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Glama

validate_ip

Validate IPv4/IPv6

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYesIPv4 or IPv6 address

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • removedInput schema / properties / args
      Removed value: -{
      -  "description": "Tool arguments",
      -  "properties": {
      -    "text": {
      -      "description": "Primary input text",
      -      "type": "string"
      -    }
      -  },
      -  "type": "object"
      -}
    • addedInput schema / properties / ip
      Added value: +{
      +  "description": "IPv4 or IPv6 address",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[]New value: +[
      +  "ip"
      +]
  2. Added

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full burden, but it only states the operation name. It does not disclose what happens with invalid IPs (e.g., returns false, throws an error), what constitutes valid, or any edge cases. The behavior is essentially the tool name restated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded phrase with zero wasted words. It states the operation and scope efficiently, making it easy to scan and understand.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema or annotations, so the description should ideally clarify return behavior and validity criteria. It only says 'Validate IPv4/IPv6', which leaves out essential context for an agent to correctly interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter 'ip', which already documents 'IPv4 or IPv6 address'. The description adds no new parameter information, but since the schema covers it fully, the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific verb 'Validate' and the resource 'IPv4/IPv6', distinguishing it from sibling validation tools like validate_email or validate_domain. It is explicit and unambiguous about the tool's purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or cases where another validation tool would be more appropriate, leaving the agent without explicit usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2/5.0
Disambiguation1/5

Multiple tools have overlapping or identical purposes, such as ocr_url and ocr_image (both OCR from an image URL), compare_texts and text_diff (both compare or diff texts), extract_url and read_url (both extract webpage content), and content_hash and hash_text (both compute hashes). The boundaries between these tools are unclear, causing a high risk of misselection.

Naming Consistency2/5

Naming conventions are mixed. Many tools use verb_noun (extract_url, validate_email), but others use noun_verb (language_detect, html_clean), single words (advisor, crawl, retrieve), or noun_noun (job_status, page_metadata). This inconsistency makes it harder to predict tool names.

Tool Count1/5

With 100 tools, the server is extremely over-scoped for a generic agent toolkit. While some tools are distinct and useful, the sheer number does not align with a focused purpose; many tools are redundant or highly specialized, and the count exceeds what is typically manageable for an agent to reason about.

Completeness3/5

The toolkit covers a broad range of utilities including extraction, validation, processing, research, memory, and orchestration. However, there are no CRUD tools for creating/updating/deleting resources, no database or file system operations, and no integration beyond web/API basics. This leaves significant gaps for agents that need general lifecycle management, though it does handle many common tasks.