Signal Oracle

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

Annotations declare readOnlyHint=true and openWorldHint=true. The description aligns by noting data is 'resolved and fetched live if not already tracked', explaining side effects. It also details return content (up to 5 recent changes, current version) and paid limitations, adding full 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?

Three sentences front-loading purpose, inputs, and output. Every sentence earns its place with no 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?

Covers all necessary aspects: inputs, outputs (up to 5 changes, version), behavior (live fetch), and limitations (paid features). Output schema exists so detailed return structure is available externally.

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?

Input schema has 100% parameter descriptions. The description adds value by explaining that package and repo are alternatives (mutually exclusive) and clarifying the since parameter as ISO-8601 filter. This enriches schema information.

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?

Description clearly states it provides a free preview of breaking changes/new releases for software dependencies. It specifies inputs (npm/PyPI package or GitHub repo) and distinguishes itself from sibling preview tools by focusing on dependency 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?

The description indicates when to use the tool (for a free preview of dependency changes) and contrasts with paid full history but does not explicitly state when not to use or compare with similar tools like packagehealth_preview. However, sibling tools cover different domains, so context is clear.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false; description adds concrete details: approximate count of ~120 feeds, filtering options, and what the response contains (categories list). 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?

Three sentences, front-loaded with purpose, no filler. Every sentence adds value: scope, filtering guidance, and follow-up usage. Efficient and well-organized.

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 output schema exists, description need not detail return values. However, it mentions the response includes a `categories` list and number of feeds, which is helpful. Covers essential usage, filtering, and follow-up. Fully complete for this 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 coverage is 100%, so baseline is 3. Description adds meaning beyond schema: explains `compact` as 'keep payload small' and `category` as filter with example values from the response. Provides context missing from field descriptions.

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?

Description states specific verb 'List' and resource 'change-intelligence feeds' with detailed enumeration of included fields (source slug, label, question, prices, endpoints). Distinguishes from sibling tools by mentioning the returned `source` slug is used with `preview_feed`.

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?

Clear context for use: suggests filtering by `category` and using `compact: true` to reduce payload. Mentions follow-up action with `preview_feed`. Lacks explicit when-not-to-use or alternative tools, but context is sufficient.

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?

Annotations already provide readOnlyHint and openWorldHint. The description adds behavioral context by specifying the data fields included in the free preview and what is reserved for the paid version. It aligns with the read-only nature and does not contradict 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 two sentences long, front-loads the core purpose, and avoids unnecessary details. Every sentence adds value, making it efficient and easy to parse.

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 the tool's purpose, output scope (free vs paid), and key data points. Given the presence of an output schema and sibling tools with distinct domains, the description adequately informs an agent. Minor missing context (e.g., error handling) is acceptable.

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 100% coverage with clear descriptions for both parameters (package and ecosystem). The tool description does not add new information about the parameters beyond what is in the schema, so it meets the baseline.

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 a dependency's health, listing specific data points (current version, deprecation flag, OpenSSF Scorecard, etc.). It distinguishes itself from the paid version and sibling tools are in different domains (depwatch, list_feeds, etc.), so there is no ambiguity.

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 mentions it is a free preview and contrasts with the paid full verdict, but does not explicitly state when to use this tool versus sibling tools. The context implies it is for quick health checks, but no direct guidance on alternatives is provided.

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?

Annotations declare readOnlyHint=true and openWorldHint=true. The description adds context: the free preview returns up to 5 recent changes, the full feed is paid via x402, and optional parameters modify behavior. No contradiction 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 a single but dense sentence using semicolons to separate clauses. It packs all necessary information without unnecessary words. Slightly long but 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 output schema exists (not shown but present) and schema coverage is 100%, the description covers all key aspects: free preview limits, parameter purposes, and the paid model. It is complete for a preview tool with these 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 coverage is 100%, so baseline is 3. The description adds significant meaning beyond schema descriptions: it explains source comes from list_feeds, scope is an entity-id prefix, and package/repo/ecosystem are for dependency feeds. This helps the agent understand when and how to use each parameter.

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 it's a free preview of up to 5 recent changes for any feed, with a specific verb ('preview') and resource ('feed'). It distinguishes from sibling tools by being a generic preview that takes a source slug, while siblings are specific feed previews.

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 explains to pass the feed's source slug from list_feeds and describes optional parameters and their use cases (e.g., 'since' for time window, 'scope' for entity-id filter). It mentions the full feed is paid, implying when not to use it. However, it does not explicitly compare with sibling 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?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by specifying the return limit (up to 5 recent items) and the payment model for the full feed. No contradictions 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 very concise at three sentences, front-loading the core purpose. Every sentence adds necessary information (purpose, return limit, payment model). 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?

Given the simple nature of the tool (one optional parameter, output schema exists), the description covers the essential aspects: what it does, return limit, and premium version. It could be improved by noting that the 'since' parameter is optional or describing the output format, but overall it is sufficient.

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% for the single 'since' parameter, with a clear description in the schema. The tool description does not add extra meaning beyond what the schema already provides, so 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 clearly states it provides a free preview of recent Federal Register regulatory actions in a tracked industry vertical. It specifies the return limit of up to 5 items. While the tool name and title help distinguish it from siblings, the description does not explicitly contrast with other preview tools like tariffwatch_preview.

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 mentions it is a free preview and that the full version is paid, implying limited usage. However, it provides no guidance on when to use this tool versus sibling tools like depwatch_preview or tariffwatch_preview. The context of tracked industry vertical is implied but not elaborated.

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?

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds that it returns up to 5 recent changes and current duty-rate state for scoped codes, and that the full feed is paid. No contradiction 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?

Two sentences: first states purpose, second covers scoping, limitations, and payment context. No filler; 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 that an output schema exists, the description adequately explains inputs (HTS, since), output (up to 5 changes + current rate), and limitations (free preview, 5 items). The mention of paid alternatives sets expectations for 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 coverage is 100% for both parameters (hts and since). The description adds examples for hts (e.g., '6109') and mentions its role in scoping, but adds little to the 'since' parameter beyond the schema description. 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 'Free preview of recent US import-tariff changes', using specific verb 'preview' and resource 'tariff/HTS changes'. It also mentions optional HTS code scoping and limit of 5 changes, fully distinguishing from sibling tools like depwatch_preview or regwatch_preview.

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 indicates when to use this tool (free preview, optionally scoped) and mentions alternatives ('Full feed and LLM brief are paid via x402'). However, it does not explicitly state when not to use it, but the context of free vs paid is clear enough.

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?

Annotations already indicate readOnlyHint and openWorldHint. The description adds context about what data is returned (free data only) but does not disclose additional behavioral traits such as rate limits or 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?

Two concise sentences front-load the key information. Every sentence adds value, with no redundancy or 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?

Given the tool's simplicity, the existence of an output schema, and the annotations, the description adequately covers the tool's purpose and limitations.

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 schema already provides complete description for the single parameter 'name'. The description merely restates its use in the broader context without adding new parameter-level 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 provides a free preview of counterparty risk by showing tracked OFAC designations and product recalls. It distinguishes itself from the paid version and sibling tools by specifying its scope.

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 sets clear context: use for a free preview of specific risk data; for authoritative screening and risk verdict, use the paid tool. It does not explicitly exclude other scenarios but is sufficient.

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