prolog-reasoner

save_rule_base

Reuse Prolog rules across queries by saving them as named rule bases. Store stable knowledge like chess moves; place transient facts directly in code.

Instructions

Save a named rule base containing Prolog rules that can be reused across execute_prolog calls.

Use this for stable, reusable knowledge (e.g. piece_moves for chess piece movement rules). For one-time facts, include them directly in prolog_code instead.

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>",
      "content": "<content>"
    },
    "name": "save_rule_base"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`content`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.1.1May 1, 2026

TDQS

A3.8/5.0

Behavior2/5

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

No annotations are provided, so the description bears the full burden. It states 'Save' but does not disclose whether this overwrites existing rule bases, if any permissions are needed, or what the side effects are. The behavioral context is insufficient for a mutation tool.

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?

Two sentences front-load the action and scope, then provide a usage example and contrast. Every sentence adds value; no fluff.

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?

The description covers purpose and usage guidelines adequately, but lacks behavioral transparency and parameter semantics. Given the existence of an output schema (which presumably documents return values), completeness is moderate but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds minimal parameter detail. It mentions 'name' and 'content' but does not explain expected formats, constraints, or what constitutes valid Prolog rules. The parameters are left almost entirely to schema interpretation.

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 tool's purpose: 'Save a named rule base containing Prolog rules that can be reused across execute_prolog calls.' It uses a specific verb and resource, and distinguishes usage from including rules directly in prolog_code.

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?

Explicit guidelines are given: use for stable, reusable knowledge (e.g., chess piece movement rules), and for one-time facts, include them directly in prolog_code instead. This provides clear when-to-use and when-not-to-use advice.

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

Deploy Server