, get_provisional_mortality) via explicit mention of drug/opioid specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage through specificity ('drug overdose deaths'), but lacks explicit when/when-not guidance comparing it to get_leading_causes_of_death or get_provisional_mortality alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_infant_mortalityAInspect
Get infant mortality rates by state and race/ethnicity.
Returns infant mortality data including rates per 1,000 live births,
broken down by state and race/ethnicity. Infant mortality is a key
indicator of community health status used in CHNAs.
Args:
state: Filter by state name (e.g. 'Ohio', 'Georgia'). Case-insensitive.
Returns all states if not specified.
year: Filter by year. Returns all available years if not specified.| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| state | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Strong disclosure of units (per 1,000 live births), breakdown dimensions, and default behaviors (returns all if unspecified) compensating for missing 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?
Well-structured with front-loaded purpose, compact return value description, and dedicated Args section—every 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?
Adequate for complexity level (2 optional params, output schema exists); mentions CHNAs context and data granularity without unnecessary verbosity.
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?
Excellent compensation for 0% schema coverage with detailed Args section including examples ('Ohio', 'Georgia'), case-sensitivity notes, and default behaviors.
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?
Clear specific purpose (infant mortality rates by state/race) but lacks explicit differentiation from sibling mortality tools despite implying it via race/ethnicity mention.
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 implied usage context (CHNAs) but lacks explicit when-to-use guidance or alternatives compared to sibling tools like get_mortality_by_state.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_leading_causes_of_deathAInspect
Get leading causes of death with death counts and age-adjusted rates.
Returns data from the NCHS Leading Causes of Death dataset, which provides
national and state-level mortality statistics by cause of death, year, and
age-adjusted death rate per 100,000 population. Data spans 1999-2017.
Args:
state: Filter by state name (e.g. 'California', 'Texas'). Case-insensitive.
Returns all states if not specified.
year: Filter by year (e.g. 2017). Returns all available years if not specified.
limit: Maximum number of records to return (default 25, max 1000).| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| limit | No | ||
| state | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Provides temporal constraints (1999-2017) and pagination limits, but lacks auth requirements, rate limits, or data freshness details.
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?
Well-structured with purpose front-loaded, followed by data source context and structured parameter documentation; no extraneous content.
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?
Comprehensive given output schema exists: covers data source, geographic scope, temporal range, and return metrics (death counts, age-adjusted rates).
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?
Excellent compensation for 0% schema description coverage by detailing filter behaviors, defaults, and case-insensitivity in Args section.
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?
Clear specific purpose (get leading causes with counts/rates) and identifies NCHS dataset, but doesn't explicitly differentiate from sibling 'get_mortality_by_state'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus sibling mortality tools or alternative data sources.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_mortality_by_stateAInspect
Compare mortality rates across states for a specific cause or all causes.
Returns age-adjusted death rates by state, useful for comparing mortality
burdens across geographies. Data from NCHS Leading Causes of Death.
Args:
cause: Cause of death to filter by (e.g. 'Heart disease', 'Cancer',
'Unintentional injuries', 'Alzheimer\'s disease'). Partial match
supported. Returns all causes if not specified.
year: Filter by year (e.g. 2017). Defaults to most recent available year
if not specified.| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| cause | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key traits: returns age-adjusted rates (not raw), data source (NCHS), and default behaviors for both optional parameters.
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?
Well-structured with purpose front-loaded, followed by return value description, then Args section; no redundant text.
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?
Adequate for tool complexity; mentions output format (age-adjusted rates) and provenance, sufficient given existence of 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?
Excellent compensation for 0% schema description coverage by providing parameter explanations with examples (e.g., 'Heart disease', 2017) and partial match behavior.
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?
Clear verb-resource combo ('compare mortality rates across states') and distinguishes geographic focus from siblings, though doesn't explicitly contrast with get_leading_causes_of_death.
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 context ('useful for comparing mortality burdens') but lacks explicit when-to-use vs siblings like get_drug_overdose_deaths or get_infant_mortality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_provisional_mortalityAInspect
Get most recent provisional mortality data including COVID and other causes.
Returns provisional death counts from the NVSS, covering major cause
groups including COVID-19, respiratory diseases, circulatory diseases,
and more. Data is updated weekly and covers the most recent periods.
Args:
state: Filter by state/jurisdiction name (e.g. 'New York', 'Florida').
Case-insensitive. Returns all jurisdictions if not specified.
cause_group: Filter by cause group (e.g. 'COVID-19', 'Respiratory',
'Circulatory', 'Malignant neoplasms'). Partial match supported.
Returns all cause groups if not specified.
limit: Maximum number of records to return (default 50, max 1000).| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| state | No | ||
| cause_group | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors absent from annotations: weekly update frequency, NVSS source, case-insensitive state matching, partial string matching for cause_group, and default return-all behavior for optional filters.
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?
Well-structured with purpose upfront followed by Args section; slightly verbose but every sentence provides distinct value (source, update frequency, coverage scope).
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?
Complete given complexity: covers data source, update cadence, filtering capabilities, and pagination limits; appropriately omits return value details since output schema exists.
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?
Comprehensively compensates for 0% schema description coverage by documenting all three parameters (state, cause_group, limit) with constraints, examples, and default behaviors in the Args section.
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 retrieves provisional/weekly mortality data from NVSS, distinguishing it from siblings via 'provisional' and 'most recent' qualifiers, though could better emphasize the timeliness trade-off vs final mortality 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?
Implies usage context (needing recent/weekly data) but lacks explicit comparison to siblings like get_mortality_by_state or guidance on when final vs provisional data is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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