What is explainability?

An explanation and auditing specialist for a knowledge graph, which stores facts and their connections. It traces the evidence behind conclusions and produces detailed explanation reports.

Use it to answer why a graph believes something, how a result was inferred, and whether a decision can be explained.

It makes graph-based decisions easier to inspect when you need to know how a conclusion was reached.

explainability — Agent for Claude Code by bibinprathap/VeritasGraph

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.

Clone the repo

git clone --depth 1 https://github.com/bibinprathap/VeritasGraph

Made for: Claude Code.

Or install veritasreason, the plugin that ships this one along with the rest of its 17 skills, 3 agents, 2 hooks.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/bibinprathap/veritasgraph/explainability/github.svg)](https://agentmods.dev/agents/bibinprathap/veritasgraph/explainability)

Your own site

<a href="https://agentmods.dev/agents/bibinprathap/veritasgraph/explainability"><img src="https://agentmods.dev/badge/agents/bibinprathap/veritasgraph/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/bibinprathap/veritasgraph/explainability"><img src="https://agentmods.dev/badge/agents/bibinprathap/veritasgraph/explainability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 71 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,132 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 95% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5.1	$0.00071	$0.01132
Opus 5.5	$0.00028	$0.00453
Sonnet 5.5	$0.00014	$0.00226
Haiku 4.5	$0.00007	$0.00113

Measured 2mo ago against content hash a633a6ead188, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

Origin

This is a copy

95% identical to explainability — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

veritas-reason/plugins/agents/explainability.md · 130 lines

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 VeritasReason library. You answer "why?" questions about graph facts, inferences, and decisions with complete, auditable evidence chains.

Your Domain

Explanation Generation

from veritasreason.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 veritasreason.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 veritasreason.kg.kg_provenance import GraphBuilderWithProvenance
from veritasreason.context.context_provenance import ContextManagerWithProvenance
from veritasreason.reasoning.reasoning_provenance import ReasoningEngineWithProvenance
from veritasreason.semantic_extract.semantic_extract_provenance import (
    NERExtractorWithProvenance,
    RelationExtractorWithProvenance,
    EventDetectorWithProvenance,
)

Read the full file on GitHub · 130 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.

2mo ago First seen · 130 lines · 71 tokens per session scan A a633a6ead188

Subscribe to this mod's changes

explainability is an agent published in the GitHub repository bibinprathap/VeritasGraph (326 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 1,132 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to explainability, differing in 20 lines, and is treated as a copy.

Analytics and metrics Data and AI LLM RAG and vectors generative-ai graph-rag information-retrieval nlp

explainability next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
explainabilitybibinprathap/VeritasGraph	Agent	326	2d ago	MIT	A	71	Claude Code
rag-pipeline-revieweraffaan-m/ECC	Agent	298k	4d ago	MIT	A	58	Claude Code
tokenjeremylongshore/tons-of-skills-marketplace	Agent	2.9k	yesterday	MIT	A	60	Claude Code
data-rag-architectroedyrustam/vibes-plug	Agent	121	yesterday	MIT	A	70	Claude Code, Cursor
wiki-qa-probebearlike/Assistant	Agent	43	7d ago	MIT	A	43	Claude Code
ai-engineerechoVic/blade-code	Agent	181	24d ago	MIT	A	48	Claude Code
rag-architectRBraga01/builder-ai	Agent	2	11d ago	MIT	A	35	Claude Code