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Ternary Intelligence Stack

rfi-irfos/ternlang

Your AI agent has two states. Ternlang gives it three. 30 tools — FREE, no key needed. The third state isn't null. It isn't "maybe". It's hold (trit=0) — a first-class routing instruction that tells your agent: evidence insufficient, gather more before committing. Every binary system that forces yes/no on ambiguous data is making a structural error. We fixed that. ⚡ trit_decide · trit_consensus · trit_vector · moe_orchestrate · ternlang_run · trit_audit ⚡ MoE-13 deliberation engine · EU AI Act Art.13/14/15 · BET VM (real compiler, not a sim) affirm = proceed. hold = wait. reject = block. Built in Graz, Austria by RFI-IRFOS. v1.0.0

Uptime
100.0%
2 direct probes · 30d
Response
461ms
last probe
Tools
40
callable
Resources
0
readable
Prompts
2
available

Tools · 40

trit_decide

Convert float evidence into a ternary decision (-1 conflict / 0 hold / +1 affirm) with confidence score and human-readable interpretation. The core ternary reasoning primitive.

trit_consensus

Balanced ternary consensus of two trit values: +1 if both affirm, -1 if both conflict, 0 (hold) for any disagreement. Use to merge two independent ternary judgements.

trit_eval

Evaluate a single ternlang expression on the live BET (Balanced Execution Trit) VM. Returns the trit result. Good for quick expression testing without writing a full program.

ternlang_run

Compile and run a complete .tern source program on the BET VM. Use for multi-statement programs, function definitions, struct usage, agent spawning, and tensor operations.

quantize_weights

Quantize f32 neural network weights to ternary {-1, 0, +1} using BitNet-style absolute-mean thresholding. Returns quantized weights, sparsity ratio, and effective compute savings.

sparse_benchmark

Benchmark sparse vs dense ternary matrix multiplication. Reports sparsity ratio, multiply-op count for both methods, and speedup factor. Demonstrates the @sparseskip efficiency gain.

moe_orchestrate

MoE-13 deliberation — routes your query through 13 specialised expert agents (deductive, inductive, safety, fact-check, causal, ambiguity, math, context, meta-safety, and more) with dual-key synergist…

moe_deliberate

EMA-based iterative deliberation engine. Feeds evidence round by round, applying exponential moving average smoothing, until the target confidence is reached or max_rounds is exhausted. Returns per-ro…

trit_action_gate

Multi-dimensional safety gate for action authorisation. Each dimension contributes weighted evidence; any dimension marked hard_block:true with negative evidence immediately vetoes the action and retu…

trit_upgrade

Returns a structured map of what is available free via MCP vs what unlocks with a paid API key: Tier 2 €24.99/mo (10k calls/mo), Tier 3 €49.99/mo (20k calls/mo), Tier 4 Enterprise (contact us). Unlock…

trit_mem_write

Write a memory entry to one of three layers: working (hot context, TTL 1h), session (flow patterns, TTL 24h), or core (identity anchors, never evicted). Annotate each entry with a trit confidence scor…

trit_mem_read

Read from three-layer memory using ternary attention. Each entry is scored: attention = key_overlap×0.35 + value_overlap×0.55 + trit_bias×0.10. Returns entries sorted by relevance. Attention trit: >0.…

trit_mem_consolidate

Run the three-layer memory consolidation cycle: (1) evict expired working entries; (2) promote affirm working entries to session with ternary compression; (3) promote long-lived affirm session entries…

trit_mem_stats

Return statistics for all three memory layers: entry counts, trit distribution (affirm/tend/reject), expired-but-not-yet-evicted entries, oldest and newest entry ages. Useful for debugging memory heal…

trit_mem_compress

Apply ternary sparsity compression to an entire memory layer in-place. Strips low-information sentences (density < 0.25) from every entry's value, keeps high-signal sentences verbatim, and truncates m…

trit_debate

Route two claims through MoE-13, compare their ternary verdicts, and return a tension score, synthesis, and AGREEMENT/CONFLICT/HOLD verdict. Useful for due-diligence, legal review, and argumentation a…

trit_uncertainty_map

Annotate every sentence (or paragraph) in a text with a trit value: +1 affirm (confident language), 0 tend (hedging language), -1 reject (contradicting language). Returns an uncertainty ratio and per-…

trit_calibrate

Analyse an AI agent's recent decision log for binary habituation. Detects how often the agent forced YES/NO when the evidence called for hold (tend). Returns a calibration score trit, binary ratio, an…

trit_translate

Convert binary control-flow code (Python if/elif/else, SQL CASE WHEN, JSON rule arrays) into equivalent .tern code with explicit tend arms injected wherever the original code had no coverage. Returns …

trit_eco_check

Evaluate a proposed action along two axes: human-optimal (via MoE-13) and eco-optimal (keyword heuristic). When they diverge, synthesis returns tend — a signal to find a path that serves both. Scoped …

trit_audit

Full TernAudit of an AI decision log. Returns binary habituation ratio, EU AI Act Article 13 (transparency) and Article 14 (human oversight) heuristic assessment, calibration score, and flagged decisi…

trit_vector

Multi-dimensional ternary evidence aggregation — the full agent reasoning tool. Provide named evidence dimensions each with a scalar value [-1.0, +1.0] and importance weight. Computes weighted-mean ag…

tsql_join

Ternary SQL Join. Unlike binary SQL (MATCH / NO-MATCH), a T-Join routes partial matches into a Deliberative Hold (State 0) for escrow audit — guaranteeing 100% data retention. Computes cosine similari…

audit_ternary_logic

Static code compliance audit. Detects Binary Habituation — over-reliance on true/false, bool types, and binary else branches — and returns a ternary calibration score with line-by-line Deliberation In…

get_industrial_standards

Returns the current triadic industrial standards published by RFI-IRFOS: T-TOKEN-v1.0 (tokenization), T-KV-CACHE-v1.0 (memory), T-Fi-v1.0 (compute billing), T-HAL-v1.0 (hardware abstraction), T-BIO-v1…

trit_compress

Ternary context compression. Score each text chunk by information density: high-signal chunks are kept verbatim (+1), medium-signal chunks are truncated to their first sentence (0/tend), low-signal ch…

trit_triage

Ternary triage and prioritisation. Score an array of text chunks against a query by word overlap, then sort: affirm (+1) = highly relevant, tend (0) = partially relevant, reject (-1) = not relevant. R…

trit_plan

Ternary task planner. Decomposes a goal into subtasks, scores each subtask by confidence and feasibility, and routes uncertain tasks into a deliberation queue. Returns an ordered plan with trit verdic…

trit_factcheck

Ternary fact-check engine. Decomposes a claim into sub-claims, scores each against an optional evidence corpus using word overlap, and returns an overall verdict: affirm (claim supported), tend (parti…

moe_full

Full 13-expert MoE orchestration with complete triad field, routing pair, per-expert verdicts, synergy scores, and deliberation trace. Returns the complete response including all expert voices and the…

llb_check

Last Look Back — blacklist check. Returns whether a path is protected by the LLB permanent blacklist (system paths, credential directories, kernel interfaces). Read-only — no disk mutation.

llb_classify

Last Look Back — safety tier classification. Classifies a path + operation into LLB safety tiers: T0/READ (low) → T1/CREATE (moderate) → T2/MODIFY (high) → T3/DELETE (critical). Each tier requires add…

llb_validate

Last Look Back — Gate 1 preflight. Validates a structured mutation request: checks blacklist, resolves path, assesses tier, and issues an authorisation verdict. No disk mutation occurs — this is the p…

llb_write_safe

Last Look Back — Safe Atomic Write advisory. Runs the full LLB preflight (Gate 1: blacklist + tier classification + intent validation) and returns a ternary verdict: +1 allow / 0 hold (local-only) / -…

engram_remember

Store an episode in your PRIVATE, durable episodic memory (ternlang-engram), namespaced to your X-Ternlang-Key and persisted on the server. Each memory is time-stamped and embedded with a ternary Trit…

engram_recall

Recall your most relevant private memories, ranked like human episodic retrieval: relevance × recency × salience × frequency. Recalled episodes are reinforced. Each hit carries a native propagated Tri…

engram_timeline

Return your memories whose timestamp falls within [from, to], in chronological order — the episodic-specific query a vector store cannot answer. Requires a valid key.

engram_consolidate

Run one consolidation pass on your memory: decay salience along a forgetting curve (vivid, frequently-recalled memories decay far slower) and evict memories below 'floor' that are older than 'min_age_…

engram_forget

Delete your memories — a GDPR right-to-erasure primitive. Provide 'id' for one episode, or 'before_ms' for everything older. Requires a valid key.

engram_stats

Health snapshot of your private episodic store: episode count, salience, native confidence, ternary sparsity, time anchor/latest/span, total recalls. Requires a valid key.

Prompts · 2

ternary_reasoning

Activate ternary reasoning mode. Use trit_decide or trit_vector when evidence is mixed or incomplete, moe_orchestrate for complex multi-faceted queries, and trit_action_gate before any irreversible ac…

decision_audit

Audit an AI system's decision log for binary habituation and EU AI Act compliance. Use trit_audit to detect over-reliance on YES/NO decisions, trit_calibrate to score calibration quality, and surface …

How to use

Add to your Claude Desktop / Cursor / Cline MCP config:

{
  "mcpServers": {
    "ternary_intelligence_stack": {
      "url": "https://ternlang.com/mcp",
      "transport": "http"
    }
  }
}