An auditable, reversible, evaluable local agent runtime that turns feedback into skills — and ships them only when evidence and tests say so.
Claude-first paid-media operations skill for Claude Code across 12 ad platforms (Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, X): source-grounded audits, deterministic findings and evidence coverage, versioned JSON reports, and capability-gated account changes.
PaperSpine5 — local-first, evidence-bound paper research, writing, figures, review and delivery. Download: https://wubing2023.github.io/PaperSpine/v5/
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
AI/ML research agents from idea to paper-ready evidence. An EvoMap open-source project.
A model-driven harness for AI coding agents: semantic modeling, app generation, progressive API Assist and evidence-based verification.
Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.
Agent skills and an AGENTS.md workflow template — isolate in worktrees, build to a service layer, prove with evidence, ship with before/after proof and Greptile review loops. For Claude Code, Cursor, and Codex.
Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.
Autonomous LLM Trading Asterism — a research-only multi-agent trading platform with evidence-first research, an auditable console, Shadow simulation and explicitly authorized broker execution.
An LLM-first SEO analysis skill for Antigravity, Codex, Claude with 16 specialized sub-skills, 10 specialist agents, and 88 optional utility scripts used as evidence collectors.
Local MCP work notes with persistent sessions, decisions, evidence and resumable tasks.
Verify that the PowerPoint you are about to deliver is exactly the PPTX that passed QA—locally, offline, and with tamper-evident evidence.
Local-first creator favorites workbench with evidence-preserving Markdown capture and a complete browser UI.
AI agent identity, signed credentials, delegated authority and portable governance evidence. Python core and offline verifier SDKs.
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
SEO foundation checks as an Agent Skill: give it a URL, get a crawler's-eye pass/fail report with evidence. 26 structural checks, zero LLM, deterministic.
AI data analyst for transparent, reproducible analysis. Works step by step in Python, verifies the evidence behind its reports, and supports a wide selection of models, including local open-weight models.
FactCircuit: an auditable claim-and-evidence verification loop with immutable provenance, staged checks, bounded retrieval, and reproducible evaluation.
NORDEF Matrix Open Control: model-independent AI safety belt with 0/1/2 decisions, Ed25519 root gate, replay protection, evidence chain, and incident-pattern eval bank
An old coder's strategy for the agent era: don't read the code — make it run the gauntlet. Evidence-first development skill for coding agents, inspired by Uncle Bob.
Evidence-grounded repository audit CLI - deterministic scanner, MCP server, live dashboard, and a GitHub Action that posts PR diffs.
Monte Carlo simulation of the NBA season, leveraging dbt, duckdb and evidence.dev
An inference chip design that runs a real LLM (Qwen2.5-0.5B) on FPGA — one transformer decoder layer in RTL, every silicon value bit-exact against a golden model. 0.56 tok/s measured, a 140× climb, full evidence trail.
A multi-agent AUTO Research loop for idea discovery, experiment execution, evidence-grounded paper writing, quality audit, and live Web observation from AI group, CNIC, CAS.
Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, audit trails. Works with LangChain, CrewAI, MCP.
Source-linked Claude 5.5 video workflows: Opus and Sonnet demos, separately labeled next-Fable testing reports, prompts, tools and production evidence.
Scientific hypothesis-discovery workbench: grounded hypothesis-evidence graphs, synthetic literature with planted causal chains, generate-debate-evolve loops over pluggable offline adapters, Elo tournaments recovering planted skill order, paraphrase dedup, Bayesian evidence accumulation, reproducible reports. NumPy core, CPU-only torch extra.
Local codebase intelligence CLI + MCP server for AI coding agents: SQLite code graph, 28 languages, 287 commands, 246 MCP tools, change-safety gates, audit evidence, zero API keys.
Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.
Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence and proves work with deterministic contracts, not model opinion. DeepWatch is the agent workspace built on DeepSeek Harness. Python + npm, MCP, CLI, REST, Web.
An evidence-led, eight-locale LLM playbook: a transferable core, the Codex flagship track, and adapters for ChatGPT, Claude Code, Gemini, DeepSeek, and Grok.
Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.
Evidence-first infrastructure for reproducible, isolated executable evaluation and online rewards.
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Track 33,707+ AI benchmark, eval, dataset, and data-quality records from 40 public sources, with linked evidence and daily updates.
Evidence-grounded cryptographic inventory and post-quantum migration planning for software repositories. Local static analysis, zero mandatory runtime dependencies, SARIF and CycloneDX output.
FOREST is a research agent for long-horizon science, where evidence gets lost, errors compound, and goals drift. It explores ideas, reads literature, forms hypotheses, runs real experiments, analyzes results, revises paths, and builds a full paper—all in an editable graph you can inspect, branch, redirect, with claims and figures linked to evidence
Open protocol for AI agent work contracts and verifiable execution — authorization, evidence, and acceptance for multi-agent systems
PaperGraph MCP turns math papers into evidence-grounded reading maps for AI agents: extract results, trace proof evidence, plan reading order, and review external dependencies without guessing.
Make Gemini code like Claude Models. Forces it to inspect files before editing, plan changes, test its work, and back up every “done” with actual evidence.
Established strong JEV based natural language to SQL performance and well-covered semantic operators for PostgreSQL(PG) with optimized cost and latency. Reusable evidence, with native execution, parallel plans and explainable embeddings in development preview.
An evidence-bound academic revision skill for social science research. It reduces defensive prose without weakening scholarly caution, foregrounds core contributions, compresses repetitive qualifications and process narration, and preserves claim ceilings, evidence status, scope, boundaries, and rival explanations for auditable, traceable revision.
Coordinate Claude, Codex and Cursor windows with shared tasks, acknowledgements, prechecks, parallel tests, source-bound proofs and independent review. Built-in skills recall lessons, simplify code and forecast work. Track progress, decisions and evidence in a bilingual local dashboard, with MCP plugins. Browse skills and verified security audits.
Local-first, auditable multi-agent control room for coding, review, evidence, and private remote work.
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.
Evaluator-neutral AI evaluation evidence, baseline regression gates, and JSON, JUnit, and SARIF reports for CI.
Evidence-first runtime for a wheeled mobile household robot with bounded actions, replayable events, and fail-closed verification.
Fail-closed cross-disciplinary research design, novelty, evidence, writing, and audit plugin for Codex-compatible agents.
Local-first, AI-centered, evidence-gated job application workflow
VeriRepro: Evidence-grounded reproduction for computational papers.
An evidence-preserving Chinese-to-English manuscript translation and review workflow for computing, medicine and other STEM disciplines.
Canonical, machine-checkable record of the Justin Sun Prize: rules, awards, candidates, and verification evidence.
Claim-Driven Development: turn software intent into verifiable evidence.
面向 Codex、Claude Code 等 AI Agent 的医学绘图 Skill,基于可信证据制作医学插画、科普漫画与科研示意图,提供可编辑成果与审核记录。 · Evidence-backed medical illustration, comics and research figures for Codex, Claude Code and other AI agents, with editable output and review records.
Contest-native, evidence-focused math modeling workflow for Codex and Claude Code
Model-agnostic Chinese and English academic editing for the latest models across Agent platforms. Reduce formulaic prose while preserving evidence and author voice.
A practical Codex skill for evidence-backed repository health audits
Research and writing can be automated. Authorship cannot. Evidence list + agent skills for spotting AI-produced papers no human stood behind.
🔎 Username, email & phone OSINT — 9,700+ lookup checks from 19 projects, with profile enrichment, bulk searches, evidence graphs and expert-reviewed updates.