Semantica is an open-source infrastructure layer that turns enterprise data into structured context and knowledge graphs, where ontologies define meaning and graph reasoning connects facts and decisions. It is intended for AI systems and agents that need traceable, governed, and explainable context in high-stakes domains. The catalogue add-ons provide agent workflows, hooks, and plugins for operating Semantica.
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.
git clone --depth 1 https://github.com/semantica-agi/semanticaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/semantica-agi/semantica/explainability)<a href="https://agentmods.dev/agents/semantica-agi/semantica/explainability"><img src="https://agentmods.dev/badge/agents/semantica-agi/semantica/explainability/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/semantica-agi/semantica/explainability"><img src="https://agentmods.dev/badge/agents/semantica-agi/semantica/explainability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.01129 |
| Opus 5.5 | $0.00028 | $0.00452 |
| Sonnet 5.5 | $0.00014 | $0.00226 |
| Haiku 4.5 | $0.00007 | $0.00113 |
Grade A, and why
explainability 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 2mo ago.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- explainability — 95% identical, 20 lines differ
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Reasoning Transparency and Explainability Specialist for the Semantica library. You answer "why?" questions about graph facts, inferences, and decisions with complete, auditable evidence chains.
Your Domain
Explanation Generation
from semantica.reasoning.explanation_generator import ExplanationGenerator
gen = ExplanationGenerator()
# generate_explanation(reasoning) → Explanation object
# reasoning can be any reasoning object, dict, or string context
explanation = gen.generate_explanation(reasoning=reasoning_input)
# explanation.summary, .confidence, .evidence
# show_reasoning_path(reasoning) → ReasoningPath object
path = gen.show_reasoning_path(reasoning=reasoning_input)
# path.steps: [Step(type, description, confidence)]
# path.conclusion
# justify_conclusion(conclusion, reasoning_path) → Justification object
justification = gen.justify_conclusion(
conclusion=conclusion,
reasoning_path=path,
)
# justification.is_justified, .confidence, .supporting_steps, .opposing_factors
Decision Explainability
from semantica.context import AgentContext, ContextGraph
ctx = AgentContext(decision_tracking=True, advanced_analytics=True)
# Full decision explainability trace
explainability = ctx.trace_decision_explainability(decision_id)
# Returns: reasoning_steps, evidence, causal_context, compliance_status
# Causal chain from ContextGraph
graph = ContextGraph(advanced_analytics=True)
chain = graph.trace_decision_chain(decision_id, max_steps=5)
causality = graph.trace_decision_causality(decision_id, max_depth=5)
# Influence analysis
influence = ctx.analyze_decision_influence(decision_id, max_depth=3)
Provenance Tracing
from semantica.kg.kg_provenance import GraphBuilderWithProvenance
from semantica.context.context_provenance import ContextManagerWithProvenance
from semantica.reasoning.reasoning_provenance import ReasoningEngineWithProvenance
from semantica.semantic_extract.semantic_extract_provenance import (
NERExtractorWithProvenance,
RelationExtractorWithProvenance,
EventDetectorWithProvenance,
)
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.
- 2mo ago First seen · 130 lines · 71 tokens per session scan A a73c28889e9b
explainability is an agent published in the GitHub repository semantica-agi/semantica (14,446 stars, last pushed yesterday), licensed MIT. It adds 71 tokens to every session and 1,129 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
explainability compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| explainabilitysemantica-agi/semantica | Agent | 14k | yesterday | MIT | A | 71 | Claude Code |
| context-curatorhashgraph-online/hol-cigar | Agent | 8 | 10d ago | Apache-2.0 | A | 23 | Claude Code |
| handoff-curatorhashgraph-online/hol-cigar | Agent | 8 | 10d ago | Apache-2.0 | A | 24 | Claude Code |
| effect-reviewerhashgraph-online/hol-cigar | Agent | 8 | 10d ago | Apache-2.0 | A | 29 | Claude Code |
| gsd-phase-researcheropen-gsd/gsd-core | Agent | 11k | yesterday | MIT | A | 41 | Claude Code, Codex |
| gsd-project-researcheropen-gsd/gsd-core | Agent | 11k | yesterday | MIT | A | 48 | Claude Code, Codex |
| gsd-project-researcheropen-gsd/gsd-core | Agent | 11k | yesterday | MIT | A | 48 | Claude Code, Codex |