ForgePoint Signal

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description bears full burden. It discloses update frequency ('Updated daily') and data source ('Federal Register and IRS Internal Revenue Bulletin'), indicating no destructive effects. However, it does not mention caching or pagination behavior.

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. The first states the core purpose, the second provides use case and data source. 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?

The tool has 2 parameters with 0% schema coverage and no output schema. The description fails to explain what the output contains (e.g., fields, format) or how parameters affect results. It is incomplete for effective agent decision-making.

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%, so the description must compensate. It fails to explain either parameter: 'limit' and 'impact_level' are not described. The description emphasizes 'high-impact' but the schema includes low/medium options, creating a mismatch. No additional meaning is added 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 tool retrieves 'the most recent high-impact regulatory changes sorted by impact level'. It uses a specific verb ('Get') and resource ('recent high-impact regulatory changes'), distinguishing it from siblings like 'get_regulation_detail' (detail of a specific regulation) and 'search_regulations' (generic search).

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 usage context: 'Ideal for daily briefings or monitoring material changes requiring immediate attention.' It implies when to use (for high-impact recent changes) but does not explicitly state when not to use or mention alternatives like 'preview_regulations' for previews.

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 must disclose behavioral traits. It states the data source (Federal Register and IRS Internal Revenue Bulletin) and implies a read operation, but does not mention authentication, rate limits, or response format. Adequate but not thorough.

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: the first explains the action and output fields, the second states the data source. No unnecessary words, well front-loaded.

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 one parameter, no output schema, and no annotations, the description provides sufficient context: it lists the fields returned and data source. It could mention error handling or return format, but for a simple detail retrieval tool, it is nearly 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 sole parameter entry_id has no schema description (0% coverage). The description adds context by referring to 'specific regulation entry', indicating the parameter is an identifier, but lacks format or example. This adds some value but not full compensation for the lack of schema description.

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 retrieves complete detail for a specific regulation entry, listing included fields like full summary, affected law, effective date, and source link. It differentiates from siblings such as search_regulations and preview_regulations.

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 explicit guidance on when to use this tool versus alternatives like get_recent_by_impact or search_regulations. The description implies it is for a known entry_id but does not compare or exclude other tools.

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 burden. It discloses that the tool is free, returns only the 5 most recent updates, covers specific tax areas, and is updated daily from authoritative sources. It does not mention any destructive actions or rate limits, which is acceptable for a read-only preview.

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?

Three sentences with no filler, front-loaded with the core action 'Get a free preview.' Every sentence provides essential information without 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?

For a simple tool with no parameters and no output schema, the description is complete: it explains the source, update frequency, domain, and limitation to 5 items. It could specify the output format, but it's sufficient for an agent to understand what to expect.

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 parameters, so the baseline is 4. The description adds meaning by explaining what the preview contains (most recent 5) and the tax law coverage, which is beyond the empty 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 tool provides a free preview of the 5 most recent US regulatory changes in estate, trust, gift, and inheritance tax law. It distinguishes from siblings like 'get_recent_by_impact' and 'search_regulations' by specifying the scope and recency.

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 obtaining an initial overview of recent changes, but lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools. The context is clear but could benefit from mentioning alternatives.

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 discloses the data source (Federal Register, IRS Bulletin), update frequency (daily), and return type (full entries with summaries and links). It lacks details on limits, pagination, or error behavior, but for a read-only search tool, this is largely sufficient.

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 tightly packed sentences. The first sentence front-loads the action and key filters, and the second provides return content and update frequency. No wasted words; each sentence adds value.

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

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

Given no output schema and 0% schema coverage, the description should be more thorough. It covers search filters but omits details on the 'limit' parameter, default behavior for empty queries, and result ordering. For a tool with 5 parameters and no schema descriptions, this is adequate but not comprehensive.

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%, so the description must compensate. It adds meaning by listing allowed values for jurisdiction (federal/state) and impact level (low/medium/high), and examples for category. However, it does not mention the 'limit' parameter or the 'query' parameter's nature (keyword string). It partially covers the 5 parameters but leaves gaps.

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 searches a specific regulatory database with multiple filter options (keyword, jurisdiction, category, impact level) and describes the return content (full entries, summaries, links). It effectively distinguishes from sibling tools like get_recent_by_impact and get_regulation_detail by focusing on the full search capability.

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 when to use the tool (for comprehensive search with filters) but does not explicitly state when not to use it or mention alternatives. For example, it could clarify that for a specific regulation's details, 'get_regulation_detail' is more appropriate.

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