lookup_ssl_cert_expiryCheck SSL certificate expiry for a domain. Returns issuer, valid dates, days remaining, and expired/expiring-soon flags. Use when monitoring certificate health.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check |
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?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds what data is returned (valid dates, days remaining, flags) but does not disclose additional behavioral traits like potential network latency, error conditions, or output formatting. This adds some context beyond annotations but is not extensive.
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?
Three short sentences: action, return data, usage context. All information is relevant, no filler. The structure is front-loaded with the primary purpose and follows with useful details.
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 read-only tool with one parameter and no output schema, the description is remarkably complete. It explains the purpose, the return data, and the usage scenario. Given the low complexity and the presence of annotations, no critical information is missing.
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 already describes the only parameter 'domain' as 'Domain to check' with 100% coverage. The tool description repeats this without adding format constraints, examples, or validation rules. Since schema coverage is high, the description adds minimal value beyond the schema itself.
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 states a specific action: 'Check SSL certificate expiry for a domain.' It lists the exact return values (issuer, valid dates, days remaining, expired/expiring-soon flags), making it distinct from broader sibling tools like lookup_ssl. The verb 'check' plus the resource 'SSL certificate expiry' is 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 includes 'Use when monitoring certificate health,' providing clear context for when to invoke this tool. It does not explicitly name alternatives or exclusion scenarios, such as contrasting with lookup_ssl, but the stated use case is sufficient for most situations.
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.
The tools are grouped into clear categories (dev, lookup, security, text, transform), which helps with disambiguation, but within categories there is some overlap. For example, lookup_ssl and lookup_ssl_cert_expiry both handle SSL certificates, and dev_url_encode/dev_url_decode are closely related but distinct. Most tools have unique purposes, but a few could be confused without careful reading of descriptions.
The naming follows a consistent snake_case pattern with a clear prefix structure (dev_, lookup_, security_, text_, transform_), which aids in organization. However, there are minor deviations like dev_cron_describe using 'describe' while others use verbs like 'generate' or 'convert', and some tools have longer names that break the verb_noun pattern slightly. Overall, the naming is predictable and readable.
With 49 tools, the count is excessive for a utility server, making it overwhelming and likely to cause confusion or inefficiency. While the tools cover many use cases, a more focused set of 15-25 tools would be more manageable and better scoped. The high number suggests feature bloat rather than a coherent, minimal surface.
The tool set is highly complete for its utility and development support domain, covering a wide range of operations from data transformation and security to lookups and text processing. There are no obvious gaps; each category provides comprehensive coverage, such as full text encoding/decoding, security functions, and various lookup capabilities, ensuring agents can handle diverse tasks without dead ends.