DaedalMap Volcanic Activity
Server Details
Historical volcanic eruption records and volcanic activity queries from the DaedalMap MCP lane.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- xyver/daedal-map
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.5/5 across 7 of 7 tools scored.
The tools have clear primary purposes (e.g., get_earthquake_events for earthquakes, get_volcanic_activity for volcanic activity), but there is significant overlap between get_catalog, get_pack, and query_dataset in terms of data discovery and access. An agent might confuse when to use get_pack versus query_dataset for detailed metadata versus direct querying, and get_catalog serves a similar discovery role.
Most tools follow a consistent verb_noun pattern (e.g., get_catalog, get_earthquake_events, get_fx_rates), which is predictable and readable. The only deviation is query_dataset, which uses a different verb ('query' instead of 'get'), but this is minor and still follows a clear naming convention.
With 7 tools, the count is well-scoped for a server focused on volcanic activity and related datasets (e.g., earthquakes, tsunamis, currency). Each tool has a distinct role in querying specific data types or metadata, and none feel redundant or excessive for the apparent domain coverage.
The tool set covers key data types in the domain (volcanic activity, earthquakes, tsunamis, currency rates) with query capabilities and metadata access. Minor gaps exist, such as no explicit tools for updating or deleting data (though this may be intentional for a read-only query server), and the overlap in discovery tools could be streamlined, but agents can work around this for core querying tasks.
Available Tools
7 toolsget_catalogGet CatalogBRead-onlyInspect
Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, indicating a safe read operation. The description adds value by specifying that it returns 'live agent-ready data packs' and implies a discovery context with 'Free discovery', but doesn't detail behavioral aspects like rate limits, authentication needs, or response format. No contradiction with annotations exists, so it meets the baseline for tools with 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 highly concise and front-loaded: two short sentences with zero waste. 'Free discovery' sets context efficiently, and the second sentence clearly states the action and resource. Every word earns its place, making it easy for an AI agent to parse quickly.
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 (0 parameters, read-only annotation, no output schema), the description is adequate but has gaps. It explains what the tool does but doesn't cover usage guidelines or differentiate from siblings, which could help in tool selection. For a list-retrieval tool, it's minimally viable but lacks completeness in contextual guidance.
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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. This aligns with the baseline score of 4 for zero-parameter tools, as it avoids unnecessary 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 the tool's purpose: 'Returns the list of live agent-ready data packs available on DaedalMap.' It uses a specific verb ('Returns') and resource ('list of live agent-ready data packs'), though it doesn't explicitly differentiate from sibling tools like 'get_pack' or 'query_dataset'. The 'Free discovery' phrase adds context but isn't essential to the core 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_pack' (which might retrieve a specific pack) or 'query_dataset' (which might search datasets), nor does it specify prerequisites or exclusions. The 'Free discovery' phrase hints at exploratory use but lacks explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_earthquake_eventsGet Earthquake EventsBRead-onlyInspect
Paid x402 tool. Queries earthquakes_events. Use event_count for aggregate counts or event metrics for raw event rows.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return. Use small limits for top-N queries such as largest event in a range. | |
| output | No | Optional output controls such as response format hints. | |
| filters | Yes | Structured filters including time ranges, region_ids, and compare clauses. | |
| metrics | Yes | Metric ids to return, such as 'event_count' or event attributes like 'magnitude'. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds context about being a 'Paid x402 tool' (implying potential access restrictions or costs) and clarifies the purpose of metrics, which adds value beyond annotations. However, it doesn't disclose behavioral traits like rate limits, error handling, or response format 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?
The description is concise with two sentences that efficiently convey key information: tool type and metric usage. It is front-loaded with the main purpose. However, the 'Paid x402 tool' phrase is somewhat cryptic and could be clarified for better efficiency.
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 (6 parameters, nested objects) and lack of output schema, the description is moderately complete. It covers the tool's purpose and metric differentiation but misses details on response structure, error cases, or integration with sibling tools, leaving gaps for an AI agent to infer usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds minimal semantics by hinting at metric usage ('event_count' vs. 'event metrics'), but this is largely redundant with the schema's description of 'metrics'. Baseline 3 is appropriate as 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 clearly states the tool queries earthquake events and distinguishes between aggregate counts and raw event rows, providing a specific verb ('queries') and resource ('earthquake_events'). However, it doesn't explicitly differentiate from sibling tools like 'get_tsunami_events' or 'get_volcanic_activity' beyond the domain focus.
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 implied usage guidance by mentioning 'event_count for aggregate counts or event metrics for raw event rows,' which suggests when to use different metric types. However, it lacks explicit when-to-use vs. alternatives, such as comparing to sibling tools like 'query_dataset' or specifying prerequisites like the 'Paid x402 tool' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fx_ratesGet FX RatesBRead-onlyInspect
Free tool. Queries the currency pack using filters.region_ids plus filters.time.granularity to return daily, weekly, or monthly FX data.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return for the requested granularity and time span. | |
| output | No | Optional output controls such as response format hints. | |
| filters | Yes | Structured filters including region_ids with loc_id country codes, time range, and granularity. | |
| metrics | No | Optional metric ids. Defaults to 'local_per_usd' for FX rate queries. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds context by specifying it's a 'Free tool' and mentions filtering capabilities (region_ids and time granularity), which adds value beyond annotations. However, it doesn't disclose behavioral traits like rate limits, authentication needs, or data freshness, leaving gaps in 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 concise with two sentences, front-loaded with key information (free tool, query action, filters). Every sentence adds value, though it could be slightly more structured by explicitly separating purpose from usage hints.
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 annotations (readOnlyHint) and high schema coverage, the description is somewhat complete but lacks output details (no output schema) and doesn't fully address behavioral aspects like error handling or data scope. For a query tool with 6 parameters and nested objects, more context on response format or limitations would improve 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 100%, so parameters are well-documented in the schema. The description adds minimal semantics by mentioning filters.region_ids and filters.time.granularity, but doesn't provide additional meaning beyond what the schema already covers (e.g., details on region_ids or granularity options). Baseline 3 is appropriate as the schema does the heavy lifting.
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 'queries the currency pack' to 'return daily, weekly, or monthly FX data', specifying both the action (query) and resource (currency pack/FX data). It distinguishes from siblings like get_catalog or get_earthquake_events by focusing on FX rates, though it doesn't explicitly differentiate from get_pack or query_dataset which might have overlapping functions.
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 implies usage for retrieving FX data with specific filters (region_ids and time granularity), but provides no explicit guidance on when to use this tool versus alternatives like get_pack or query_dataset. It mentions 'Free tool' which hints at cost considerations, but lacks clear when/when-not scenarios or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_packGet PackARead-onlyInspect
Free discovery. Returns detailed metadata, coverage, metrics, and first-query guidance for one pack.
| Name | Required | Description | Default |
|---|---|---|---|
| pack_id | Yes | Pack identifier such as 'currency', 'earthquakes', 'volcanoes', or 'tsunamis'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds context about what is returned (metadata, coverage, metrics, guidance) and the 'Free discovery' aspect, which is useful but does not fully disclose behavioral traits like rate limits, authentication needs, or error handling beyond the 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 a single, efficient sentence that is front-loaded with key information ('Free discovery. Returns detailed metadata...'), with no wasted words, making it highly concise and well-structured.
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 low complexity (1 parameter, read-only, no output schema), the description is complete enough for its purpose. It covers what the tool does and returns, though it could benefit from more behavioral context or output details, but annotations help fill some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'pack_id' fully documented in the schema. The description does not add meaning beyond the schema, such as examples or constraints, so it meets the baseline for high schema coverage without extra value.
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 specific action ('Free discovery. Returns detailed metadata, coverage, metrics, and first-query guidance') and resource ('for one pack'), distinguishing it from siblings like get_catalog (which likely lists multiple packs) or query_dataset (which queries data rather than returning metadata).
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 implies usage for discovering pack details, but does not explicitly state when to use this tool versus alternatives like get_catalog or query_dataset. It provides context (e.g., 'first-query guidance') but lacks explicit guidance on exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tsunami_eventsGet Tsunami EventsBRead-onlyInspect
Paid x402 tool. Queries tsunamis_events for tsunami source events and related metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return. Use small limits for largest-wave or latest-event queries. | |
| output | No | Optional output controls such as response format hints. | |
| filters | Yes | Structured filters including time ranges, region_ids, and compare clauses. | |
| metrics | Yes | Metric ids to return, such as 'event_count', 'max_water_height_m', or event attributes. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds some behavioral context beyond annotations: it indicates this is a 'Paid x402 tool,' suggesting potential access or cost implications not covered by the readOnlyHint annotation. However, it doesn't disclose other traits like rate limits, error handling, or performance characteristics. With annotations covering read-only safety, the description provides moderate additional value, but lacks depth in behavioral 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?
The description is concise and front-loaded, consisting of two sentences that directly state the tool's purpose and access note. There is no wasted verbiage, and it efficiently conveys key information. However, it could be slightly improved by integrating usage hints more seamlessly, but it's still highly 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?
Given the tool's complexity (6 parameters, nested objects, no output schema) and annotations (readOnlyHint only), the description is moderately complete. It covers the basic purpose and access note, but lacks details on output format, error cases, or integration with sibling tools. With no output schema, the description doesn't explain return values, leaving gaps in contextual understanding for effective agent use.
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 description does not add meaning beyond the input schema, which has 100% coverage with detailed descriptions for all parameters. It mentions 'tsunami source events and related metrics,' which loosely relates to the 'metrics' parameter, but offers no additional syntax, examples, or constraints. Given the high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
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: 'Queries tsunamis_events for tsunami source events and related metrics.' It specifies the verb ('queries'), resource ('tsunamis_events'), and scope ('tsunami source events and related metrics'). However, it doesn't explicitly differentiate from sibling tools like 'get_earthquake_events' or 'query_dataset' beyond the resource name, which is why it doesn't reach a score of 5.
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 minimal usage guidance. It mentions 'Paid x402 tool,' which implies a cost or access restriction, but doesn't specify when to use this tool versus alternatives like 'get_earthquake_events' for earthquake data or 'query_dataset' for general queries. No explicit when/when-not scenarios or prerequisites are provided, leaving the agent with little context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_volcanic_activityGet Volcanic ActivityBRead-onlyInspect
Free tool. Queries volcanoes_events for eruption records and volcanic activity metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return. Use small limits for top-N eruption lookups. | |
| output | No | Optional output controls such as response format hints. | |
| filters | Yes | Structured filters including time ranges, region_ids, and compare clauses. | |
| metrics | Yes | Metric ids to return, such as 'event_count', 'VEI', or eruption attributes. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation 'readOnlyHint: true' already indicates this is a safe read operation, so the description doesn't need to repeat that. The description adds minimal behavioral context by specifying the data source ('volcanoes_events') and types of data returned ('eruption records and volcanic activity metrics'), but it lacks details on rate limits, authentication needs, or response format. No contradiction with annotations exists, so this is adequate given the annotation coverage.
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 and front-loaded, consisting of just two sentences: 'Free tool. Queries volcanoes_events for eruption records and volcanic activity metrics.' Every word contributes directly to the tool's purpose, with no wasted information or redundancy. It efficiently communicates the core functionality 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?
Given the tool's complexity (6 parameters, nested objects) and the presence of annotations (readOnlyHint: true) but no output schema, the description is minimally complete. It covers the basic query intent and data source, which is sufficient for a read-only tool with good schema documentation. However, it doesn't address output details or advanced usage scenarios, leaving some gaps in contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the input schema. The description doesn't add any meaningful semantic details beyond what's in the schema—it doesn't explain parameter interactions, provide examples, or clarify usage beyond the basic query purpose. This meets the baseline for high schema coverage but doesn't enhance 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's purpose: 'Queries volcanoes_events for eruption records and volcanic activity metrics.' It specifies the verb ('queries'), resource ('volcanoes_events'), and scope ('eruption records and volcanic activity metrics'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_earthquake_events' or 'query_dataset', which would be needed for a perfect score.
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 no guidance on when to use this tool versus alternatives. It mentions 'Free tool' but doesn't explain if this is a distinguishing factor from siblings or provide any context about prerequisites, typical use cases, or exclusions. Without such information, an agent might struggle to choose between this and similar tools like 'get_earthquake_events' or 'query_dataset'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_datasetQuery DatasetARead-onlyInspect
Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Currency and volcanoes are free; earthquakes and tsunamis are paid via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return for the requested source or pack. | |
| output | No | Optional output controls such as response format hints. | |
| filters | No | Structured filters including time, region_ids, and compare clauses. | |
| metrics | No | Metric ids to return. Use event_count for aggregate counts when supported. | |
| pack_id | No | Pack id such as 'currency', 'earthquakes', 'volcanoes', or 'tsunamis'. | |
| source_id | No | Concrete source id such as 'earthquakes_events' or 'volcanoes_events'. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds valuable context about pricing tiers (free vs paid data types) and references the specific API contract, which goes beyond what annotations provide. However, it doesn't describe rate limits, authentication requirements, or response format details that would be helpful for a query 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?
The description is extremely concise with just two sentences that both earn their place. The first sentence establishes the core functionality and API contract, while the second provides critical pricing information. There's zero wasted verbiage and the most important information (pricing tiers) is appropriately positioned.
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 query tool with rich input schema (8 parameters, 100% coverage) and read-only annotations, the description provides excellent complementary information about pricing tiers and API contract reference. The main gap is the lack of output schema, so the agent doesn't know what data structure to expect in return. However, the description compensates well for this by providing practical usage context.
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 100% schema description coverage, the input schema already documents all 8 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'source_id or pack_id access' which aligns with two parameters but doesn't provide additional semantic context. The baseline of 3 is appropriate when the schema does the heavy lifting.
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 performs 'Generic structured query for direct source_id or pack_id access' with a specific API endpoint reference. It distinguishes itself from siblings by mentioning direct access to specific data sources/packs rather than catalog browsing or specialized endpoints. However, it doesn't explicitly contrast with all sibling tools like 'get_fx_rates' or 'get_volcanic_activity'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance by stating 'Currency and volcanoes are free; earthquakes and tsunamis are paid via x402.' This clearly indicates when to use this tool (for querying these specific data types) and includes cost/payment considerations that differentiate it from potential alternatives. The API endpoint reference also provides implementation context.
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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