Xyla AI

Ask for a post fix

request_post_fix

Starts a fix for one post's image or video in this Xyla shop. Xyla first checks the media for a problem on its side, which makes the fix free; otherwise the fix costs credits. Nothing is changed or charged yet. Then call post_fix_status with the audit_id to learn the cost, tell the merchant, and call confirm_post_fix only once they agree.

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": {
      "post_id": "<post_id>",
      "what_to_change": "<what_to_change>"
    },
    "name": "request_post_fix"
  }
}

Input Schema

Name	Required	Description	Default
`post_id`	Yes	The ID of the post to fix.
`what_to_change`	Yes	What the merchant wants changed, in their words.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 22, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations only cover the safety profile (readOnly=false, destructive=false, idempotent=false, openWorld=false); the description adds the crucial behavioral facts: nothing is changed or charged at this stage, and the fix is free if Xyla finds the problem on its side, otherwise it costs credits. That is real disclosure beyond structured fields.

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, front-loaded with what it does, then cost behavior, then the exact follow-up sequence. No filler and no repetition of schema or annotations.

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?

No output schema exists, yet the description covers what an agent needs: what happens on invocation (nothing charged yet), how cost is determined, and which tool to call next with which identifier. Nothing material is missing for correct invocation.

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 100%, so both parameters are already documented in the schema. The description implies the post target and that the change is phrased in the merchant's own words, but adds no format or constraint detail beyond that. Baseline 3 applies when the schema does the heavy lifting.

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 with scope: 'Starts a fix for one post's image or video in this Xyla shop.' The two-phase framing (request → status → confirm) makes it unmistakable against siblings like confirm_post_fix and post_fix_status.

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?

Explicitly sequences the workflow: call post_fix_status with the audit_id to learn the cost, tell the merchant, and call confirm_post_fix only once they agree. This names the alternatives and the exact condition that selects each, leaving nothing to inference.

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

All Xyla AI tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?