Validate CORS policy against security best practices. Reports issues by severity.
| Name | Required | Description | Default |
|---|---|---|---|
| max_age | No | Access-Control-Max-Age in seconds | |
| allow_origin | Yes | Access-Control-Allow-Origin value(s) | |
| allow_headers | No | Allowed request headers | |
| allow_methods | No | Allowed HTTP methods | |
| expose_headers | No | Access-Control-Expose-Headers | |
| allow_credentials | No | Access-Control-Allow-Credentials |
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?
No annotations are provided, so the description carries the full burden. It discloses that the tool reports issues by severity, but it does not describe the output format, whether it reads external data, or any side effects. This is minimal behavioral insight.
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: the first states the action, the second states the report nature. It is front-loaded and 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?
With 6 parameters and no output schema, the description needs to explain the return value. 'Reports issues by severity' is too vague; it does not specify the exact output structure, severity levels, or how to interpret the results. This is inadequate for a validation 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?
All 6 parameters have descriptions in the schema (100% coverage), so the description need not add parameter details. It adds none, which is acceptable because the schema already handles parameter semantics.
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 validates CORS policies against security best practices, which is a specific verb+resource. It does not explicitly differentiate from sibling tools, but the sibling list contains no similar validation tool, so the purpose 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?
Usage is implied from the purpose: use when you need to validate CORS policy. However, there is no explicit guidance on when to use this tool versus alternatives, nor any conditions, prerequisites, or exclusions.
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 has a distinct purpose and target resource or operation. While some tools are thematically related (e.g., detect_secrets and classify_gdpr both analyze text), their specific outputs and use cases are clearly separated by names and descriptions.
Most tools follow a clear verb_noun pattern (convert_currency, generate_uuid, validate_iban), and the noun_to_noun conversion tools (csv_to_json, html_to_text) form a consistent sub-pattern. The mix of verb_noun and X_to_Y is understandable and predictable, though not uniform.
23 tools is on the higher end for a utility server, feeling like a grab-bag of many unrelated functions. While each tool is simple and serves a purpose, the count exceeds the typical well-scoped range, making it heavier than ideal.
The tool coverage is broad but scattered with no clear domain focus. Obvious complementary utilities are missing, such as URL encoding/decoding, YAML conversion, or PDF generation. However, within each small category, core operations are present, so agents can work around gaps.