Skip to main content
Glama

Enhance a prompt

enhance_prompt
Read-only

Free (same hourly allowance as the portal). Rewrites an image or video prompt into a stronger one; keeps quoted text, colours, counts and structured shot lists exactly, and returns those unchanged.

Args: kind: image | video. prompt: the draft, max 4000 chars (empty writes a starting one). context: one line of context (optional, max 500 chars).

Returns: {ok, prompt, unchanged?: true}

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": {
      "kind": "<kind>",
      "prompt": "<prompt>"
    },
    "name": "enhance_prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindYes
promptYes
contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true; the description adds real behavioral context beyond that — the cost model ('Free, same hourly allowance as the portal'), the exact-preservation guarantee for quoted text, colours, counts and shot lists, and the `unchanged?: true` return flag signaling when nothing was modified. It does not mention failure modes or what happens when a prompt cannot be improved, which keeps it short of a 5.

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?

Structured as an Args/Returns block with no filler sentences; each line conveys a distinct fact. The opening pricing note is slightly misplaced ahead of the purpose sentence, but nothing is redundant.

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

Completeness4/5

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

There is no output schema, yet the description supplies the return shape ({ok, prompt, unchanged?}), which is the key missing piece. For a three-parameter, read-only tool this covers what an agent needs, with only minor gaps around the meaning of `context` and error behavior.

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

Parameters4/5

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

With 0% schema description coverage, the description carries the full burden and mostly does: it explains `kind` (image | video), `prompt` (the draft, plus the non-obvious behavior that an empty string writes a starting prompt), and `context` (one line, optional). The one gap is that 'context' is never explained in terms of what content belongs there.

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 states a specific verb and resource: 'Rewrites an image or video prompt into a stronger one,' and scopes it to two kinds via the `kind` parameter. It does not name any sibling tool or explicitly contrast itself with the generation tools (generate_image, generate_video_clip), but the purpose is unambiguous on its own.

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?

Usage is implied rather than stated: an agent can infer this is a pre-step before image/video generation, and 'empty writes a starting one' hints at a drafting use case. There is no explicit when-to-use vs when-not guidance and no named alternative, so the agent must infer the workflow placement.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources