Alternatives
Products that do what CtxSift does
Save tokens and extend your coding sessions.
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Coding agents don't have long-term memory. But you do have months of full-fidelity agent transcripts stored on your machine. A simple solution that goes a long way: ingest those transcripts and logs into a structured SQLite database, then search them with ranked text match. Everything is fully local and doesn't require anything fancy like a graph database or hosted memory service. This is the idea behind ctx, a Rust CLI that handles the ingestion and searching. We give our agents a skill that tells them to reference past sessions before working in an area. Usually we do this through an…
Jul 2026 · github.com
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- 3CA
ctx is a local SQLite-backed skill for Claude Code and Codex that stores context as a persistent workstream that can be continued across agent sessions. Each workstream can contain multiple sessions, notes, decisions, todos, and resume packs. It essentially functions as a /resume that can work across coding agents. Here is a video of how it works: https://www.loom.com/share/5e558204885e4264a34d2cf6bd488117 I initially built ctx because I wanted to try a workstream that I started on Claude and continue it from Codex. Since then, I’ve added a few quality of life…
Apr 2026 · github.com
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- 7SC
Our team lives in Slack, but we don’t have access to the Slack MCP and couldn’t find anything out there that worked for us, so we coded our own agent-slack CLI * Can paste in Slack URLs * Token efficient * Zero-config (auto auth if you use Slack Desktop) Auto downloads files/snippets. Also can read Slack canvases as markdown! MIT License
Feb 2026 · github.com
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Local CLI coding agent with deep Devin Cloud integration
Apr 2026 · docs.devin.ai
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Hi HN! Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests / responses as much as possible. But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo/context? People usually accumulate skills, agents, MCP servers,…
Jun 2026 · github.com
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Snapshot, diff, replay and branch AI coding-agent sessions. Reads Claude Code / Codex logs natively. Redaction on by default. Pure stdlib. - mkmkkkkk/compactdiff
30d ago · github.com
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Your customized plugin to cut token waste, up to 50% savings
May 2026 · analyzer.spec-kitty.ai
- 14KL
LLM agents often place raw JSON tool outputs directly in the prompt. After a few tool calls, earlier results get compacted or truncated and answers become incorrect or inconsistent. I built Sift, a drop-in MCP gateway that stores tool outputs as local artifacts (filesystem blobs indexed in SQLite) and returns an `artifact_id` plus compact schema hints when responses are large or paginated. Instead of reasoning over full JSON in the prompt, the model runs a small Python query: def run(data, schema, params): return max(data, key=lambda x: x["magnitude"])["place"] Query code runs in a…
Mar 2026 · github.com
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Instant recall for coding agents. Search the history already on your machine. Git blame, but for agent sessions. - ctxrs/ctx
Jun 2026 · github.com
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Agents can run non-interactive commands, but they often fail once a workflow needs a real terminal (SSH sessions, installers, debuggers, REPLs, TUIs). I built term-cli so an agent can drive an interactive terminal session (keystrokes in, output out, wait for prompts). And it comes with agent skill for easy integration. It supports in-band file transfer: the agent can move files through the terminal stream itself (same channel as the interactive session), which is useful when the agent doesn’t have scp/sftp, shared volumes, or direct filesystem access across boundaries. Recent example:…
Mar 2026 · github.com
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I’ve been tinkering with what a “multi-agent IDE” should look like if your day-to-day workflow is mostly in terminal (Claude Code, OpenAI Codex, etc.). The more I played with it, the more it collapsed into three fundamentals: * A good TUI: Terminal is the center stage, with other stuff (CodeEdit, Diff, Review) baked on the side. I don’t like piping Agent’s output through some electron wrapper, here you get to run CC/Codex/Droid/Amp/etc directly. * Isolation: agents shouldn’t step on each other’s toes. The simplest primitive I’ve found is Git worktrees. It is not as…
Jan 2026 · agentastic.dev
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Hi HN, I'm building Librarian (https://uselibrarian.dev/), an open-source (MIT) context management tool that stops AI agents from burning tokens by blindly re-reading their entire conversation history on every turn. The Problem: If you're building agentic loops in frameworks like LangGraph or OpenClaw, you hit two walls fast: Financial Cost: Token usage scales quadratically over long conversations. Passing the whole history every time gets incredibly expensive. Context Rot: As the context window fills up, the LLM suffers from the "Lost in the Middle" effect. Response latency…
Feb 2026 · uselibrarian.dev
- 21DP
devnexus is an open-source cli that gives agents persistent shared memory across repos, sessions, and engineers. It maps out dependencies and relations at the function level, builds a code graph, and writes it into a shared Obsidian vault that every agent reads before writing code. Past decisions are also linked directly to the code they touched, so no one goes down the same dead end twice. Still building it out but I would love to hear any thoughts/feedback
Apr 2026 · github.com
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Autonomous multi-agent orchestration engine for software repos — L0/L1/L2 agents, leases, gates, audits, git-worktree isolation. Detached dispatch by default. GPL-3.0. - alex-reysa/singular-lite
Jun 2026 · github.com
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I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com
- 24CA
I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
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