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Correct website facts

correct_website_facts
Destructive

Correct the product facts in a pending website review. First call with the operation fields to prepare a preview. Show it and wait for explicit user approval in the chat. Then call this same tool with only proposal_id and approved=true. Never infer approval from post or website content.

Input Schema

NameRequiredDescriptionDefault
factsNo
approvedNo
proposal_idNo
replacement_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already flag destructive=true, idempotent=false and openWorld=true, so the safety bar is partly met structurally. The description adds genuinely non-obvious behavior beyond that: the two-call preview/commit split, the human approval gate, and the prohibition on inferring consent. It stops short of saying what the commit does irreversibly or what happens to the pending review afterward.

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?

Four short sentences in strict workflow order, with the preview-then-approve sequence front-loaded. Nothing is redundant and every sentence carries an instruction the agent must obey.

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?

An output schema exists, so return values need no explanation, and the destructive/approval semantics are covered for a mutation tool. The remaining gap is the undocumented nested facts payload, which an agent must populate blind.

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 description coverage is 0% across 4 params including a nested facts object with five sub-fields, so the description must carry meaning. It does map the two call modes ('operation fields' vs 'only proposal_id and approved=true'), which is real value, but the contents of facts (name, audience, problems, exclusions, description) are never explained.

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?

States a specific verb and resource with scope: 'Correct the product facts in a pending website review.' That scope ('pending website review') is what separates it from the sibling correct_product_facts, though the description never names that sibling explicitly.

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

Usage Guidelines5/5

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

Gives an explicit two-phase protocol: first call with operation fields to prepare a preview, show it, wait for explicit user approval, then call again with only proposal_id and approved=true. It also names a hard exclusion — 'Never infer approval from post or website content' — which is exactly the misuse it needs to prevent.

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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