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Replace the feed's output schema

update_output_schema
DestructiveIdempotent

Sets the OutputSchema (controls the XML shape of the served feed). Pass null to revert to pass-through (use the source XML structure verbatim). Otherwise pass a full OutputSchema JSON. Use case: switching from RSS to Heureka SHOP/SHOPITEM shape, or mapping g:title → custom_name.

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": {
      "feedId": "<feedId>",
      "outputSchema": "<outputSchema>"
    },
    "name": "update_output_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
feedIdYes
outputSchemaYesFull OutputSchema JSON (see /api/feeds/[feedId]/output-preview) or null for pass-through.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare destructive=true and idempotent=true, so the safety bar is lower. The description still adds real behavior: null reverts to pass-through, and pass-through is defined as using the source XML structure verbatim. It does not say whether the existing schema is fully discarded without merge, nor whether a refresh_feed is needed for the change to take effect.

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?

Three compact sentences with the core verb and effect front-loaded, followed by the null-branch semantics and a concrete use case. No filler or repetition of the title.

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 destructive replacement on a live served feed, the description omits what happens to the previous schema, whether invalid schemas are rejected or leave the feed in a broken state, and the relation to refresh_feed. It covers the shape of the argument well but leaves lifecycle/consequence gaps.

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?

Schema coverage is 50% and feedId has no description anywhere, so the description must compensate. It explains the null branch semantically (pass-through = source XML verbatim) and that the non-null branch requires the complete OutputSchema JSON, which goes beyond the schema's terse note.

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?

States a specific verb and resource ('Sets the OutputSchema') plus the effect ('controls the XML shape of the served feed'), which cleanly separates it from siblings like update_field_rules, update_filter_rules, and preview_render. An agent knows exactly what this mutates without opening the schema.

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?

Concrete use cases are given ('switching from RSS to Heureka SHOP/SHOPITEM shape, or mapping g:title → custom_name'), which implies when to reach for this tool. It does not explicitly exclude alternatives (e.g. field rules vs. output schema) or state prerequisites such as needing platform specs first, so it falls short of a 5.

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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