api-changelog-tracker

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

No annotations are provided, so the description must fully disclose behavior. It mentions filtering and scanning all APIs but does not address side effects, authentication, rate limits, or the read-only nature of the 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 two sentences, front-loading the purpose, with no wasted words. Every 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?

With no output schema and four parameters, the description explains the tool's purpose and filtering but does not describe the output format or any other behavioral details needed for full 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 high (75% or more), so the baseline is 3. The description adds the note about omitting api_id to scan all APIs, but mostly restates schema information without significant new meaning.

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 detects breaking changes across one or multiple APIs, using a specific verb and resource. It distinguishes from siblings like diff_versions and fetch_changelog by focusing on breaking changes specifically.

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 by mentioning filtering options (severity, date) and the ability to scan all APIs. However, it does not explicitly compare to sibling tools or state when not to use it.

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 the core behavior (comparing and showing additions/removals) but does not specify whether it is read-only, any error scenarios, or limitations. With no annotations, the description carries full burden and provides only partial behavioral context.

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 filler: first states the purpose, second clarifies the output. Every word earns its place.

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 output schema and moderate complexity, the description is decent but could be improved by noting that it is a read-only operation or describing the format of the diff (e.g., list of changes). It does not fully cover potential usage 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?

The schema covers 2 of 3 parameters with descriptions (from_date and to_date as ISO 8601). The description reinforces the date range concept but does not elaborate on api_id. Parameter semantics are adequate but not exceptional.

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: comparing changelog state between two dates for an API and showing additions/removals. It distinguishes itself from sibling tools like 'fetch_changelog' (which likely retrieves the full changelog) and 'detect_breaking_changes' (which focuses on breaking 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?

There is no guidance on when to use this tool versus alternatives. No explicit when-to-use, when-not-to-use, or prerequisites are provided, leaving the agent to infer from the name and description alone.

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 fully convey behavioral traits. It minimally describes fetching and filtering but omits important details like rate limits, authorization needs, or what happens when no entries match.

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 sentence that conveys the core functionality efficiently. The list of APIs is inline but could be structured better; however, it remains concise and 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?

The tool has 4 parameters and no output schema. The description lacks details about return format, pagination, or ordering. Given moderate complexity, it is incomplete for an agent to anticipate results without additional 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 description coverage is 100%, so baseline is 3. The description adds minor value by listing supported APIs and mentioning date/breaking filters, but does not provide additional semantics beyond the schema's 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 'Fetch versioned changelog entries for a specific API' with a list of supported APIs and filtering options. This distinguishes it from sibling tools like detect_breaking_changes and 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 implies usage for fetching changelog entries but lacks explicit guidance on when to use this tool versus alternatives. No 'when not to use' or mention of prerequisites 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?

No annotations are provided, so the description carries full burden. It does not disclose important behavioral traits such as pagination, rate limits, whether it returns all APIs or only active ones, or any constraints beyond the optional category filter.

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 core purpose, and every word is useful. No redundancy or unnecessary 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?

With one optional parameter and no output schema, the description adequately covers what the tool does and its filter capability. However, it lacks details on output structure, pagination, or ordering, which would be helpful for a list 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?

The schema already describes the category parameter, but the description adds value by enumerating example categories (ai, payments, etc.), which is not present in the schema description. This enriches the semantic understanding 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 lists all tracked APIs with metadata and latest changelog status, and mentions filtering by category. This distinguishes 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 indicates when to use the tool (to list APIs, with optional category filter) but does not explicitly state when not to use it or suggest alternatives. The context of sibling tools provides some implicit 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 must disclose behavior. It mentions the fields searched and that it is full-text, but lacks details on pagination, ordering, or whether it is read-only (though implied). Adequate but could be more specific.

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 with no waste. Front-loaded with the core purpose, efficiently covering scope.

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 does not explain return format or result ordering. For a search tool, this is a moderate gap. However, the tool is simple and the missing details are somewhat inferable.

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 clear descriptions for all parameters. The description adds context for the 'q' parameter by listing search fields, but provides no additional meaning for 'limit', 'api_id', or 'breaking_only' beyond what the schema already offers.

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 performs full-text search across changelog entries and specifies which fields are searched (title, summary, change descriptions). It distinguishes itself from siblings like 'diff_versions' and 'fetch_changelog' by focusing on search, but does not explicitly differentiate.

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: use to search changelog entries. No explicit guidance on when to use this tool versus alternatives (e.g., 'detect_breaking_changes' or 'list_tracked_apis'), nor any exclusions or prerequisites.

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 available; description only states it returns a subscription ID. Lacks details on idempotency, error behavior, durability, or authentication needs. Minimal behavioral disclosure.

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?

Single sentence, 12 words, conveys core function and return value with zero redundancy. Optimal conciseness.

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 subscription tool with 4 parameters, no output schema, and no annotations, the description is too sparse. Lacks context on unsubscription, validation, rate limits, or error handling.

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 75%, so baseline is 3. Description adds no extra meaning beyond schema; it only mentions 'webhook or email' which are already in parameter 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?

Clear action verb 'register', specific resource 'webhook or email', and domain 'changelog update notifications'. Distinguishes from sibling tools (e.g., fetch_changelog, detect_breaking_changes) by focusing on subscription.

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 on when to use this tool over siblings, nor when not to use. No prerequisites, context, or selection criteria provided.

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