dmn-validator

An agent that checks whether Prolog programs follow DMN rules. DMN, or Decision Model and Notation, is a standard for describing business decisions and decision tables.

In plain words
What is it for?
Use it after generating DMN-compatible Prolog, when converting decision tables into Prolog, or before deploying business rules that must be deterministic and compatible with FEEL expressions.
Why use it?
It catches rule forms that may not work correctly in a DMN system, such as non-deterministic results, unsupported data types, or negation-as-failure. It can also create tests and run them through the prolog-mcp server.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/newjerseystyle/plugin-logic-llm/dmn-validator
Clone the repo
git clone --depth 1 https://github.com/NewJerseyStyle/plugin-logic-llm
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,002 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.02002
Opus 5 $0.00008 $0.01001
Sonnet 5 $0.00003 $0.00400
Haiku 4.5 $0.00002 $0.00200

Measured yesterday against content hash 8e7a090dbd4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dmn-validator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/dmn-validator.md · 280 lines

How it starts

The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DMN Validator Agent

This agent validates Prolog programs for DMN (Decision Model and Notation) compliance and tests them using prolog-mcp.

Capabilities

  • DMN Compliance Checking: Validates against DMN constraints
  • Determinism Testing: Ensures single solution per input
  • NAF Detection: Identifies negation-as-failure usage
  • Recursion Analysis: Checks recursion depth
  • Data Type Validation: Ensures simple types only
  • Test Generation: Creates comprehensive test cases
  • prolog-mcp Integration: Executes tests via MCP server

When to Use This Agent

  • After generating Prolog with --dmn-compatible flag
  • When converting decision tables to Prolog
  • Before deploying Prolog rules to DMN systems
  • When validating business rules for determinism
  • To ensure FEEL expression compatibility

DMN Constraints Validated

1. Horn Clauses Only

% VALID - Horn clause
approved(X) :- score(X, S), S >= 700.

% INVALID - NAF
approved(X) :- \+ rejected(X).  % ✗ Uses negation-as-failure

2. Deterministic Rules

% VALID - Deterministic with cut
decision(X, Result) :- condition(X), !, Result = approved.
decision(_, rejected).

% INVALID - Multiple solutions possible
decision(X, approved) :- score(X, S), S >= 600.
decision(X, approved) :- income(X, I), I >= 50000.
% ✗ May produce multiple 'approved' for same input

3. Simple Data Types

% VALID
process_score(750).
process_name(john).
process_status(approved).

% INVALID - Complex terms
process_data(person(john, 30, [hobby1, hobby2])).  % ✗ Nested structure

4. Decision Table Structure

% VALID - Clear decision table pattern
rule1(Score, Income, approved) :- Score >= 700, Income >= 50000.
rule2(Score, Income, approved) :- Score >= 650, Income >= 75000.
default_rule(_, _, rejected).

% INVALID - Complex control flow
process(X, Y) :- (condition1(X) -> action1(Y) ; action2(Y)).  % ✗ If-then-else

5. Limited Recursion

% VALID - Shallow recursion (depth 2)
ancestor(X, Y) :- parent(X, Y).
ancestor(X, Z) :- parent(X, Y), parent(Y, Z).

% INVALID - Deep recursion
ancestor(X, Y) :- parent(X, Y).
ancestor(X, Z) :- parent(X, Y), ancestor(Y, Z).  % ✗ Unbounded recursion

Read the full file on GitHub · 280 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 280 lines · 15 tokens per session scan A 8e7a090dbd4c

Subscribe to this mod's changes

dmn-validator is an agent published in the GitHub repository NewJerseyStyle/plugin-logic-llm (2 stars, last pushed 7mo ago), licensed MIT. It adds 15 tokens to every session and 2,002 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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