Search Results for "evidence"
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Showing 198 open source projects for "evidence"
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CRM
An open-source, agentic-first CRM
...The agent operates on its own schedule and work queue, investigates contacts and companies, records supported facts, and schedules future checks. Rather than guessing personal details, it prices evidence and writes strong observations while sending weak evidence to a human for resolution. The interface manages contacts, companies, deals, tasks, pipeline views, and agent activity. Email threads, meetings, signature blocks, optional web research, and enrichment services can provide evidence. Durable sessions survive reloads and deployments, while a restricted sandbox prevents direct database access and network egress. ... -
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Harness-1
Ultra Recipe for Training Long-Horizon Search Agents
Harness-1 is a 20B search agent trained with reinforcement learning inside a stateful retrieval harness. It is designed for long-horizon search tasks where the model must search, inspect documents, curate evidence, verify claims, and decide when enough evidence has been gathered. The harness externalizes search state, including candidate documents, evidence links, verification records, and budget-aware context. This lets the policy focus on higher-level decisions instead of trying to keep every detail inside the model context. The repository includes inference utilities, training scripts, evaluation runners, dataset tools, and documentation for running the released checkpoint. ... -
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CyberPPT
A Codex Skill for generating high-density, editable PowerPoints
CyberPPT is a Codex Skill for converting documents, research, and business data into dense, editable, consulting-style PowerPoint presentations. It extracts facts, numbers, claims, recommendations, conflicts, and caveats from formats such as PDF, DOCX, TXT, and XLSX. The workflow builds an MBB-style evidence table before developing storylines and converging on an SCR narrative. Users select from eight fixed visual systems, after which the skill plans each slide’s hierarchy, grid, charts, palette, and information density. Image-generation blueprints guide reconstruction while native text, shapes, tables, charts, and vectors preserve core editability. ... -
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Gajae-Code
Gajae Code MVP
...It runs beside existing tools rather than hiding inside a specific agent runtime, so users can apply it to a chosen repository or isolated worktree. The workflow is built around clarifying requirements, planning before mutation, turning approved plans into goals, and tracking evidence until completion. It includes tmux-backed execution options for coordinating parallel workers when a task is large enough to benefit from them. Gajae-Code is useful for developers who want coding agents to behave less like single-prompt assistants and more like disciplined project collaborators. Its main value is giving AI coding work a clearer loop for interviews, plans, goals, execution checks, and evidence. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Better Harness
Help your coding agents get better at getting better
...Instead of reviewing only the final code change, it examines how an agent understood the task, executed work, validated results, delivered safely, and captured reusable lessons. It gathers project and session evidence while marking missing or unobserved behavior explicitly. Reports organize findings across five Agent Work Loop dimensions and connect each conclusion to visible supporting evidence. Supported gaps become prioritized recommendations with expected outcomes, repair boundaries, and acceptance checks. Repeated reports can be compared through a history view to observe workflow trends without claiming unsupported causation. ... -
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unlazy
Anti-laziness skill for AI agents. Core: the Depth Tree method
...It requires agents to define acceptance gates before claiming that work is finished. Each gate can specify a command, expected result, working directory, and recorded evidence. A bundled checker validates the ledger, runs approved checks, and can reverify previously completed work. The workflow emphasizes reviewing returned work and reporting only conclusions supported by verifiable evidence. It can be installed for Claude Code, Codex CLI, and other skill-compatible agents, with additional templates and orchestration guidance for more complex tasks. -
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The Fable Method
How Claude Fable 5 worked, distilled into skills
...It converts observed problem-solving habits into explicit steps that different language models can follow. The core process classifies the request, defines completion criteria, gathers primary evidence, chooses one recommendation, makes the smallest correct change, and verifies the result. Four included skills cover planning, execution, judging completed work, and generating domain-specific adapters. The repository preserves evaluation cases, raw judge outputs, failures, and results from hundreds of agent runs. Its rules include bounded retries, authorization gates, evidence requirements, and honest caveat reporting. ... -
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Quint Code
Structured reasoning framework for Claude Code, Gemini, and Cursor
Quint Code is a structured reasoning and decision-support framework aimed at making AI-assisted software engineering and decision workflows more rigorous and auditable. It implements the First Principles Framework (FPF) to guide users and AI tools through hypothesis generation, logical verification, evidence gathering, and documented decision making, reducing reliance on ad hoc or “vibe” coding. Instead of accepting the first plausible answer generated by an AI assistant, Quint Code encourages generating multiple competing hypotheses, verifying them, and validating them against real evidence stored in a structured “knowledge base” within your project. ... -
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Shannon
Fully autonomous AI hacker to find actual exploits in your web apps
...The project blends source-aware analysis with automated web interaction so it can validate issues like injection flaws, authentication bypasses, and other exploitable paths in a way that resembles an actual attacker’s workflow. Instead of requiring you to manually reproduce findings, Shannon is designed to produce actionable evidence that a weakness can be weaponized, which helps teams prioritize what truly matters. It positions itself as a pre-attacker safety net, aiming to break your web app before someone else does and thereby reduce the gap between “potentially vulnerable” and “confirmed exploitable.” -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
...The overall workflow aims to minimize hallucinations by grounding outputs in retrieved material and then applying structured reasoning over that evidence before generating a final report. -
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PaperSpine
Motivation-driven skill for learning from strong academic papers
...The project asks the agent to study target formats and strong examples before drafting or revising. It emphasizes the central motivation of a paper, helping writers connect claims, structure, evidence, citations, and revisions into a coherent argument. The suite includes specialized skills for research, citation, rewriting, LaTeX, auditing, translation, humanization, and updates. It is best suited for users who need format-aware, evidence-aware academic writing support rather than generic text generation. -
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reverse-skill
Reverse Engineering and Authorized Penetration Testing
...The package checks locally available tools and can bootstrap supporting scripts, MCP servers, and utilities when needed. Scope gates, case initialization, timelines, evidence chains, reports, and field journals encourage repeatable and auditable work. It supports clients such as Claude Code, Codex CLI, Cursor, and Cline across Windows, Linux, macOS, and Kali Linux. The repository also preserves reusable lessons so later investigations can avoid previously documented mistakes. -
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anti-slop
Opinionated Oxlint rules for rejecting low-evidence TypeScript
Anti-slop is an opinionated Oxlint rule set for rejecting low-evidence TypeScript and JavaScript patterns. It is designed to be copied into a repository and customized rather than consumed as a fixed npm dependency. Its rules target practices such as chained type assertions, unsafe dictionary types, broad object parameters, ad hoc runtime type checks, module mocking, and contracts that return unknown. -
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CampusShame
Crowdsource and document the reputational history of companies
...It compiles lists of companies that have had so-called “shameful” behaviors, such as rescinding offers, canceling intention letters, or terminating three-party agreements after acceptance, alongside a parallel list of companies without reported negative incidents. The project draws on publicly available anecdotes, snapshots, and forum posts from platforms such as NowCoder, Maimai, and Zhihu to provide evidence and context for each entry, preserving details that might otherwise be lost as threads get deleted or censored. It also includes commentary on recruitment pitfalls and encourages contributors to share their own experiences or corrections to keep the list up to date. -
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VulnClaw
Based on AI Agent + MCP toolchain + penetration Skill orchestration
...Its newer architecture uses a goal-driven solving engine instead of a fixed-round loop, helping the agent stop when the goal is reached, the search space is exhausted, or a safety budget is met. It also includes evidence checks designed to reduce hallucinated conclusions by requiring real tool output before accepting key findings. VulnClaw is intended for authorized testing, CTFs, security education, and controlled red-team environments. -
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Growth Lab
An end-to-end growth tool that understands the product
...It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work. Each growth model follows an observe-act-review loop and keeps persistent memory of evidence, actions, results, and recommended next steps. The project currently includes workflows for SEO page growth and Xiaohongshu content research, creation, compliance checks, and review. ... -
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Hiring Agent
AI agent to evaluate and score resumes
...The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access. -
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MemProcFS Analyzer
Automated Forensic Analysis of Windows Memory Dumps for DFIR
...The Analyzer layer adds higher-level parsing and extraction routines—for example, carving strings, locating injected modules, enumerating handles, or reconstructing network sockets—so investigators can go from raw memory to actionable evidence more quickly. It emphasizes automation and reproducibility: parsers can be chained, results exported, and reports templated to fit incident workflows. Because memory contains transient but critical traces of running malware or misuse, the project focuses on robust parsing in the face of corruption and mismatched OS versions. -
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AutoCVE
Agent-driven automated CVE discovery platform for source code auditing
...Users can choose enhanced scanning, intelligent auditing, or comprehensive auditing based on speed and depth requirements. The interface records agent trees, tool calls, phase progress, sessions, findings, and supporting evidence for review. Vulnerabilities are deduplicated and stored in a structured management system, while configurable skills extend individual agents. The platform uses a React frontend, FastAPI backend, PostgreSQL database, and Docker-based deployment. -
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Loop Library
A library of practical AI-agent loops and an installable skill
...The repository contains both a public loop library website and the Loopy skill that agents can use to discover, audit, adapt, run, and prepare loops. It helps turn open-ended prompts into measurable workflows with evidence, stopping criteria, and human approval points. The skill can work with agent environments such as Codex, Cursor, and Claude Code through the Skills CLI. Overall, it is useful for teams that want safer, reusable, and more reliable agent workflows instead of one-off prompting. -
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MetaScreener
AI-powered tool for efficient abstract and PDF screening
MetaScreener is an open-source AI-assisted tool designed to streamline the screening process in systematic literature reviews and academic research workflows. The system helps researchers analyze large collections of academic abstracts and research papers to determine which studies are relevant for inclusion in evidence synthesis projects. Instead of manually reviewing hundreds or thousands of documents, researchers can use MetaScreener to apply machine learning techniques that assist with classification and prioritization of candidate papers. The platform can analyze both abstracts and full PDF documents, enabling automated filtering based on research criteria defined by the user. ... -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. ... -
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MyContext
MyContext is a local-first desktop app for everyday communication
...It connects conversations, documents, meetings, activities, people, projects, topics, and other sources into an evolving private knowledge structure. A personal context graph lets users explore relationships between information while retaining links to supporting evidence. Natural-language search combines full-text retrieval, semantic matching, and graph queries to answer questions across work history. Its digital-self workflow can recall relevant background and draft context-aware responses while leaving consequential actions under explicit user approval. Data and indexes are stored locally in a SQLite-based vault and can be exposed selectively to models, local agents, and authorized AI applications. -
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ResultTypes.jl
A Result type for Julia—it's like Nullables for Exceptions
ResultTypes provides a Result type that can hold either a value or an error. This allows us to return a value or an error in a type-stable manner without throwing an exception.