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Glama

Tools for Agents

by io.github.max124vip-dev

ssl_check

TLS certificate check

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
portNo
domainYesHostname

Schema Changelog

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

  1. Changed4 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 / domain
      Added value: +{
+  "description": "Hostname",
+  "type": "string"
+}
    • addedInput schema / properties / port
      Added value: +{
+  "default": 443,
+  "type": "integer"
+}
    • changedInput schema / required
      Previous value: -[]New value: +[
+  "domain"
+]
  2. Added

TDQS

D1.3/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to mention what the check entails—whether it validates expiry, trust chain, or just establishes a connection—and gives no insight into potential side effects or network usage.

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

Conciseness2/5

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

While the description is extremely short, this is under-specification rather than concise efficiency. A few key sentences about purpose and behavior would be more valuable than a three-word fragment that adds no information.

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

Completeness1/5

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

The tool has no output schema and no annotations, so the description is the only source of context. It fails to explain what the check returns, how to interpret results, or any prerequisites, making the tool essentially unusable for an AI agent.

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

Parameters1/5

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

Schema description coverage is only 50% (domain has a description, port does not), and the tool description adds zero information about parameters. It does not explain the role of 'domain' or 'port' beyond their raw names, leaving the agent to guess.

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

Purpose2/5

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

The description 'TLS certificate check' essentially restates the tool name without specifying any concrete action or output. It lacks a clear verb+resource structure and does not distinguish from sibling tools like dns_lookup or validate_url.

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

Usage Guidelines1/5

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 or how it differs from related tools. The description provides no context for selection, such as 'use for checking certificate validity or expiry'.

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.

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