惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

C
CXSECURITY Database RSS Feed - CXSecurity.com
K
Kaspersky official blog
A
Arctic Wolf
Attack and Defense Labs
Attack and Defense Labs
L
LINUX DO - 热门话题
N
News | PayPal Newsroom
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
L
Lohrmann on Cybersecurity
PCI Perspectives
PCI Perspectives
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
The Last Watchdog
The Last Watchdog
B
Blog RSS Feed
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
W
WeLiveSecurity
Know Your Adversary
Know Your Adversary
博客园 - Franky
T
Tenable Blog
T
Tailwind CSS Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Help Net Security
Help Net Security
WordPress大学
WordPress大学
T
The Exploit Database - CXSecurity.com
www.infosecurity-magazine.com
www.infosecurity-magazine.com
博客园 - 司徒正美
阮一峰的网络日志
阮一峰的网络日志
D
Darknet – Hacking Tools, Hacker News & Cyber Security
H
Heimdal Security Blog
TaoSecurity Blog
TaoSecurity Blog
S
Security Affairs
J
Java Code Geeks
小众软件
小众软件
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Apple Machine Learning Research
Apple Machine Learning Research
NISL@THU
NISL@THU
O
OpenAI News
The Cloudflare Blog
月光博客
月光博客
Google Online Security Blog
Google Online Security Blog
V
V2EX
罗磊的独立博客
美团技术团队
博客园 - 三生石上(FineUI控件)
Security Latest
Security Latest
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
C
Cyber Attacks, Cyber Crime and Cyber Security
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Cyberwarzone
Cyberwarzone
L
LINUX DO - 最新话题
Hacker News - Newest:
Hacker News - Newest: "LLM"
大猫的无限游戏
大猫的无限游戏

Hacker News: Show HN

PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. Show HN: Tracking Top US Science Olympiad Alumni over Last 25 Years GitHub - Potarix/agent-hub: One place to talk to all your agents Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration) GitHub - dubeyKartikay/lazyspotify: Terminal Spotify client for macOS and Linux GitHub - the-banana-tool/king-louie: Easy to use GUI Personal AI Assistant. Win/Linux/Mac. Show HN I made my vacation rental bookable by AI agents–no Airbnb, 0% commission GitHub - basteez/jsf-autoreload: maven plugin to enable hot reload on jsf projects uvm32/hosts/host-gdbstub at main · ringtailsoftware/uvm32 GitHub - labsai/EDDI: Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus. GitHub - glitchnsec/fortyone-oss: AI Executive Assistant Platform Quickstart | Alien GitHub - muxshed/shed: One stream in, or many. Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店 GitHub - EdoardoBambini/Agent-Armor-Iaga: AI agents are getting tool access — shell, file system, databases, APIs, secrets. But **nobody is governing what they actually do with it**. Frameworks like LangChain, CrewAI, AutoGen, and Claude Code give agents the power to execute. Agent Armor gives you the power to control, audit, and approve every single action before it happens. HN Vibes — Week 15, Apr 7–13 2026 GitHub - chojs23/ec: Easy terminal-native 3-way git mergetool vim-like workflow GitHub - SethPyle376/hiraeth: Local AWS emulator focused on fast integration testing, with SQS support, SQLite-backed state, and a debug-friendly web UI. GitHub - JakOb-dotcom/cloud-sandbox-security-analysis: Technical analysis and Proof of Concept (PoC) regarding environment variable exfiltration in containerized cloud sandboxes via side-channel data leaks. Springboards - Flint Alpha Show HN: A simpler coding agent harness GitHub - audiodude/sudomake-friends GitHub - 256thFission/mini-mythos: OSS clone of Anthropic’s Mythos harness to locate C/C++ memory vulnerabilities Show HN: OpenParallax: OS-level privilege separation for AI agent execution Hacker News Sorted - Chrome 应用商店 Show HN: How to Install Docker on Ubuntu 24.04 LTS: Complete 2026 Guide GitHub - himanshudongre/smriti GitHub - sverrirsig/claude-control: macOS desktop dashboard for monitoring and managing multiple Claude Code sessions GitHub - ory/dockertest: Write better integration tests! Dockertest helps you boot up ephermal docker images for your Go tests with minimal work. Chiral - Chrome 应用商店 Show HN: Two Claudes collaborating through shared memory on a $100 mini-PC GitHub - pmichaillat/latex-cv: Minimalist LaTeX template for academic CVs GitHub - oguzbilgic/posse: A web UI for Anthropic Managed Agents. GitHub - sshiraz/depsly: Dependency risk analysis tool for npm packages ABI Add safari/agent-harness — Safari browser automation via safari-mcp by achiya-automation · Pull Request #212 · HKUDS/CLI-Anything GitHub - Halfblood-Prince/trustcheck: Verify PyPI package attestations and improve Python supply-chain security GitHub - oguzbilgic/kern-ai: Agents that do the work and show it. GitHub - bruits/satteri: High-performance Markdown and MDX processing for the JavaScript ecosystem GitHub - tylergibbs1/feedstock: High-performance web crawler and scraper for TypeScript, powered by Bun and Playwright GitHub - Grimm67123/grimmbot: The self-improving sandboxed and open-source AI agent. With persistent memory and scheduling. GitHub - whitevanillaskies/whitebloom: Local whiteboard that blooms. GitHub - hwdsl2/docker-whisper: Docker image for a self-hosted Whisper speech-to-text server with speaker diarization and OpenAI-compatible transcription and translation APIs. Powered by faster-whisper. Supports all Whisper models, NVIDIA GPU (CUDA) acceleration, JSON/SRT/VTT output, SSE streaming, offline mode, and multi-arch (amd64, arm64). GitHub - yisding/reviewwiggum GitHub - MarwanAlsoltany/serrors: Structured errors for Go: sentinel hierarchies, typed data, custom formatting, and slog integration. GitHub - soatok/age-php GitHub - Luthiraa/markitme GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits GitHub - tombedor/excalicharts GitHub - wh1le/excalidraw-edit: Open and edit .excalidraw files from the terminal. Offline, auto-saves to disk. MalExt Sentry - Malicious Extension Scanner - Chrome 应用商店 GitHub - syi0808/asciianimesvg: Generate animated ASCII art SVGs from text. CLI, Rust library, WASM, and web editor. GitHub - zaina-ml/ml_forge: A visual-based graph node editor for training computer vision models. GitHub - anakin87/llm-rl-environments-lil-course: 🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models GitHub - takaakit/superpowers-uml: Superpowers-UML modifies Superpowers to ensure a software development workflow in which AI agents design through UML modeling. AdriByte Studio - Sviluppo Web e Soluzioni Digitali GitHub - chouligi/angel-copilot: Your personalized Angel Investment Advisor Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 GitHub - agenteractai/lodmem: Level Of Detail Context Management for Agents GitHub - ostefani/subnetlens: A fast, concurrent network scanner with a TUI and plain-text CLI, built in Go. It discovers live hosts on your network, scans their open ports, resolves hostnames, and fingerprints operating systems—delivered. Cyber Pulse: Agentic Intel - Apps on Google Play Whisper API: Self-Hostable Speech to Text Transcription The Agent-Web Protocol Stack: A Research Thesis GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Show HN: Provepy – A Python decorator that proves your code using Lean and LLMs Show HN: Pardonned.com – A searchable database of US Pardons GitHub - patrickdappollonio/dux: Dux is a terminal UI that lets you run multiple AI coding agents side by side, each in its own git worktree, with full companion terminals, macros, commit generation, and a command palette that knows more tricks than you do. kMC Crystal Simulator Show HN: HyperFlow – A self-improving agent framework built on LangGraph GitHub - stef41/vibescore: 🎵 Grade your vibe-coded project. One command, instant letter grade across security, quality, dependencies, and testing. GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. imgur.com GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. GitHub - nowork-studio/toprank: Open-source Claude Code skills for SEO, SEM, Google Ads GitHub - tacomanator/sash: Lightweight macOS menu bar app for reliably cycling through windows of the current application. Appents | Social Media Management for Product-First Teams GitHub - pnhoang/youtube-spam-blocker: Automatically detects and hides spam messages in YouTube Live chat. Set rate limits, keyword filters, and block repeat offenders. GitHub - decisionnode/DecisionNode: CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable. GitHub - AvaCodeSolutions/django-email-learning: An open source Django app for creating email-based learning platforms with IMAP integration and React frontend components. The $100K Gap in Kubernetes Security Tooling Function Calling Harness: From 6.75% to 100%
GitHub - ctxvault/ctxvault: Local source of truth for carrying AI work across sessions and tools.
LuxBennu · 2026-05-07 · via Hacker News: Show HN

Know what your AI tools see.

CtxVault is the local trust layer for AI work. It turns local project sources into safe, receipt-backed handoffs for AI tools, agents, coding workflows, and future API surfaces. It preserves the decisions, constraints, and working state that should survive across agents, editors, command-line sessions, and other AI work surfaces.

v0.4.0 packages the deterministic context handoff path as a complete local trust-and-handoff release. The public core still centers on local source extraction, context selection, receipt inspection, and projection before context reaches AI tools:

local sources -> context-extract -> context slices -> privacy and quality receipts -> gated projection -> receipt inspection

The baseline is intentionally constrained: no model call, no embedding service, no vector database, no remote provider. The value is that the operator can see which sources were imported, which local context was selected, why it was allowed or blocked, how large it is, and which receipt links it to an AI work surface.

The roadmap treats this as AI work quality infrastructure: specs define what "done" means, context receipts explain what was selected or blocked, and trace or runtime receipts can later inspect how AI work happened. v0.4.0 adds a static Receipt/Trust Gallery and clearer demo/review materials while keeping optional Workbench UX and native wrapper source outside the open-core package.

This public repository exposes the deterministic trust floor behind that source-to-context-to-projection loop:

  • local file-backed objects and rebuildable indexes
  • CLI and MCP entry points over the same deterministic core
  • review-gated promotion and projection receipts
  • experimental compiled workstream state with source refs
  • deterministic context slicing and local context search
  • source-grouped context selection with token budget previews
  • one-command local extraction from static source exports and Markdown vaults
  • stable source fingerprints and idempotency keys for extraction runs
  • deterministic context-quality, density, retrieval-gain, source-retention, search-trace, and source-conflict receipts
  • selected-slice privacy preflight before projection
  • projection receipts linked to context-selection receipts
  • human-readable receipt inspection for extract, selection, privacy, quality, and projection chains
  • owner-operated public review pack with reusable public-source scenarios, boundary checks, and a synthetic blocked-selection check
  • read-only doctor diagnostics and projection healthchecks
  • Markdown-vault import as source material
  • review-gated logical purge for derived slice, search, preview, and selected projection data
  • public schemas, fixtures, and deterministic tests

Official Project

This repository is the maintainer-controlled public core for ctxvault.

Official releases, schemas, fixtures, and compatibility checks are published only through maintainer-controlled CtxVault channels. Forks and integrations are welcome under the Apache-2.0 core license, but unofficial builds should use distinct names and should not imply maintainer endorsement.

This repository contains the public deterministic core. Optional product surfaces and maintainer release operations remain outside this repo.

What To Inspect First

If you are evaluating the project, start with:

  • the Quick Start below for a clean deterministic run;
  • spaces/huggingface/v032-deterministic-demo/ for the toy-source demo;
  • scripts/run_v032_deterministic_demo.py for the offline demo loop;
  • scripts/inspect_v032_demo_receipts.py for receipt-chain inspection;
  • scripts/run_v032_selection_scorecard.py for lightweight selection quality and safety checks;
  • scripts/run_v033_public_review_pack.py for owner-operated public package review before publication;
  • scripts/run_v034_context_extract_stability.py for one-click extraction stability checks;
  • scripts/run_v034_context_quality_scorecards.py for deterministic context quality checks.
  • release/v0.4.0/receipt-trust-gallery/ for static selected, omitted, blocked, privacy, projection, and proof receipt examples;
  • release/v0.4.0/receipt-trust-gallery/index.html for the static Receipt/Trust Gallery page;
  • release/v0.4.0/trials/controlled-trial-record.template.md for non-author controlled trial records;
  • docs/v0.4.0-release-notes.md for the complete local trust-and-handoff release scope.

Scope

The public core is for developers who want to inspect or build on:

  • reviewed context organization around workstreams
  • context projection into practical AI working surfaces
  • local context storage and rebuildable indexes
  • deterministic review-gated promotion flows
  • local privacy and policy gates
  • artifact and receipt surfaces
  • early source-of-truth and evidence semantics for future AI work quality contracts
  • compiled current workstream state with source refs
  • local context slice rebuild, search, and selected-slice preflight
  • explicit logical purge of derived data without a secure-wipe claim
  • Markdown-vault import as source material
  • read-only projection adapter healthchecks
  • optional local snapshot/replica backup writes
  • deterministic context extraction from static local exports
  • receipt inspection for human review before sharing context

The public core currently marks these contracts as experimental:

  • src/ctxvault/intelligence.py
  • Episode
  • Workstream
  • compiled workstream state read model
  • doctor report
  • plugin manifest and projection receipt contracts
  • the first local plugin executor paths for reviewed context projection targets
  • projection adapter healthchecks
  • runtime event receipts
  • context selection receipts
  • context extraction receipts
  • context quality and scorecard receipts

Experimental means useful and inspectable, but not yet frozen as long-term public semantics.

v0.3.5 First-Run UX Boundary

v0.3.5 records the private Workbench UX patch over v0.3.4. The Workbench can make first-run extract and inject easier for the maintainer-operated product surface, but the public open-core package does not ship that UI and does not claim runtime control.

The public boundary for this release is:

  • CtxVault prepares receipt-backed handoff context
  • agent runtimes such as Codex or Claude Code remain user-controlled
  • no running session is attached, controlled, inspected, or impersonated
  • demo data is explicit fixture seeding, not automatic private-data import
  • Git worktree creation, SSE progress, and runtime inventory remain roadmap items, not shipped public behavior

v0.3.4 Context Extract And Quality Receipts

v0.3.4 is a release-experience cut over the safe handoff path. It does not add model, embedding, vector, remote provider, official plugin, live connector, or public Workbench dependencies. It makes the first useful trial shorter:

  • run context-extract --dry-run to fingerprint sources and preview imports without writing governed objects
  • run context-extract to import static local sources, rebuild slices, prepare context, and optionally project when the handoff is ready
  • inspect the newest receipt chain with receipt-inspect --latest --summary
  • verify stale source fingerprints, missing selection receipts, projection links, and blocked extraction runs with read-only doctor
  • run deterministic quality and stability scorecards before making public quality claims
  • keep projection gated by handoff_ready, privacy preflight, and token-budget checks

v0.3.3 Safe Context Handoff

v0.3.3 is a hardening release over the v0.3.2 composer. It does not add model, embedding, vector, remote provider, official plugin, live connector, or public Workbench dependencies. It makes the public path easier to verify:

  • run the public review pack from reusable public-source scenario fixtures
  • prepare exact local slices with context-prepare
  • inspect selection_status, handoff_ready, budget state, warnings, blocked reasons, and receipt paths
  • project approved selected slices with context-project
  • verify the projection receipt and linked context-selection receipt
  • confirm the synthetic secret fixture is withheld and blocks projection when explicitly selected

v0.3.2 Context Selection Composer

v0.3.2 is a fast-follow release after v0.3.1. It does not add model, embedding, vector, remote provider, official plugin, or live connector dependencies. It adds the deterministic step that should happen before context is projected into an AI work surface: choose exact local slices, inspect the budget, run privacy preflight, and keep the receipt chain.

  • source-grouped local context candidate composition
  • explicit multi-slice selection
  • token budget preview
  • target-aware privacy preflight for selected slices
  • ctxvault.context-selection-receipt/v1
  • projection receipts linked to context selection receipts
  • local pin, hide, and archive preferences for slice suggestions
  • CLI and MCP tools over the same deterministic core

v0.3.1 Local Safety And Context Slicing

v0.3.1 keeps the v0.3 source-to-context-to-projection path and adds the local safety substrate needed for safer context selection:

  • import project docs, sessions, and Markdown notes
  • organize them around reviewed Workstream state
  • compile current truth, open questions, decisions, warnings, and source refs
  • rebuild deterministic local context slices from governed sources
  • search slices locally without model, embedding, remote service, or hosted API
  • run privacy preflight before selected slices are projected
  • project that state into AGENTS.md, CLAUDE.md, and a workstream brief
  • inspect projection receipts, privacy preflight receipts, logical purge receipts, tombstones, and read-only diagnostics

This is the same source-to-context-to-projection loop from M1, now made denser with compiled current state and explicit health visibility.

CtxVault remains a local context layer for AI work, not a single-harness memory plugin. ChatGPT, Claude.ai, DeepSeek, local Ollama-style UIs, Claude Code, Codex, Cursor, shell traces, project notes, and rules files can all be source or target surfaces over time. Current named-source support is explicit: normalized transcript import where stable, and experimental adapters only where marked as such.

Quick Start

Run deterministic checks:

python3 scripts/run_deterministic_checks.py

Run the v0.3.4 one-click context handoff trial:

export PYTHONPATH=src
export CTXVAULT_TRIAL=/tmp/ctxvault-v034-trial

python3 -m ctxvault.cli init-vault --root "$CTXVAULT_TRIAL"
python3 -m ctxvault.cli seed-fixtures --root "$CTXVAULT_TRIAL"

python3 -m ctxvault.cli context-extract   --root "$CTXVAULT_TRIAL"   --source-path fixtures/v0.3.4-context-extract/markdown-vault   --source-kind markdown-vault   --recursive   --prepare-query "stable one click extraction privacy projection receipts"   --workstream-ref workstream://ws_20260421_ctxvault_schema   --workstream-id ws_20260421_ctxvault_schema   --project-target workstream-brief

python3 -m ctxvault.cli receipt-inspect --root "$CTXVAULT_TRIAL" --latest --summary
python3 -m ctxvault.cli doctor --root "$CTXVAULT_TRIAL"

Run the v0.3.4 deterministic quality and stability scorecards:

python3 scripts/run_v034_context_extract_stability.py --root /tmp/ctxvault-v034-stability
python3 scripts/run_v034_context_quality_scorecards.py --root /tmp/ctxvault-v034-quality

Run the v0.3.3 public package review pack:

python3 scripts/run_v033_public_review_pack.py --root /tmp/ctxvault-v033-public-review --force

Start with the generated human report:

/tmp/ctxvault-v033-public-review/artifacts/v0.3.3-public-review/owner-review.md
/tmp/ctxvault-v033-public-review/artifacts/v0.3.3-public-review/owner-review.html

Run the clean-user core validation flow:

bash scripts/run_clean_user_core_validation.sh /tmp/ctxvault-clean-verify

Run the v0.3.2 deterministic demo:

python3 scripts/run_v032_deterministic_demo.py --root /tmp/ctxvault-v032-demo
python3 scripts/inspect_v032_demo_receipts.py --root /tmp/ctxvault-v032-demo
python3 scripts/run_v032_selection_scorecard.py --root /tmp/ctxvault-v032-scorecard

Emit reviewed context projections:

PYTHONPATH=src python3 -m ctxvault.cli emit-agents-projection --root /tmp/ctxvault-clean-verify --workstream-id ws_20260421_ctxvault_schema --output-path exports/AGENTS.md --receipt-output-path artifacts/agents-md-receipt.json
PYTHONPATH=src python3 -m ctxvault.cli emit-claude-projection --root /tmp/ctxvault-clean-verify --workstream-id ws_20260421_ctxvault_schema --output-path exports/CLAUDE.md --receipt-output-path artifacts/claude-md-receipt.json
PYTHONPATH=src python3 -m ctxvault.cli emit-wiki-projection --root /tmp/ctxvault-clean-verify --workstream-id ws_20260421_ctxvault_schema --output-path exports/workstream.md --receipt-output-path artifacts/workstream-md-receipt.json

Build compiled workstream state:

PYTHONPATH=src python3 -m ctxvault.cli compiled-workstream-state --root /tmp/ctxvault-clean-verify --workstream-id ws_20260421_ctxvault_schema

Import a Markdown vault as source material:

PYTHONPATH=src python3 -m ctxvault.cli markdown-vault-import --root /tmp/ctxvault-clean-verify --vault-path /path/to/notes --scope-kind project --scope-value ctxvault

Run read-only diagnostics:

PYTHONPATH=src python3 -m ctxvault.cli doctor --root /tmp/ctxvault-clean-verify

Rebuild and search deterministic local context slices:

PYTHONPATH=src python3 -m ctxvault.cli context-slice-rebuild --root /tmp/ctxvault-clean-verify
PYTHONPATH=src python3 -m ctxvault.cli context-search --root /tmp/ctxvault-clean-verify --query "projection receipts"

Run selected-slice privacy preflight before projecting a slice into a target:

PYTHONPATH=src python3 -m ctxvault.cli context-selection-preflight --root /tmp/ctxvault-clean-verify --slice-ref SLICE_REF --target-kind agents-md --write-receipt

Compose selected local slices with a budget preview and a selection receipt:

PYTHONPATH=src python3 -m ctxvault.cli context-selection-compose --root /tmp/ctxvault-clean-verify --query "projection receipts" --target-kind harness.agents-md --slice-ref SLICE_REF --token-budget 1200 --write-receipt

Prepare and project a safe context handoff:

PYTHONPATH=src python3 -m ctxvault.cli context-prepare --root /tmp/ctxvault-clean-verify --query "projection receipts" --target-kind harness.agents-md --token-budget 1200 --write-receipt
PYTHONPATH=src python3 -m ctxvault.cli context-project --root /tmp/ctxvault-clean-verify --target workstream-brief --workstream-id ws_20260421_ctxvault_schema --slice-ref SLICE_REF --output-path exports/workstream.md --receipt-output-path artifacts/workstream-md-receipt.json

Pin, hide, or archive local slice suggestions:

PYTHONPATH=src python3 -m ctxvault.cli context-slice-preference-set --root /tmp/ctxvault-clean-verify --slice-ref SLICE_REF --action pin --target-kind harness.agents-md

Plan a review-gated logical purge of derived data:

PYTHONPATH=src python3 -m ctxvault.cli logical-purge-plan --root /tmp/ctxvault-clean-verify --slice-ref SLICE_REF --include-projections

Run read-only projection adapter healthchecks:

PYTHONPATH=src python3 -m ctxvault.cli adapter-healthcheck --root /tmp/ctxvault-clean-verify --target-kind agents-md --target-path exports/AGENTS.md
PYTHONPATH=src python3 -m ctxvault.cli adapter-healthcheck --root /tmp/ctxvault-clean-verify --target-kind claude-md --target-path exports/CLAUDE.md
PYTHONPATH=src python3 -m ctxvault.cli adapter-healthcheck --root /tmp/ctxvault-clean-verify --target-kind workstream-brief --target-path exports/workstream.md

Write an optional local snapshot/replica backup to an explicit local target:

PYTHONPATH=src python3 -m ctxvault.cli local-backup-write --root /tmp/ctxvault-clean-verify --target file:///tmp/ctxvault-clean-verify-backup --label "local backup rehearsal" --device-id local-target

Inspect the default runtime layout:

PYTHONPATH=src python3 -m ctxvault.cli print-layout

Initialize a local vault:

PYTHONPATH=src python3 -m ctxvault.cli init-vault

Run the stdio MCP transport:

PYTHONPATH=src python3 -m ctxvault.cli serve-mcp

M1 Projection Evidence

Run the source-to-projection golden path:

python3 scripts/run_context_injection_m1_golden_path.py --root /tmp/ctxvault-m1-context-injection

The checked-in M1 fixture evidence is in:

  • fixtures/context-injection-m1/projections/AGENTS.md
  • fixtures/context-injection-m1/projections/CLAUDE.md
  • fixtures/context-injection-m1/projections/workstream-brief.md
  • fixtures/context-injection-m1/projections/agents-md-receipt.json
  • fixtures/context-injection-m1/projections/claude-md-receipt.json
  • fixtures/context-injection-m1/projections/workstream-brief-receipt.json
  • fixtures/m1-context-injection/README.md

v0.4.0 Evidence

The v0.4.0 local trust-and-handoff release, v0.3.5 first-run UX boundary, v0.3.4 context extraction path, v0.3.3 safe handoff path, v0.3.2 context-selection composer, v0.3.1 local safety, and compiled context projection evidence are described in:

  • docs/v0.3-compiled-context.md
  • docs/v0.4.0-release-notes.md
  • release/v0.4.0/receipt-trust-gallery/index.html
  • release/v0.4.0/receipt-trust-gallery/README.md
  • release/v0.4.0/receipt-trust-gallery/manifest.json
  • release/v0.4.0/trials/controlled-trial-record.template.md
  • docs/v0.3.5-release-notes.md
  • docs/v0.3.4-release-notes.md
  • docs/v0.3.3-release-notes.md
  • fixtures/v0.3.4-context-extract/README.md
  • fixtures/v0.3.3-public-review/README.md
  • docs/v0.3.2-release-notes.md
  • docs/v0.3.2-injection-composer/implementation-plan.md
  • docs/v0.3.2-injection-composer/experimental-schemas/ctxvault-context-selection-receipt-v1.schema.json
  • docs/v0.3.1-release-notes.md
  • docs/v0.3.1-local-safety/approved-boundary-decisions.md
  • docs/v0.3.1-local-safety/hardening-status.md
  • docs/v0.3-release-notes.md
  • docs/v0.2-m2-developer-framework.md
  • docs/v0.2-m2-compatibility-evidence.md
  • docs/v0.2-m2-release-notes.md

The local backup write path is optional local durability. It creates a governed snapshot, copies the snapshot manifest, restore bundle, and sync manifest into an explicit local target, and verifies the target as a replica before reporting success. It does not make a hosted service the source of truth and does not replace a separate offsite backup strategy.

Public Docs

  • docs/public-core-boundary.md
  • docs/public-release-checklist.md
  • docs/experimental-contract-evolution-policy.md
  • docs/workstream-plan-ledger-contract.md
  • docs/v0.3-compiled-context.md
  • docs/v0.4.0-release-notes.md
  • release/v0.4.0/receipt-trust-gallery/index.html
  • release/v0.4.0/receipt-trust-gallery/README.md
  • release/v0.4.0/receipt-trust-gallery/manifest.json
  • release/v0.4.0/trials/controlled-trial-record.template.md
  • docs/v0.3.5-release-notes.md
  • docs/v0.3.4-release-notes.md
  • docs/v0.3.3-release-notes.md
  • docs/v0.3.2-release-notes.md
  • docs/v0.3.2-injection-composer/implementation-plan.md
  • docs/v0.3.1-release-notes.md
  • docs/v0.3.1-local-safety/approved-boundary-decisions.md
  • docs/v0.3.1-local-safety/hardening-status.md
  • docs/v0.3-release-notes.md
  • docs/v0.2-m2-developer-framework.md
  • docs/v0.2-m2-compatibility-evidence.md
  • docs/v0.2-m2-release-notes.md
  • fixtures/v0.3.4-context-extract/README.md
  • fixtures/v0.3.3-public-review/README.md
  • fixtures/README.md
  • schemas/README.md
  • CHANGELOG.md
  • TRADEMARK.md

Feedback

The most useful feedback is concrete: what you ran, what confused you, and which receipt, slice, projection, or workflow step was hard to trust.

Feedback is separated by evidence level:

  • ordinary issues are for bugs, wording gaps, install friction, and general trust questions;

  • first 10 minutes trial reports capture the first activation path and the first blocker, but may be self-reported;

  • non-author controlled trial evidence uses release/v0.4.0/trials/controlled-trial-record.template.md and is the only feedback category that can support later public beta readiness claims.

  • v0.3 Compiled Context feedback: .github/ISSUE_TEMPLATE/workflow-pain-point.yml

  • v0.3.1 local safety, privacy, or purge feedback: .github/ISSUE_TEMPLATE/trust-or-privacy-concern.yml

  • v0.3.2 context-selection composer feedback: .github/ISSUE_TEMPLATE/workflow-pain-point.yml

  • v0.3.3 safe context handoff feedback: .github/ISSUE_TEMPLATE/workflow-pain-point.yml

  • v0.3.5 first-run UX boundary feedback: .github/ISSUE_TEMPLATE/workflow-pain-point.yml

  • v0.4.0 First-Run Feedback: .github/ISSUE_TEMPLATE/v0.4.0-first-run-feedback.yml

  • v0.4.0 First 10 Minutes Trial Report: .github/ISSUE_TEMPLATE/v0.4.0-first-10-minutes-trial.yml

  • v0.4.0 Non-Author Controlled Trial Record: release/v0.4.0/trials/controlled-trial-record.template.md

  • Mac App Alpha feedback: .github/ISSUE_TEMPLATE/mac-app-alpha-feedback.yml

  • v0.2/M2 Developer Framework Feedback: .github/ISSUE_TEMPLATE/v0.2-m2-feedback.yml

  • M1 Quick Feedback: .github/ISSUE_TEMPLATE/m1-quick-feedback.yml

  • workflow friction: .github/ISSUE_TEMPLATE/workflow-pain-point.yml

  • trust or privacy concerns: .github/ISSUE_TEMPLATE/trust-or-privacy-concern.yml

  • broader positioning or adapter discussion: GitHub Discussions

License

Apache-2.0. See LICENSE.

Trademark and official-project usage guidelines are in TRADEMARK.md.