check_riskFraud/security view of an IP: is it a VPN, proxy, Tor exit, datacenter/hosting, or mobile network, plus a 0-100 risk score and a one-line assessment. Answers "is this IP an anonymizer / bot / datacenter, or a clean residential IP?". Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | An IPv4 or IPv6 address to assess, e.g. "8.8.8.8" or "185.220.101.1". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "ip": "8.8.8.8"
+ },
+ {
+ "ip": "185.220.101.1"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by noting 'keyless' (no authentication) and describing the output components (risk score, one-line assessment). No contradictions.
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, no wasted words. Front-loaded with key output details and purpose. Every sentence contributes meaning.
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 single parameter and lack of output schema, the description is complete. It explains what the tool returns and the type of question it answers, satisfying the needs for selection and invocation.
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 coverage is 100%, so baseline is 3. The description does not add new information about the 'ip' parameter beyond what the schema provides (IPv4/IPv6 examples). The description could have clarified input format or limitations but does not.
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's purpose: fraud/security assessment of an IP address, listing specific detection types (VPN, proxy, Tor, etc.) and a risk score. It answers a precise question and is distinct from sibling tools like lookup_ip.
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 implies usage for security checks but does not explicitly distinguish when to use this tool over alternatives like lookup_ip or ai_visibility_check. It mentions 'keyless' but lacks guidance on 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.
Many tools are clearly distinct, but the existence of multiple ask_pipeworx variants (standard, beta, grounded) and the overlapping check_risk/lookup_ip tools create meaningful selection ambiguity. Description differentiation helps but doesn't fully resolve it.
All names use snake_case, but conventions vary between verb-noun (lookup_ip, compare_entities), noun phrases (entity_profile, recent_alerts), and domain-prefixed names (polymarket_edges, pipeworx_trending). It's readable but not a consistent pattern.
At 33 tools the surface is large, with duplicated ask_pipeworx variants, a modest IP lookup core, and a large number of meta/management tools (memory, subscriptions, onboarding, feedback). Even with a broad scope this feels overloaded, and it is well above the 25+ threshold.
The query domain is well covered: entity profiles, comparison, claim validation, deep research, changes, plus memory and subscription management. Minor gaps exist (no direct subscription update, no raw citation fetch utility), but agents can work around them.