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ViralMint

by net.viralmint
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Revise an AI short plan

ai_short_revise
Read-only

Free. Changes an AI short's plan in plain words ("make it funnier", "music only", "15 seconds"). A question gets an answer in reply and the plan back unchanged. Nothing is made or charged.

Args: plan: the plan from ai_short_draft / ai_short_revise. instruction: what to change, 1-4000 chars. history: the history from the last answer (optional, max 40 turns). attachment_ids: staged image ids (up to 8).

Returns: The same shape as ai_short_draft.

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": {
      "plan": "<plan>",
      "instruction": "<instruction>"
    },
    "name": "ai_short_revise"
  }
}

Input Schema

NameRequiredDescriptionDefault
planYesThe `plan` from ai_short_draft / ai_short_revise.
historyNoThe conversation so far: pass back the `history` the last answer gave you.
instructionYes
attachment_idsNoStaged image ids (up to 8) the short may show or use as references.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond `readOnlyHint=true`, the description adds important behavioral context: the operation is free, nothing is created or charged, and question-style inputs return an answer in `reply` with the plan unchanged. This is unusually complete for a read-only planning tool.

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 compact and front-loaded: it states cost, purpose, question behavior, arguments, and return shape without wasted wording. The Args/Returns structure makes it easy to scan.

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?

For a 4-parameter tool with a nested `plan` object and no output schema, the description covers the essential behavior, parameter roles, and return shape by reference to `ai_short_draft`. It gives the agent enough to invoke the tool correctly and interpret a question response.

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

Parameters5/5

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

The description explains each parameter's role beyond the schema: `plan` comes from draft/revise, `instruction` is plain-language change text with examples and a length range, `history` is the prior conversation up to 40 turns, and `attachment_ids` are staged images. This meaningfully supplements the 75% schema coverage.

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 states a specific verb and resource: it revises an existing AI short plan using plain-language instructions. It also names the source of the `plan` from `ai_short_draft` / `ai_short_revise`, which helps distinguish it from initial drafting.

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

Usage Guidelines4/5

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

It clearly frames usage as revising an existing plan, and it explains the special case where a question produces a `reply` without changing the plan. It does not explicitly compare against sibling tools beyond referencing `ai_short_draft`, but the intended use is still clear.

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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