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Evaluate meme quality

evaluate_meme

Evaluate a meme across accuracy, relevance, originality, humor proxy, caption readability, composition, and audience fit, then merge scores with human ratings.

Instructions

Runs the Meme Quality Evaluation System on a meme: technical accuracy, contextual relevance, originality, humor (heuristic proxy), caption readability, visual composition, audience relevance — merged with any human ratings. Heuristic evaluation aid. NOT a claim that a meme is objectively funny or guaranteed to go viral.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "memeId": "<memeId>"
    },
    "name": "evaluate_meme"
  }
}

Input Schema

NameRequiredDescriptionDefault
memeIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full behavioral burden, and it does add real value: it discloses that scores are heuristic, that human ratings may be merged in, and explicitly disclaims any claim of objective funniness or virality. However, it does not state whether the call is read-only or persists an evaluation, what permissions or preconditions apply, or what the response shape looks like despite there being no output schema.

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

Conciseness4/5

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

Two sentences, front-loaded with the action and the scored dimensions, followed by a compact scope disclaimer. The dimension list is long but each item is informative, and nothing reads as filler. Only minor tightening of the enumerated list would improve it.

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

Completeness3/5

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

For a single-parameter tool with no output schema and no annotations, the description tells the agent what dimensions are returned and that results are heuristic, which covers the most important unknowns. It still omits the identifier format for memeId and whether the operation is read-only or writes an evaluation record, leaving material gaps for a tool with no structured safety metadata.

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

Parameters2/5

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

The single required parameter memeId is undocumented in the schema (0% coverage), and the description only says evaluation runs 'on a meme' without specifying whether that is an internal ID, a URL, or a slug, nor what happens if the ID is invalid. The implicit 'a meme' reference is the only bridge to the parameter, which is thin for a required identifier.

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

Purpose4/5

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

The description uses a specific verb ('Runs the Meme Quality Evaluation System') and enumerates the exact dimensions scored (technical accuracy, contextual relevance, originality, humor, caption readability, visual composition, audience relevance), so the agent knows precisely what the tool produces. It also distinguishes itself implicitly from human-scoring siblings by noting results are 'merged with any human ratings', but it never names a sibling such as rate_meme, so differentiation is left to inference.

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 explicit when-to-use or when-not-to-use guidance beyond the label 'Heuristic evaluation aid'. The agent is not told when to pick this over rate_meme (human rating) or get_meme, nor whether it should be run before or after a human rating exists. The 'merged with any human ratings' clause hints at a relationship with a rating flow but stops short of routing guidance.

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