Classify content you already have (status code + content-type + body sample) without an outbound fetch. Useful if your agent already fetched the URL via another tool.
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | ||
| body_sample | Yes | ||
| content_type | Yes |
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 provided, the description carries the burden of behavioral disclosure. It does disclose the key trait that the tool makes no outbound fetch, which is critical for a classification tool. However, it does not describe the output format, potential side effects, or any error behavior, leaving notable gaps.
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 and every word earns its place. The first sentence states the action and inputs; the second provides the usage context. No redundant or filler content.
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?
There is no output schema, so the description should explain what the tool returns, but it does not. It adequately covers the input semantics and when-to-use guidance, but lacks information about the classification result, success/failure behavior, or edge cases. For a relatively simple tool this is a moderate gap.
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 0%, so the description must clarify the parameters. It does so by naming all three parameters as 'status code + content-type + body sample', which maps directly to the schema properties. This adds meaningful semantics beyond the bare type definitions, though it does not provide format examples or constraints.
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 the specific verb 'Classify' with a clear resource: content the agent already has. It explicitly lists the inputs (status code, content-type, body sample) and distinguishes itself from sibling tools by stating 'without an outbound fetch', making its scope unambiguous.
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 a clear when-to-use scenario: when the agent has already fetched the URL via another tool. It implies an exclusion—do not use if an outbound fetch is needed—but does not explicitly name sibling alternatives or contrast with them beyond the fetch distinction.
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 operation: check fetches and analyzes a URL, classify works on already-fetched content, diff compares hashes over time, and resolve traces redirects only. The input and output contexts are clearly separated in descriptions, leaving little room for confusion.
All tools follow a uniform 'linkpulse_' prefix with a simple verb suffix: check, classify, diff, resolve. This consistent verb-only pattern makes the toolset predictable and easy to memorize.
Four tools cover the core needs of a link-checking utility without unnecessary bloat. Each tool adds a distinct capability—full inspection, offline classification, change detection, and redirect resolution—making the count well-scoped for the domain.
The tool set provides complete lifecycle coverage for the implied purpose: fetching and analyzing a link, resolving redirects, classifying content, and detecting changes. The wayback fallback in check also handles dead links, leaving no obvious dead ends or missing operations.