agentfeeds.jp

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 states that data is factual and not investment advice and that the catalog is machine-readable, but it does not describe output format, update behavior, or access limitations beyond the disclaimer.

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 concise sentence, front-loaded with 'Free' and a clear object. Every word earns its place, and the disclaimer is short but relevant.

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 no-parameter catalog endpoint, the description is adequate but minimal. It clarifies the domain and disclaims investment advice, but it does not describe the catalog's structure, expected response format, or how it relates to the sibling data tools, leaving some operational 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?

The tool has zero parameters and the input schema is empty, so the description does not need to explain parameter semantics. The baseline of 4 applies because the schema already fully covers the (empty) parameter set.

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 a machine-readable product catalog for agentfeeds.jp, which distinguishes it from siblings like reg_events or sanctions_check. However, it lacks an explicit action verb (e.g., 'retrieves' or 'lists'), making it slightly less directive.

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 about when to use this tool versus alternatives. The 'Free:' and 'not investment advice' notes are qualifiers, not usage criteria, and there is no mention of appropriate contexts or exclusions.

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 discloses important behavioral traits: the tool is paid ($0.005/call) and provides only descriptive statistics with a 'not investment advice' disclaimer. It also defines the anomaly criterion. However, it does not mention output format, ordering, or other side effects. Without annotations, this is a moderate level of 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 a single, tightly worded sentence that conveys the tool's core function, cost, and a disclaimer. It is well-structured and front-loaded with the most important information, with 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?

The tool has no output schema, no annotations, and sparse parameter descriptors. The description explains what an anomaly is but omits critical details such as the output structure, how 'since' should be formatted, and any other behavioral expectations. This leaves the agent under-informed for a data query 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%, and the description provides no information about the parameters 'pair', 'limit', or 'since'. The meaning of these parameters is left entirely to inference from their names. The description does not compensate for the lack of schema descriptions, making it difficult for an agent to construct valid calls.

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's purpose: it returns DEX spread anomaly events, defined as 1-minute |spread| values above a trailing 30-day p99 threshold. This is specific and distinguishes it from the sibling 'dex_spread_summary' (which likely provides aggregate summaries, not anomaly events).

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 alternatives. The description does not reference sibling tools like 'dex_spread_summary' or state conditions for choosing this over other data sources. The usage context is only implied via the anomaly definition, not explicitly stated.

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 transparently discloses the cost ($0.002/call), supported pairs, venues, and a caveat. However, it does not disclose what statistics are returned, how `limit` or `since` affect behavior, or potential errors/rate limits—important details for a paid 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 a single, efficient sentence that front-loads cost and purpose. Every clause adds value: payment, time window, venue/pair scope, and investment caveat. No filler 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?

Given no output schema and no annotations, the description should explain return values and parameter defaults, but it leaves `limit` and `since` undefined and does not describe the response structure. It provides enough for a basic understanding but is incomplete for a paid tool with additional parameters.

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 the description fails to explain `limit` or `since` semantics, including defaults or time range formatting. It partially addresses `pair` by naming supported pairs, but overall the description does not compensate for the missing schema-level documentation.

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 1-minute cross-venue DEX spread statistics for specific pairs (WETH/USDC on Base, SOL/USDC via Jupiter). It differentiates from the sibling dex_spread_anomalies by emphasizing 'Descriptive statistics only,' though it lacks an explicit verb like 'retrieve' or 'get.'

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 useful context: it is paid, descriptive only, not investment advice, and names supported pairs/venues. However, it does not explicitly state when to use this tool versus dex_spread_anomalies or other siblings; the guidance is implied through 'Descriptive statistics only.'

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 of behavioral disclosure. It is a noun phrase stating content, but does not explicitly say the tool 'returns' the terms, nor does it mention any side effects, response format, or access requirements.

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, a single short phrase with no fluff. The initial 'Free:' is slightly ambiguous and could be omitted without losing meaning, but the overall structure is appropriately minimal for such a simple 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?

For a tool with no parameters and no output schema, the description gives the essential content (license terms and disclaimer) but lacks an explicit statement of what the tool returns or that it is a read-only fetch. This is a clear gap given the absence of any other documentation.

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 the schema is trivially complete. The description does not need to explain parameters, and with no params the baseline is 4. It neither adds nor detracts from 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 identifies the resource (license terms and disclaimer) and its scope (agentfeeds.jp data), making it obvious that this tool retrieves these terms. It distinguishes itself from the sibling tools (catalog, DEX spread, reg events, sanctions check) which all relate to other data categories.

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?

Usage is implied: if an agent needs the license terms or disclaimer for agentfeeds.jp, it should invoke this tool. However, there is no explicit guidance on when to use it relative to alternatives, though none of the siblings serve a similar purpose.

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 usefully discloses the per-call cost, human-review status, factual nature, and a disclaimer (not investment/legal advice). Still, it omits practical behavioral details such as result ordering, pagination, expected update frequency, or any required permissions/authentication.

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, packing cost, geographic scope, topical scope, language, and review status into one sentence, plus a one-line disclaimer. It is front-loaded with the most operationally relevant detail (cost). 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?

The tool has no output schema, so the description should explain what the returned data looks like or at least how results are presented. It does not. It also leaves 'since' syntax and the semantics of the result set ambiguous. Given the sibling context and simple query nature, this is a notable gap.

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 no parameter descriptions, and the description provides zero explanation of 'limit', 'since', or 'category'. While the names are somewhat self-explanatory, the format for 'since' (e.g., ISO date?) and how the enum values map to events is unclear. The description does nothing to compensate for the 0% schema coverage.

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 resource as 'Japan digital & financial regulatory events' and specifies relevant domains (crypto, AML/sanctions, tax, AI). However, it lacks an explicit verb like 'list' or 'retrieve', so the action is implied rather than stated. It is sufficiently distinct from sibling tools (e.g., sanctions_check, get_terms) due to the event 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 implies usage when Japan regulatory event data is needed, and it clearly notes it is a paid tool. However, it does not explicitly state when to use this versus alternatives, nor does it provide any exclusions or prerequisite context. The guidance is basic and inferred from the resource type.

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 transparency burden. It discloses that the tool is paid, targets Japan MOF designations, and that the output is factual screening data, not legal advice. This goes beyond a minimal description, though it does not detail return formats or error handling, which are typical for a simple screening 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 a single, front-loaded sentence that includes the cost, purpose, scope, and a disclaimer. Every word adds value, and it is immediately clear what the tool does.

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 low-complexity with a single parameter, and the description covers the essential context: the screening target, jurisdiction, cost, and a legal disclaimer. It does not describe the return value, but without an output schema, the phrase 'screen' implies a yes/no result, which is adequate for this 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 coverage is 0%, so the description must compensate. It explicitly clarifies that the 'address' parameter is a 'crypto address', adding meaning beyond the generic alphanumeric pattern in the schema. However, it does not specify which blockchain or address format, leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('screen') and resource ('a crypto address against Japan MOF asset-freeze sanctions designations'). This uniquely distinguishes it from sibling tools like catalog, dex_spread_anomalies, and reg_events, which cover different domains.

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 clear context on when to use the tool: when you need to check a crypto address against Japan's sanctions list. It does not explicitly state exclusions or alternative tools, but the sibling tools are unrelated, so no further guidance is necessary. The cost note ('Paid ($0.002/call)') adds an implicit usage consideration.

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