InsuranceOracle - 12 insurance compliance tools: GDV, BaFin VAG, Solvency II, IDD.
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Average 3.4/5 across 12 of 12 tools scored.
Most tools are clearly distinct, but solvency_check overlaps with insurance_regulation and insurance_company by combining news and registration data. Natcat_live and earthquake_risk both provide earthquake alerts but from different sources; descriptions mitigate ambiguity.
All tool names follow a consistent snake_case pattern with a domain prefix and a noun/verb suffix (e.g., claim_news, risk_score, weather_risk). No mixed conventions or vague verbs.
12 tools is well within the ideal range for a specialized information service. Each tool contributes a distinct capability without bloat.
The tool set covers company lookup, glossary, news (claims, industry, regulation), live and historical NatCat, earthquake, weather, solvency compliance, and a combined risk score. No obvious dead ends or missing critical operations for an insurance intelligence server.
claim_newsBInspectMajor insurance claim news by event type: storm, flood, earthquake, hail, fire, cyber.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language: de or en (default: de) | |
| limit | No | Max articles 1-20 (default: 10) | |
| event_type | No | Event type: storm, flood, earthquake, hail, fire, cyber, all (default: storm) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for disclosing behavior. It omits details about return format, sorting, or what 'major' means, leaving the agent to infer that it returns a list of news articles. The description is minimal and does not explain side effects 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?
The description is a single sentence that is front-loaded with the core action and lists event types efficiently. Every word contributes value, with no filler or repetition.
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 has no output schema, so the description should convey what is returned. 'Major insurance claim news' implies a list of articles, but it does not explicitly state return type, default behavior, or any additional details needed for full understanding. It is adequate for a simple tool but leaves gaps given the absent output schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for all three parameters, including defaults and allowed values. The tool description repeats the event type list but adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides 'Major insurance claim news' filtered by event type, listing specific types. This gives a specific resource and scope, though it does not explicitly differentiate from the sibling 'insurance_news' 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?
The event type list implies usage for claim news related to those events, giving clear context for when it applies. However, it does not mention alternatives or when not to use this tool, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
earthquake_riskBInspectReal-time earthquake data from USGS. Filter by time period, minimum magnitude, and proximity to a location.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Time period: hour, day, week, month, significant_month (default: week) | |
| latitude | No | Filter near this latitude | |
| longitude | No | Filter near this longitude | |
| radius_km | No | Search radius in km (default: 500) | |
| min_magnitude | No | Minimum magnitude (default: 4.5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the data source (USGS) and real-time nature, but doesn't specify pagination, response format, or rate limits. The lack of destructive side effects is implied by 'data', meeting a baseline level.
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?
A single, front-loaded sentence that conveys the core purpose and key filters with zero fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 optional parameters and no output schema, so the description should explain what data is returned. It doesn't, leaving a gap in understanding the service's response structure. Still, for a simple data fetch, it's minimally 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 coverage is 100%, providing baseline 3. The description adds value by synthesizing parameters into three filter dimensions (time period, magnitude, location), making it easier to understand how to invoke the tool.
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 identifies the tool as providing real-time earthquake data from USGS, distinguishing it from weather or health-related siblings. However, it lacks an explicit action verb, stating a noun phrase rather than 'fetch' or 'query'.
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 is provided on when to use this tool vs siblings like natcat_live or weather_risk. The description only states what it does, not the appropriate context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkAInspectInsuranceOracle server status and backend connectivity check.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It implies a read-only health check but does not explicitly state non-mutating behavior, what the response contains (e.g., HTTP status, plain message), or whether any side effects occur. More detail on expected output or failure modes would be valuable.
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 sentence of eight words, front-loading the key information ('InsuranceOracle server status and backend connectivity check'). No unnecessary words or repetition.
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 zero-parameter tool, the description is minimally adequate: it names what is checked. However, no output schema exists, so the description should at least mention the expected return type or status semantics (e.g., 'returns 200 OK or 503'). It does not, leaving some ambiguity about how to interpret the result.
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 takes zero parameters, so the description does not need to explain parameter meaning. The baseline for zero-parameter tools is 4, and there are no gaps to compensate for.
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 a specific verb ('check') and resource ('InsuranceOracle server'), and specifies what is checked (status and backend connectivity). It distinguishes itself from all sibling tools, which focus on domain-specific data like claims, news, and risk scores.
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, nor does it mention typical scenarios like pre-flight checks or debugging connectivity. No exclusions or alternatives are noted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
insurance_companyAInspectLook up EU insurance company by name or LEI number. Returns GLEIF registration status, country, address, and Wikidata enrichment.
| Name | Required | Description | Default |
|---|---|---|---|
| lei | No | LEI code (alternative to name) | |
| name | No | Company name e.g. 'Allianz SE', 'AXA SA', 'Munich Re' | |
| country | No | Country code filter: DE, FR, GB, NL (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It partially discloses behavior by listing returned fields, but it does not clarify that at least one of name or LEI is expected, nor does it describe edge-case behavior (e.g., no parameters, both parameters provided, or no match found). This is a moderate amount of transparency for a simple read-only lookup.
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, front-loaded sentence with no filler. It immediately states the action and resource, then lists key identifiers and return fields, earning every word.
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 straightforward lookup tool, the description covers the core purpose, input identifiers, and output details. It lacks explicit handling of missing/both identifiers and error scenarios, but given the simplicity and complete schema descriptions, it is reasonably 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 description coverage is 100%; each parameter already has a clear description (e.g., 'LEI code (alternative to name)', 'Country code filter: DE, FR, GB, NL (optional)'). The main description adds minimal extra parameter semantics, only restating the name/LEI lookup modes, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Look up') and resource ('EU insurance company'), and clearly states the lookup keys ('by name or LEI number') and returned data ('GLEIF registration status, country, address, and Wikidata enrichment'). This clearly distinguishes it from sibling tools like insurance_glossary or risk_score, which serve different purposes.
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 phrase 'Look up EU insurance company by name or LEI number' implies when to use this tool, but it does not explicitly contrast it with alternatives or state when not to use it. Given the sibling tools (e.g., insurance_glossary, insurance_regulation), explicit disambiguation would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
insurance_glossaryAInspectExplain insurance and Solvency II terms in German or English. Covers: SCR, MCR, ORSA, SFCR, IDD, LEI, NAT CAT, reinsurance, premium, DORA, IFRS 17.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Response language: de or en (default: de) | |
| term | No | Term to explain e.g. 'SCR', 'Solvency II', 'ORSA', 'Elementarschadenversicherung' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the core behavior (explaining terms) and a scope of terms, but omits details like response language default behavior (despite schema indicating default 'de') and any limitations beyond the list. It is not misleading, 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?
Two short sentences, front-loaded with the core purpose and followed by a useful list of example terms. 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 two-parameter tool with full schema coverage, the description adequately covers purpose, language, and scope. No output schema exists, so explaining terms and listing examples is sufficient. Missing explicit default language, but schema covers that.
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 descriptive parameter definitions for both 'lang' and 'term'. The description adds a list of covered terms but does not enhance parameter semantics beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Explain' and the resource 'insurance and Solvency II terms in German or English'. It also lists specific covered terms, distinguishing it from sibling tools like news and risk 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?
The description implies usage for explaining listed terms, but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The coverage list offers some implicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
insurance_newsBInspectInsurance industry news by topic. Topics: solvency, life, health, property, liability, auto, reinsurance, regulation, natcat, cyber, claims, dora.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language: de or en (default: de) | |
| limit | No | Max articles 1-20 (default: 10) | |
| topic | No | Topic: solvency, life, health, property, natcat, cyber, claims, dora, regulation, reinsurance (default: solvency) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It doesn't state that the tool is read-only, describe the output format, or mention any pagination or rate limits. The topic list is informational but not behavioral; it fails to explain what happens when the tool is called (e.g., returns article summaries or URLs).
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 sentence, front-loaded with the core purpose, followed by a compact topic list. Every word contributes to understanding; there is no filler or redundant detail, making it exceptionally concise and well-structured for a simple news tool.
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 is simple and the schema documents all parameters, but the description lacks information about the output format and doesn't provide usage context relative to siblings. It covers purpose and topics adequately but leaves the return value and positioning among similar tools unclear, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaningful value by listing 'liability' and 'auto' as valid topics, which are absent from the schema's topic enumeration. This expands the semantic understanding of the 'topic' parameter beyond what the schema provides, though other parameters (lang, limit) are not elaborated further.
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 identifies the tool as providing 'Insurance industry news by topic' and enumerates the supported topics, which conveys the resource and scope. However, it lacks an explicit verb like 'retrieve' or 'list', and it doesn't explicitly differentiate from sibling tools such as claim_news, though the broad topic list implies wider coverage.
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, for instance, that claim_news should be used for claims-specific news, nor does it state any exclusions or preferred contexts. The only usage hint is the list of topics, which implicitly suggests coverage but offers no comparative direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
insurance_regulationCInspectEU and German insurance regulatory news and updates. Topics: general, bafin, eiopa, idd, gdpr, dora, ifrs17, sustainability, consumer.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language: de or en (default: de) | |
| topic | No | Topic: general, bafin, eiopa, idd, dora, ifrs17, gdpr, sustainability, consumer (default: general) | |
| country | No | Country: DE, EU (default: DE) |
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 only lists content topics and does not disclose whether the operation is read-only, returns articles, or has any defaults 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?
The description is a single sentence that front-loads the core purpose and then lists topics, with no unnecessary words or repetition.
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?
Without an output schema or annotations, the description should explain return values and behavior. It fails to describe what the tool returns, any pagination, or default parameter handling, leaving the agent without enough context for confident 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?
Schema description coverage is 100% with all parameters documented. The description's topic list mirrors the schema enum but adds no additional meaning about parameter interactions or defaults beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as providing EU and German insurance regulatory news and updates, with a specific topic list. The word 'regulatory' distinguishes it from general insurance news, but it lacks an explicit verb like 'retrieves' or 'lists'.
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?
There is no explicit guidance on when to use this tool versus the sibling insurance_news or claim_news tools. The topic list implies regulatory focus, but no alternatives or exclusions are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
natcat_historyBInspectHistorical natural catastrophe statistics for risk modeling. Significant events by type.
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | Region filter (optional) | |
| event_type | No | Event type: earthquake, flood, storm, fire (default: earthquake) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It only says 'historical natural catastrophe statistics' and 'significant events by type' without explaining what 'significant' means, how the data is sourced, whether the output is a summary or raw list, or any limitations. This is minimal disclosure beyond the basic nature of the 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 exceptionally concise: two short sentences with no filler. It front-loads the core concept 'historical natural catastrophe statistics' and adds a useful clarifying note about significant events. Every word serves a purpose, making it a model of conciseness.
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 annotations and no output schema, the description must provide sufficient context for the agent to know what to expect. It does not describe the output format, the meaning of 'significant', or how this tool differs from the sibling natcat_live beyond the obvious 'historical' keyword. Given the presence of several risk-related sibling tools, the description is under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters fully, giving 100% schema description coverage. The description adds the phrase 'by type' which aligns with the event_type parameter, but it does not provide extra context about defaults, interactions, or how region filters the data. The value added over the schema is minimal.
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 identifies the tool as providing historical natural catastrophe statistics, which distinguishes it from the sibling natcat_live by the word 'historical'. However, it lacks an explicit action verb like 'get' or 'retrieve', and the phrase 'significant events by type' is somewhat vague about the exact resource. Still, it is not a tautology and conveys 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 implies usage for risk modeling and the word 'historical' contrasts with natcat_live, so an agent can infer when to use it. However, there is no explicit statement of when to prefer this tool over alternatives, nor any exclusions or prerequisites. The guidance is implicit rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
natcat_liveBInspectLive natural catastrophe alerts worldwide from GDACS. Returns earthquakes, floods, cyclones, wildfires sorted by severity.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max events 1-50 (default: 20) | |
| country | No | Filter by country name (optional) | |
| severity | No | Filter severity: Red, Orange, Green | |
| event_type | No | Filter by type: EQ (earthquake), FL (flood), TC (cyclone), VO (volcano), WF (wildfire) — empty for all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the data source (GDACS), the scope (worldwide), and that results are 'sorted by severity,' which is useful. However, it does not disclose whether the operation is read-only, how real-time the data is, pagination behavior, or any rate limits—leaving notable gaps for an agent.
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, front-loaded with the core message: 'Live natural catastrophe alerts worldwide from GDACS.' Every sentence adds relevant detail (scope, source, event types, sorting) with no filler or repetition.
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 is relatively simple (4 optional parameters, no output schema, no annotations), so the description covers the essential behavior: what it returns and how it's sorted. However, without an output schema, the description does not explain the structure of each alert (fields, severity levels), and lacks any guidance on edge cases or integration with sibling tools. This makes it minimally adequate but not fully 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?
The input schema provides 100% coverage for all 4 parameters, each with descriptive text. The description adds only minimal value by mentioning event types that correspond to the event_type parameter, but it does not introduce any new semantic meaning not already present in the schema. Baseline 3 applies.
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 function with a specific verb ('Returns') and resource ('live natural catastrophe alerts worldwide from GDACS'). It lists event types and sorting, making the purpose unambiguous. However, it does not explicitly differentiate from siblings like natcat_history or earthquake_risk, so it stops short of a 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 does not provide any guidance on when to use this tool versus alternatives such as natcat_history or earthquake_risk. It implies a use case (live global alerts) but offers no exclusions, conditions, or explicit alternative suggestions, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
risk_scoreAInspectCombined location risk score (0-100) for underwriting: earthquake + weather/storm + NatCat proximity.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | No | Latitude (alternative to location) | |
| location | No | City or address e.g. 'Tokyo', 'Hamburg', 'Los Angeles' | |
| longitude | No | Longitude (alternative to location) |
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 score range and the factors combined, but it does not explain the calculation method, what happens if neither latitude/longitude nor location is provided, or if both are provided. This leaves some behavioral ambiguity.
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 sentence that front-loads the purpose, includes the output range and constituent factors, and contains no extraneous 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?
For a simple tool with three optional parameters and no output schema, the description sufficiently covers the score's purpose and composition. It lacks guidance on parameter ambiguity (e.g., providing both lat/long and location), but is otherwise complete for basic 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 coverage is 100% with each parameter described, so the description adds little beyond the schema. It mentions 'location' generically but does not enhance the meaning of latitude, longitude, or location beyond what the schema already states.
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 computes a combined location risk score (0-100) for underwriting, breaking it down into earthquake, weather/storm, and NatCat proximity components. This specific verb+resource+scope distinguishes it from sibling tools like earthquake_risk and weather_risk.
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 the tool is for underwriting scenarios that need a combined score, but it does not explicitly state when to use this tool versus the individual risk tools or provide exclusions. Usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
solvency_checkBInspectSolvency II compliance news and GLEIF registration status for an insurer.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language: de or en (default: de) | |
| company | No | Insurance company name (optional — omit for general Solvency II news) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as whether the operation is read-only, what data sources it uses, or how it handles missing company names. It simply states the outputs without side-effect information.
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?
A single, succinct sentence front-loads the core purpose. Every word contributes meaning; 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?
The tool is simple with two optional params and no output schema, but the description omits return format, error behavior, and usage scenarios, limiting full 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?
Schema covers both parameters fully with descriptions. The description adds the context that company relates to an insurer and that omitting it yields general news, but this largely mirrors the schema, so no significant extra meaning is provided.
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 names two outputs: Solvency II compliance news and GLEIF registration status. It distinguishes from siblings by referencing specific regulatory topics, though it lacks an explicit verb.
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 choose this tool over siblings like insurance_news or insurance_regulation. The schema's company parameter hint is the only usage-related clue, but it doesn't address tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
weather_riskAInspect7-day weather risk assessment for any location. Returns storm, flood, and wind risk with insurance recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | No | Latitude (alternative to location) | |
| location | No | City or address e.g. 'Hamburg', 'Munich' | |
| longitude | No | Longitude (alternative to location) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions the output types (storm, flood, wind risk, insurance recommendations) but does not disclose whether the operation is read-only, any potential side effects, data sources, or error behavior. This is insufficient for a tool with no structured safety hints.
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 short sentences that cover purpose, time frame, scope, and output types. Every word earns its place, with no filler or repetition.
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 3-parameter schema with full coverage and no output schema, the description adequately conveys the tool's core functionality and expected return facets (storm, flood, wind risk, insurance recommendations). However, it could be slightly more complete by noting the need for either a location or lat/lon pair, though this is implied by the 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 description coverage is 100%, so the baseline is 3. The description adds no information about parameter syntax or selection beyond the schema, which already documents latitude, longitude, and location alternatives. Thus, it provides no additional semantic 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 tool's function: a 7-day weather risk assessment for any location, specifying the outputs (storm, flood, wind risk, and insurance recommendations). It distinguishes itself from sibling tools like earthquake_risk and natcat_history by focusing on weather-specific perils and a 7-day forecast horizon.
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 is for any location and for obtaining short-term weather risk, which gives a basic context. However, it does not explicitly state when to prefer this tool over alternatives (e.g., earthquake_risk, natcat_history) or exclude scenarios, so it lacks clear when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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