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Latent Defense MCP Server

Latent Defense MCP Server

Official
by latent-defense
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_inference_schedule

Set up a recurring JEPA inference schedule using a cron expression. Optionally target specific branches or run on all branches.

Instructions

Create a recurring JEPA inference schedule.

Args: name: Schedule name. cron: Cron expression (e.g. "0 2 * * *" for 2 AM daily). branch_labels: JSON array of branch label strings to target. Ignored if all_branches is true. all_branches: Run on all branches if true.

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": {
      "name": "<name>",
      "cron": "<cron>"
    },
    "name": "create_inference_schedule"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
cronYes
branch_labelsNo[]
all_branchesNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. However, it only describes parameters and lacks information about return values, side effects, authorization requirements, or error conditions. It does not go beyond stating the action 'create'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and structured with an 'Args:' block. However, some parameter descriptions like 'Schedule name' for 'name' are somewhat redundant but not overly verbose. It could be slightly tighter.

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?

Given the output schema exists (covers return values), the description is moderately complete. It explains all parameters but lacks usage context (e.g., when to use, side effects, or how the schedule interacts with other entities). A bit more context on scheduling behavior would improve completeness.

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?

Schema description coverage is 0%, so the description fully compensates by explaining all 4 parameters: 'name' (schedule name), 'cron' (with an example), 'branch_labels' (JSON array, ignored if all_branches true), and 'all_branches' (run on all branches). This adds significant meaning beyond the empty schema.

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 clearly states 'Create a recurring JEPA inference schedule', identifying the specific verb ('create') and resource ('recurring JEPA inference schedule'). It is distinct from sibling tools like 'run_inference' (one-time) and 'list_inference_schedules' (list).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. For example, 'run_inference' performs a one-time inference, and 'list_inference_schedules' lists existing schedules, but the description doesn't mention these distinctions or any prerequisites.

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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