api-changelog-tracker

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 filtering behavior and the all-APIs scan option, but it does not explicitly state that the operation is read-only or describe the output format. This leaves some behavior ambiguous, though the tool name implies analysis rather than mutation.

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 three short sentences that front-load the main purpose and include key usage nuances without any redundant 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 description covers the core function, scope, and filtering options. It lacks an explicit statement about return values, but since no output schema exists, this is a minor gap. For a tool with four parameters and no annotations, the description provides sufficient context for an agent to select and invoke it.

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 covers 75% of parameters with descriptions. The description adds a useful tip about omitting api_id to scan all APIs, but largely restates the filter options (severity, date) that are already in the schema. Thus it adds only marginal 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 with a specific verb (detect) and resource (breaking changes). It also notes the scope (one or multiple APIs) and distinguishes itself from sibling tools like diff_versions and fetch_changelog by focusing on breaking changes detection.

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 usage context by explaining that severity and date filters are available and that omitting api_id scans all APIs. However, it does not explicitly mention alternatives or when-not-to-use, so it falls short of a 5.

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 of disclosing behavior. It transparently states the operation is a comparison that outputs added/removed items, which covers core behavior. However, it does not disclose potential limitations like pagination, sorting, or whether modifications are included, leaving some behavioral aspects opaque.

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 primary action ('Compare changelog state...') and then clarifying the output. Every word earns its place, with no redundant 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 3-parameter tool with no output schema and no annotations, the description gives a basic understanding of purpose and result (added/removed). However, it lacks detail on output format, edge cases, or any required context, making it only partially complete for a new agent.

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 covers 67% of parameters with descriptions (from_date/to_date as ISO 8601). The tool description adds no parameter-specific details beyond implying api_id identifies the API and the dates set the range. This is adequate but does not substantially enhance 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 that the tool compares changelog state between two dates and shows what was added or removed, using a specific verb and resource. It distinguishes itself from siblings like fetch_changelog (full retrieval) and detect_breaking_changes (impact analysis) by its time-bounded comparison, though it doesn't explicitly name alternatives.

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 a changelog diff over a date range is needed, but it provides no explicit guidance on when to use this tool versus siblings or any exclusionary cases. No alternatives are mentioned, leaving the 'when' somewhat inferred.

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 must carry the full transparency burden. It only states what the tool does (fetch entries and filters) but does not disclose pagination behavior, default ordering, error handling, or what the response looks like. This is a significant gap for an un-annotated 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, information-dense sentence that starts with the action and resource. It is concise, covers the key features, and avoids any redundant wording.

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 output schema, the description should clarify return format and default behavior, but it only says 'fetch entries' and leaves response details and pagination unstated. Given the simple parameter set, it is 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 schema already describes all four parameters, but the description adds value by listing valid api_id values (openai, anthropic, etc.) and summarizing the filter options. This goes beyond the schema's generic 'API identifier' and justifies a score above 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 action (fetch) and resource (versioned changelog entries for a specific API), and enumerates the supported API identifiers. It also mentions filtering by date and breaking-only, which distinguishes it from sibling tools like diff_versions and 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 implies usage when you need changelog entries for one of the listed APIs, but it does not explicitly compare with alternatives such as detect_breaking_changes or search. It lacks explicit exclusions or 'when not to use' guidance.

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. It adds context about the output including metadata and latest changelog status, but does not mention potential pagination, authentication requirements, rate limits, or that this is a read-only operation. The description is not misleading but lacks depth.

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, front-loaded with the primary purpose, and includes the key filtering detail in the second sentence. Every word earns its place 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?

For a simple list tool with one optional parameter and no output schema, the description adequately conveys the return content ('metadata and latest changelog status') and filtering options. It could be slightly more complete by noting the default category behavior or potential result limits, but overall it is sufficient for the tool's simplicity.

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 only states 'Filter by category', but the description enriches it by enumerating the valid categories (ai, payments, developer-tools, communications, infrastructure, email). This goes beyond the schema and helps the agent understand acceptable values. Given the high schema coverage, this additional semantic detail justifies a 4.

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 lists all tracked APIs, which is a specific verb+resource combination. It also includes the scope of the operation ('all tracked APIs') and the kind of information included ('metadata and latest changelog status'), distinguishing it from sibling tools like detect_breaking_changes or fetch_changelog.

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 browsing or listing all tracked APIs, with category filtering. However, there is no explicit guidance on when to prefer this over search or other sibling tools, nor any exclusions or alternative scenarios.

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 must carry the behavioral burden. It adds useful context by listing the searchable fields, but does not disclose other behaviors such as result ordering, case sensitivity, or handling of empty results. This is adequate 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?

The description is two concise sentences, front-loaded with the main action and then relevant details. 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 four parameters and no output schema or annotations, yet the description only explains its scope. It does not discuss when to prefer this tool over siblings or what the return payload looks like, leaving some gaps for a search 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 the baseline is 3. The description adds a little value by explaining what the query searches across (title, summary, change descriptions), but does not elaborate on limit, api_id, or breaking_only beyond their schema 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?

The description clearly states the tool performs full-text search across all changelog entries, specifying the exact fields searched (title, summary, change descriptions). This distinguishes it from sibling tools like fetch_changelog or diff_versions, which have 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 description conveys clear context for use: searching across all changelog entries. However, it does not explicitly mention alternatives or when not to use this tool, so it stops short of a 5.

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 full responsibility for behavioral disclosure. It mentions returning a subscription ID but omits any side effects, such as whether a confirmation is sent, idempotency, permission requirements, or behavior on invalid inputs. The mutating nature of the operation is also not explicit.

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, using two short sentences with no filler. The key action is front-loaded ('Register'), and the return value is stated clearly, making it easy to grasp quickly.

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 4 parameters and no annotations or output schema, the description is incomplete. It does not explain the relationship between email and webhook_url, the role of api_id (the only required field), or the notify_breaking_only option. This lack of parameter guidance could lead to incorrect invocation despite the clear overall purpose.

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 75%, with api_id undocumented, and the description does not compensate by explaining that api_id refers to the tracked API. It does add some context that email and webhook_url are alternative notification methods, but it does not clarify if they are mutually exclusive or how notify_breaking_only behaves, 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 tool's specific action ('Register') and resource ('webhook or email') within the context of 'changelog update notifications', and it distinguishes itself from siblings by focusing on subscriptions rather than on-demand change detection. Mentioning the return of a subscription ID further clarifies its unique 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 setting up notifications but does not explicitly state when to choose this tool over alternatives like fetch_changelog. It lacks explicit prerequisites (e.g., having a tracked API) and does not discuss exclusions or alternative tools, leaving usage guidance mostly implied.

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