html_security_scan
Scan HTML for XSS-prone patterns (javascript: URLs, inline handlers, eval). Note: best-effort / heuristic — not a full language parser.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Scan HTML for XSS-prone patterns (javascript: URLs, inline handlers, eval). Note: best-effort / heuristic — not a full language parser.
| Name | Required | Description | Default |
|---|---|---|---|
| text | 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, the description carries full responsibility. It discloses the heuristic nature and mentions patterns, but critically omits what the tool returns (e.g., matched patterns, a boolean, or a report). The output behavior is unclear, which is a significant gap for a scanning tool.
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 concise sentences with no superfluous words. It front-loads the core purpose and adds an important caveat. 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?
Given the tool's simplicity (one param, no output schema), the description covers purpose, patterns, and limitations. However, the lack of output specification makes it incomplete for an agent to fully understand the tool's behavior. It is minimally complete but has a notable 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?
The single parameter 'text' has 0% schema description coverage. The tool description implicitly clarifies that 'text' is the HTML to scan, adding minimal semantics. However, no details on encoding, limits, or allowed characters are provided. This is adequate but not thorough.
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 'Scan HTML for XSS-prone patterns', listing specific patterns like javascript: URLs, inline handlers, and eval. It distinguishes from sibling tools such as html_encode or html_to_markdown by focusing on security scanning. The verb 'scan' and resource 'HTML' are specific, and the heuristic note adds nuance.
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 does not provide explicit guidance on when to use this tool versus alternatives like sql_danger_scan. It only implies usage for XSS scanning. No exclusions or context about prerequisites are given, leaving the agent to infer appropriate usage from the tool name alone.
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.
Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.
All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.
193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.
Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.