List every package with breaking-change data available, including tracked versions and how many breaking changes each has. Call this first if you are unsure whether a package is covered.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It explicitly states the tool lists packages and returns tracked versions and breaking-change counts, implying a safe, read-only operation. It does not mention side effects, pagination, or performance, but for a simple list operation the description is transparent enough about what to expect.
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, front-loaded with the main action and output details, followed by a usage hint. Every word earns its place; no fluff 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?
For a simple list tool with no parameters and an output schema, the description is complete. It covers what the tool does, what information it returns, and when to use it. The presence of an output schema handles return format details, so no further elaboration is needed.
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 tool has zero parameters, so the schema is empty. The description adds meaning by explaining the purpose and what the returned data represents, which is more valuable than the schema alone. Given the baseline for no parameters is 4, this 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 uses a specific verb ('list') and clearly defines the resource ('every package with breaking-change data available') and the output contents (tracked versions, counts). It differentiates from siblings by framing itself as a coverage discovery tool, distinct from check_upgrade_safety and get_breaking_changes which likely target specific packages.
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 explicit guidance: 'Call this first if you are unsure whether a package is covered.' This clearly indicates when to use the tool, though it does not name specific alternatives or exclusions. The context is sufficient for an agent to decide when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct role: list_packages for discovery, get_breaking_changes for detailed data, and check_upgrade_safety for an actionable summary. No two tools overlap in purpose, making selection straightforward.
All tool names follow a consistent verb_noun pattern (list_packages, get_breaking_changes, check_upgrade_safety). The verbs clearly indicate the action and the nouns the target, creating a predictable and readable naming scheme.
Three tools are well-scoped for a focused migration data server: one for discovering coverage, one for retrieving details, and one for safety checks. This is neither minimal nor excessive, fitting the domain perfectly.
The server covers the full workflow: identify if a package is tracked, retrieve comprehensive breaking change details, and get upgrade safety guidance. No obvious gaps such as missing version comparisons or update/save operations are needed in this read-only context.