truth first
by Roy Yuen
Eliminate hallucinations with an evidence-first verification framework for system state, configs, and file contents.
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15 skills found
by Roy Yuen
Eliminate hallucinations with an evidence-first verification framework for system state, configs, and file contents.
by 王晓菲
Eliminate hallucinations and errors using double-blind, multi-agent adversarial verification loops.
by Sir Benjamin
A lightweight defensive layer that prunes hallucinations and boosts reasoning quality for 8k-32k context agents.
Audit, verify, and format academic citations across AMA, APA, and Vancouver styles to eliminate AI hallucinations.
Audit any AI-generated output for unsupported claims, then verify every factual and technical assertion against its real source before it ships.
Audits any AI draft for unsupported claims — flags each one, grades its source, and returns a substantiation report.
A pre-publish audit gate to extract claims, verify facts, and flag compliance risks in public-facing content.
Runs an ordered evidence-integrity gate over any AI draft — grade sources, ground claims, verify technical assertions, stress-test — then returns one PASS/REVISE/FAIL ship decision.
by Nex AI
Stop AI hallucinations in cold email with server-side legal footers and Belgian GDPR compliance guardrails.
Stop leaving your AI startup exposed to malicious users trying to steal your proprietary system prompts or bypass your paywalls. The AI Prompt Injection Defense Shield is an automated code review agent that deeply analyzes your Next.js or Python backend, instantly detecting insecure LLM input fields, un-sanitized API data streams, and weak prompt boundaries. By automatically generating the exact copy-paste code patches required to harden your AI wrapper against the latest OWASP top 10 LLM vulnerabilities, this skill allows solo developers and indie hackers to confidently launch their SaaS without the fear of massive, unexpected API billing spikes or catastrophic data leaks.
by Kaymue
Diagnose broken RAG systems. 8 failure categories: chunking, embeddings, retrieval, reranking, hallucination. Recall@k measurement.
by Shandra
Tests AI agents, prompts, and agent skills against edge cases, unsafe behavior, output failures, permission risks, escalation gaps, memory leaks, and marketplace-quality weaknesses.
by Timoranjes
Teaches AI coding agents to self-detect context rot (regression loops, instruction drift, hallucination drift, lost-in-the-middle) during long sessions and execute a structured checkpoint/recovery pro
Convert instructional videos into machine-readable, schema-validated specs without hallucinations or invented parameters.
by Timoranjes
Teaches AI coding agents to perform structured, high-signal code reviews specifically for AI-generated code — catching the failure modes unique to LLM output (confident hallucinations, silent error sw