DAP Bellwether

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 behavioral detail by stating it retrieves every revision, which is beyond what annotations provide. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no extraneous words. The first sentence states the main purpose, the second provides usage guidance and input source. Efficient 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 simplicity (one parameter, read-only with annotations), the description covers all necessary context: what it does, when to use it, and where the input comes from. No output schema is needed as the purpose is clear.

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 a description for the id parameter. The description adds value by explaining that the id comes from a search or recent result, providing context beyond the schema.

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

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

The description clearly states the verb 'retrieve', the resource 'one record in full', and the unique aspect 'including every revision observed since it was first seen'. This effectively differentiates it from sibling tools like list_coverage which lists coverage, and search_regulatory_changes which is for searching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this to answer whether a document was amended after publication and what moved' and clarifies that the id comes from a search or recent result. It provides strong usage context but does not explicitly mention when not to use the tool, though it's implied.

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?

Adds meaningful behavioral context beyond annotations: lists all regulators/feeds, includes last successful collection and data freshness. readOnlyHint aligns with listing. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff. Front-loaded with key action and resource. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, description fully explains what is returned: regulators, feeds, last collection time, freshness. Sufficient for a listing tool with no 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?

No parameters exist (schema coverage 100%). Description doesn't need to add param meaning, but it correctly implies no filtering. Baseline 4 for zero-param tools.

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 explicitly states 'List every regulator and feed being monitored' with details on freshness and last collection. It clearly identifies the tool's purpose and distinguishes it from siblings (get_regulatory_change, etc.) by focusing on coverage rather than changes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: 'Use to answer what this connector covers, or to check whether a jurisdiction is being watched before relying on an absence of results.' This tells when to use and implies alternative tools for regulatory changes.

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 adds behavioral context beyond the readOnlyHint annotation: it mentions ordering ('newest first'), scope ('all covered regulators'), and usage context ('general catch up'). It does not contradict annotations and provides sufficient transparency for safe usage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences with no wasted words. The first sentence states the core function, and the second provides usage guidance. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, usage timing, ordering, and scope. It lacks explicit mention of the output format (e.g., fields returned), but given the simplicity of the tool and rich schema, it is nearly complete for an AI to decide invocation.

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 parameters are well-described in the schema (days, limit, jurisdiction with defaults and ranges). The description does not add significant new parameter semantics beyond the schema, earning a baseline score of 3.

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 action ('list'), the resource ('most recent regulatory publications'), and the scope ('across all covered regulators, newest first'). It also includes an example usage pattern, distinguishing it from siblings like search_regulatory_changes for specific topics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'when asked what is new, what happened this week, or for a general catch up rather than a specific topic.' This provides clear context but does not explicitly exclude alternatives like get_regulatory_change or list_coverage.

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 adds that matching is against title and summary, and results are sorted by date descending. Annotations already declare readOnlyHint=true, so the safety profile is clear. The description does not detail pagination, exact match semantics, or case sensitivity, leaving some behavioral gaps.

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 consists of two concise sentences with no extraneous information. The first sentence defines the scope and data sources, the second clarifies usage. Every sentence adds value, and the structure is front-loaded with the core purpose.

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 7 optional parameters and no output schema, the description effectively explains the tool's domain and typical use cases. It covers the main filtering dimensions (query, date range, category, regulator, jurisdiction) and ordering. Minor omissions like pagination handling or result format do not significantly hinder agent 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?

All 7 parameters have descriptions in the schema (100% coverage). The tool description adds minimal additional context beyond what the schema provides, such as 'Keywords matched against title and summary' which essentially repeats the schema for 'query'. Baseline 3 is appropriate as schema carries the full 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 specifies the tool searches regulatory publications from Canada, US, UK, and EU, and states it returns most recent matches first. This distinguishes it from sibling tools like get_regulatory_change (single item) and recent_regulatory_changes (just recent), making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use for questions about what a regulator has published on a topic, or what has changed in a date range,' providing clear context. However, it does not offer explicit guidance on when not to use this tool (e.g., for single document retrieval) or directly mention sibling tools as alternatives.

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