deterministic-logic
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| evaluate_booleanA | Evaluates a boolean logic expression given a variable assignment map. Operators: &&, ||, !, ^ (XOR), => (IMPLIES), <=> (IFF). |
| generate_truth_tableA | Generates a complete truth table for a boolean logic expression and analyzes whether it is a Tautology, Contradiction, or Satisfiable. |
| solve_satA | DPLL SAT solver for boolean satisfiability. Converts expression to Conjunctive Normal Form (CNF) and finds satisfying assignments or proves UNSAT. |
| evaluate_json_logicA | Evaluates deterministic JSON Logic rules against a context dataset. Supports boolean, comparisons, math, conditionals, and array rules. |
| evaluate_decision_tableB | Evaluates a matrix of decision rules against input context. Checks table for completeness and determinism. |
| analyze_state_machineA | Formally analyzes a Finite State Machine (FSM) for determinism, unreachable states, and deadlock states. |
| verify_state_reachabilityA | Checks whether a target state can be reached from the initial state in a state machine, returning the shortest path execution sequence. |
| simulate_state_machineC | Simulates a sequence of inputs step-by-step through a state machine deterministically. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool targets a distinct aspect of logic and state machine analysis: boolean logic evaluation, truth table generation, SAT solving, JSON logic evaluation, decision table analysis, FSM analysis, reachability, and simulation. No significant overlap.
All tools follow a consistent verb_noun pattern (evaluate_boolean, generate_truth_table, solve_sat, etc.), with clear verbs and specific nouns. The naming is predictable and easy to understand.
Eight tools is well-scoped for the domain, covering boolean logic, SAT, JSON logic, decision tables, and state machines without being too few or too many. Each tool serves a clear purpose.
The tool surface covers core operations for boolean logic (evaluate, truth table, SAT) and state machines (analysis, reachability, simulation). Minor gaps exist (e.g., no JSON logic validation, no state machine minimization) but do not hinder primary workflows.