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diceuear

by io.github.pipeworx-io

Generate Avatar

generate_avatar
Read-onlyIdempotent

Generate a custom avatar SVG. Specify a style (e.g., 'avataaars', 'pixel-art', 'lorelei') and seed (e.g., username). Returns the SVG URL ready to display.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedYesA seed string that determines the avatar appearance. Same seed + style always produces the same avatar.
styleYesThe avatar style to use. Available styles: adventurer, avataaars, bottts, fun-emoji, identicon, initials, lorelei, micah, miniavs, notionists, open-peeps, personas, pixel-art, thumbs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe SVG URL for the generated avatar
seedYesThe seed string that determines avatar appearance
styleYesThe avatar style that was used
formatYesThe format of the avatar (always SVG)

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "format": {
+      "description": "The format of the avatar (always SVG)",
+      "enum": [
+        "svg"
+      ],
+      "type": "string"
+    },
+    "seed": {
+      "description": "The seed string that determines avatar appearance",
+      "type": "string"
+    },
+    "style": {
+      "description": "The avatar style that was used",
+      "type": "string"
+    },
+    "url": {
+      "description": "The SVG URL for the generated avatar",
+      "type": "string"
+    }
+  },
+  "required": [
+    "style",
+    "seed",
+    "url",
+    "format"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "seed": "john_doe",
+    "style": "avataaars"
+  },
+  {
+    "seed": "user123",
+    "style": "pixel-art"
+  }
+]
  3. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description doesn't need to repeat safety. It adds that the result is an SVG URL ready to display, which is useful context. No contradiction, but little extra behavioral detail beyond annotations.

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?

One precise sentence, front-loaded with the action, includes parenthetical examples for clarity, no filler words.

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

Completeness5/5

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

With two simple parameters, high schema coverage, annotations covering safety, and an output schema, the description is complete. It tells the agent what to expect (SVG URL) and how to call the tool.

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 covers both parameters with descriptions, including the full style list and determinism seed semantics. The description's examples reinforce this but add no new meaning, so baseline 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 tool generates a custom avatar SVG, specifies the two inputs (style and seed), and notes the output as an SVG URL. This is a specific verb+resource with distinct output, differentiating it from sibling tools like generate_llms_txt.

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

Usage Guidelines3/5

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

The description implies usage when an avatar is needed, and gives concrete examples of style values. However, it does not mention alternatives (e.g., list_styles to see available styles) or when not to use the tool, so guidance is minimal.

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

A4.1/5.0
Disambiguation4/5

Tools have mostly clear distinctions: ask_pipeworx variants differ by grounding/evidence guarantees, and meta-tools (discover_tools, suggest_questions) serve onboarding. However, ask_pipeworx_beta currently matches ask_pipeworx exactly, creating transient ambiguity, and deep_research vs ask_pipeworx overlap in routing capability though with different scopes.

Naming Consistency4/5

All tools use snake_case and most follow verb-first naming (ask_pipeworx, compare_entities, generate_avatar, subscribe). A few are descriptive nouns (recent_alerts, recent_changes, pipeworx_trending) but still readable and predictable. No mixed conventions; overall consistent style.

Tool Count2/5

33 tools is excessive for a single server, and many are auxiliary (avatar generation, memory, feedback) that do not serve the core data-access purpose. The primary question-answering capability is centralized in a few routers, making many separate tools feel redundant or unrelated, which dilutes navigability.

Completeness4/5

The core domain of structured data access is well covered with routing, grounded answering, deep research, entity profiles, comparisons, and claim validation. Subscription lifecycle (subscribe/unsubscribe/alerts) and memory (remember/recall/forget) round out the surface. Minor gaps like lack of direct tool invocation outside the router are covered by discover_tools, and no critical dead ends exist for typical queries.

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