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aegis

aegis

by Acacian
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

evaluate_batch

Evaluate multiple AI actions at once against the governance policy to ensure compliance.

Instructions

Evaluate multiple actions at once against the governance policy.

    Each action dict should have: action_type, target,
    and optionally params, description, agent_id.

    Args:
        actions: List of action dicts to evaluate.

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": {
      "actions": "<actions>"
    },
    "name": "evaluate_batch"
  }
}

Input Schema

NameRequiredDescriptionDefault
actionsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions 'evaluate' which suggests a read operation, but does not explicitly state whether it is read-only, whether it modifies state, or any side effects. Missing details on permissions, rate limits, or error handling.

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 includes a one-line summary followed by a bullet-like list of required fields. It could be more structured (e.g., using proper Args format), but it avoids unnecessary verbosity and is easy to scan.

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?

While the output schema exists and may cover return values, the description does not mention what the tool returns (e.g., per-action results) or error handling. For a tool with one parameter, it covers input adequately but not output or edge cases. Some completeness is missing.

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?

The schema provides no parameter descriptions (0% coverage), so the description adds value by specifying that each action dict should contain 'action_type', 'target', and optionally 'params', 'description', 'agent_id'. However, it does not define the types or expected formats for these fields, leaving ambiguity.

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 the verb 'Evaluate multiple actions at once against the governance policy' and distinguishes from the sibling 'evaluate_action' by emphasizing batch processing. It also lists the required fields for each action dict, making the purpose unambiguous.

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?

It implicitly advises using this tool for batch evaluation of multiple actions rather than single-action evaluation, but does not explicitly contrast with alternatives like 'evaluate_action' or state when not to use it. Could be more explicit about the batch vs. single distinction.

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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