List all tracked APIs with metadata and latest changelog status. Filter by category (ai, payments, developer-tools, communications, infrastructure, email).
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter by category |
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.
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Tools are mostly distinct: list_tracked_apis focuses on API metadata, fetch_changelog retrieves entries, diff_versions compares time ranges, detect_breaking_changes filters by severity, search provides full-text, and subscribe_feed handles notifications. Slight overlap exists between detect_breaking_changes and fetch_changelog (both can return entries filtered by date), but descriptions clarify the breaking-change focus.
All tool names follow a consistent verb_noun pattern (detect_, diff_, fetch_, list_, subscribe_) with snake_case, and 'search' is a simple verb that fits the pattern. No mixed conventions.
Six tools is well-scoped for a changelog tracker, covering discovery, analysis, and subscription functionality without unnecessary bloat.
The core lifecycle is covered: listing APIs, fetching changelogs, detecting breaking changes, diffing versions, searching, and subscribing. Minor gaps include no unsubscribe/resubscription management and no single-entry detail view, but these are not critical for the primary use case.