Odile Gate

Apply learned app routes and rate limit

gate_update_app

Destructive

Apply stored learning suggestions to an existing app and return the applied routes, suggested per-minute limit and learning-session metadata. Review gate_learn_suggestions first, then explicitly confirm; requires the project owner key or an admin member key. mode="extend" adds learned routes (default); "replace" removes existing routes before applying them. Both modes set the learned rate limit and keep the app key. Only learned suggestions can be applied: arbitrary routes or rate limits are not accepted, and this tool never starts learning.

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": {
      "project_id": "<project_id>",
      "admin_key": "<admin_key>",
      "app": "<app>",
      "confirm": "<confirm>"
    },
    "name": "gate_update_app"
  }
}

Input Schema

Name	Required	Description
`app`	Yes	The app id (app_...) with stored learning suggestions
`mode`	No	Extend existing routes (default), or replace them with learned routes; both set the suggested rate limit
`confirm`	Yes	Explicit confirmation to apply the reviewed learning suggestions
`admin_key`	Yes	The project owner key (ga_...) or an accepted admin member key (gm_...). Read it from the .env; never print it.
`project_id`	Yes	The project id from gate_create_project, e.g. p1a2b3...

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 1, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already mark the tool as destructive and non-idempotent, and the description adds important behavioral context: replace removes existing routes before applying new ones, both modes set the learned rate limit and keep the app key, only learned suggestions are accepted, and learning is never started.

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 dense but front-loaded and structured: it states what the tool does, the review/confirm requirement, authentication needs, mode semantics, and constraints in a few efficient sentences.

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, but the description names the returned data: applied routes, suggested per-minute limit, and learning-session metadata. Combined with explicit mutation and authentication context, it is complete for an agent to invoke correctly.

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 100%, so the schema already documents all parameters. The description still adds useful semantics by clarifying the default mode, the destructive replace behavior, the explicit confirm requirement, and the key type accepted.

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 applies stored learning suggestions to an existing app and returns applied routes, rate limit, and session metadata. It also clearly distinguishes this tool from gate_learn_suggestions by saying it never starts learning.

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?

It explicitly says to review gate_learn_suggestions first and then explicitly confirm, states the required owner/admin key, explains the default extend mode vs replace mode, and excludes arbitrary routes or rate limits. This gives clear when-to-use and when-not-to-use guidance.

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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