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semantic-saga-mcp

semantic-saga-mcp

by ananthaprakashb
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_actions

List active action contracts, schemas, semantic effects, risk, hashes, and execution policies to inspect allowed side effects and their failure compensation safeguards.

Instructions

List active action contracts, schemas, semantic effects, risk, hashes, and execution policies.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_actions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are present, so the description must disclose behavior on its own. 'List' implies a read-only operation, and the description enumerates what is returned, which is helpful. However, it does not mention authorization requirements, pagination, filtering behavior, or how 'active' is determined.

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?

A single sentence that front-loads the verb and resource while compactly enumerating the returned facets. There is no filler or redundancy.

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?

With no parameters, no output schema, and no annotations, the description does the necessary work by naming the six content types returned and signaling this is a listing operation. It is reasonably complete, though it could be stronger with a note on response shape or the meaning of 'active'.

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?

The tool has zero parameters and the schema is empty, so there is no parameter semantic burden. The description adds useful context by enumerating the categories of data returned, which is the main information an agent needs.

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?

The description uses a specific verb 'List' and names the resource: active action contracts, schemas, semantic effects, risk, hashes, and execution policies. This clearly identifies the tool's function and implies a broad inventory view that distinguishes it from singular tools like get_action, though it does not explicitly name a sibling.

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

Usage Guidelines3/5

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

The phrase 'active action contracts' gives implied context that this is for surveying currently active actions rather than retrieving a single action or checking policies. However, it provides no explicit when-to-use guidance or exclusions pointing to alternatives such as get_action or get_policy_status.

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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