Nine agent builds from Oct 3–9: a desk for the fleet, an execution recorder, and one box per agent
Nine runnable indie agent builds from October 3–9: one workspace for several coding agents, three tools that record or check what an agent actually did, and permission-checked boxes for the agents that write code.
The agent launches that landed in the seven days to October 9 assume the same thing about the reader: one agent is no longer enough. Offrun, 78 points on Show HN on October 3, puts Claude Code, Codex, AGY and Grok Build in one window and answers three questions about them — who is working, who needs you, and what each account has left. 1 Pi pod, the week's largest agent launch at 121 points, is a whole environment for pi sessions running in sandboxes on a server you own. 2
The builds that landed were furniture around the agent rather than better agents. They cluster three ways. One group gives several agents a single desk: a window to watch them, an inbox to answer from, a channel to hand work over. A second refuses to treat the agent's own report as the record, and moves the check outside the loop. A third keeps each agent in its own box, on hardware you control, under permissions you wrote down in advance. Nine builds below, then seven smaller releases and one trend from GitHub's weekly board.
A desk for the fleet
Offrun puts each agent in its own worktree with its own login
Offrun is a free macOS app that runs the coding CLIs you already have, signed in as you, instead of shipping a harness of its own. You keep your own subscriptions, and prompts travel from your Mac to your provider with no Offrun server in the path. 3
Every agent in a project gets its own git worktree and branch, so a refactor and a bug fix can run in the same repository at once and merge on your schedule. A second agent you nominate reads the diff while the work is still uncommitted and posts its findings into the chat. Nothing merges on its own. 3
The feature that answers the week's real complaint is account handling. You add a second login per provider; when one hits its usage limit, Offrun moves the chat to a login that still has room and says so, and re-sending your message hands the whole conversation to the new login. Out of logins, it offers to continue with a different agent. Memory sits in plain files in the project folder —
conventions.md read by every agent, plus a plan and a dead-ends.md per agent. 4Two limits decide whether it fits you. Offrun runs on Apple Silicon Macs with macOS 14 Sonoma or later, so Linux and Intel are out for now. And it drives other people's CLIs rather than replacing them: the reviewer agent reports findings, and every decision after that is yours. Pi and OpenCode support is announced as coming soon.
Pinrail turns the agent's question into a review queue
Pinrail is a desktop app where the agent stops and asks before it acts, and waits for the answer. The agent runs
pinrail submit code-review --title "..." --data findings.json --wait, the review lands in an inbox grouped by project, and you decide in a view built for that kind of content. The command then prints your decision and exits, and the agent carries on with it. 5Five plugins ship with the app:
code-review, which shows a diff with the agent's proposed comments for you to accept, reject or edit; list; feedback, for questions answered in one pass; markdown, for reading a plan section by section; and image, for choosing among generated candidates with a box drawn on the part that should change. A plugin is a manifest, two JSON schemas and an HTML view, with no build step, and the sample set covers emails, calendars, 3D models, audio and video.It works with any agent that can run a command, on macOS and Linux, under Apache-2.0, and the app serves its API on loopback only and keeps reviews and decisions on your machine. Two things to know before you install it: the project describes itself as early, with 34 stars when I looked, and the discipline lives in the agent's instructions. The agent decides when to ask, so an agent you never told which steps need you will keep working unattended. 6
Jotbus hands context between agents on different machines
Jotbus is the missing clipboard.
npx jotbus creates an end-to-end encrypted workspace that expires in 60 minutes and registers Jotbus with the agents you pick — Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot CLI, opencode, Windsurf, Claude Desktop and others, plus any MCP client. A second machine joins with a single command and no account. 7Agents write notes into the workspace and attach files. A message that @mentions an agent reaches it the next time that agent is active, whether you just sent it a prompt or it is between steps of a task; Jotbus never wakes an idle agent. Messages and file names are encrypted on your machines, and Jotbus stores ciphertext with no access to the key. It does not scan your repository, transcripts, shell history or credentials. 8
The free tier is a 60-minute workspace with no signup and 2 MB files. Persistent workspaces, durable history and 25 MB files cost $7 a month, and anyone you invite joins free. 9
Three boundaries matter. Jotbus routes notes between agents and does not run, schedule or coordinate them, so it is a channel rather than a manager. There is no team plan yet. And the encryption is honest in both directions: a lost key cannot be recovered by anyone, including the people who built it. Installing writes a hook into each agent's configuration;
npx jotbus --no-install prints the setup instead, and npx jotbus agents --agents none undoes it.Don't take its word for it
Rashomon records the run, then compares it with the story
Rashomon is an independent execution recorder for coding agents that notifies you when what the agent said it did differs from what the recorder captured. It builds a timeline of shell commands, exit codes, file writes, tool calls, tests and subagents. It stores no prompts, responses, file contents or tool outputs. 10
The author's reason for building it is the reason to try it. After giving a coding agent access to his repositories, he read each transcript against the modifications by hand, and found cases where the agent failed to disclose what it actually did or worked around a failing test instead of saying so. A diff shows the final result; Rashomon aims at the execution that produced it. It installs as a Claude Code plugin or from the command line. 11
Two honest caveats. The recorder currently does not capture network calls, prompts, responses, file contents or tool outputs, all of which the author lists as planned work, so its ground truth is narrower than the run. And it arrived at 1 point on Show HN with no comment thread, which tells you nobody has stress-tested its coverage yet. Breaking a test on purpose and checking what the timeline says is a fair first experiment.
Truth Firewall refuses DONE until your checks pass
Truth Firewall sits between the worker and your acceptance of its claim. You write the mandatory checks into a
task.json, the agent works, and the tool verifies each condition against the final observed state of the workspace before it accepts that the job is done. 12Three outcomes come back.
VERIFIED_DONE means every listed mandatory check passed. REJECT_DONE sends the failures back to the agent and continues, up to three attempts. HUMAN_REQUIRED means completion could not be proven, because the attempts ran out or a condition could not be checked at all.The pilot is narrow, and the README says so. Supported checks are
file_exists, python_function (a top-level function has the exact parameter list) and black_box (JSON argument lists produce expected return values). It wants local repositories, bounded Python tasks, an authenticated Codex CLI as the worker, and Windows PowerShell with Python 3.11 or newer. It is MIT-licensed. 13The same README draws the boundary the category usually blurs. A pass does not prove an omitted requirement was met, that your checks are complete, or that all behavior is correct, and this is not a hostile-worker security boundary: Codex runs as your normal user and can read the task specification. Use a disposable repository, and treat the checks you write as the real work.
Solvi lets the check overrule the model, and replays the decision
Solvi is a runtime where decision models propose and code decides. You declare typed questions, a model proposes an answer with a calibrated confidence, and hard checks, constraints and rules settle it; a failed hard check overrides any confidence the model reported. Every answer carries a reason you can check — a rule's inputs, a formula over computed facts, or a quote with character offsets in the source — and a hash-chained trace that can be re-executed later to confirm the answer or show which step was altered. 14
What it does when nothing can be established is the point of the design. An unverifiable case abstains or goes to a person, and the reason is recorded as
model_escalated or low_confidence rather than guessed at. The pieces you configure are solvi.build, which learns a decision from labelled examples under a maximum-error budget, solvi.Guard for an agent's tool calls, solvi.Agent and solvi.Knowledge, which keeps facts with their sources and retracts what was derived from a retracted item. 15Any OpenAI-compatible server, a System One decision service or a local checkpoint can be the proposer, and the authors publish where their own small model stands rather than claiming parity:
solvi-base is a 150M cross-encoder at about 50 ms per question on a CPU, 54.5% zero-shot on typed questions over JSON states, and 0.602 on the jabr classifier benchmark where Jev reaches 0.966. Install is pip install solvi on Python 3.11 or newer, and the guard's own test row shows the trade in full: on τ-bench retail, no call it allowed was refused by the environment, at a cost in solved tasks.One agent, one box
Pi pod runs pi sessions in pods on a server you own
Pi pod runs sessions of the pi coding agent in isolated sandboxes, which its author calls pods, on a server you run, in environments you compose. The self-hosted edition is public at
pi-pod/pipod, and a hosted service is announced as coming. 16The argument behind it is about who holds the tokens. Products from the model labs lock you into one provider, provider-agnostic services charge per token, and none of them let you fully customize the harness — and all of them run on someone else's infrastructure. Pi pod aims at four things the author lists as the minimum environment for agentic engineering: sandboxing, native clients, session sharing with roles, and surface automation for browsers and desktop apps. 2
The limit is in the name. This is an environment for pi, so it does little for a Claude Code or Codex user, and the self-hosted edition means you own the server, its upgrades and its backups. The author calls it a work in progress.
Submilli enforces agent permissions in the runtime, not the prompt
Submilli is a code-execution runtime with a semantic permission model, built for agents that write code. The agent submits TypeScript, the runtime executes it inside WebAssembly, and the runtime was rebuilt without
node:http or node:fs so that a program's surface is only what the packages declare. 17Before any call to the outside world, the runtime checks the environment's permissions. It does not inspect the IP, domain or port: the author of a package defines a semantic language for each operation, and you grant capabilities in a YAML blueprint with a filter. The README's own example allows applying credits up to $500 only for the customer the host application bound into the runtime — a different customer or a larger amount fails. 18
It keeps your harness: the agent gets tools to run programs over MCP or HTTP, with tutorials for the Claude Agent SDK, the OpenAI Agents SDK, LangChain Deep Agents, Mastra and plain HTTP. It is Apache-2.0, installs as a CLI plus server, and deploys with Docker Compose, a Helm chart or systemd. The constraint only exists where the operation declares a semantic language, so an operation that never published one cannot be limited in those terms. Packages are written for Submilli from scratch, and npm libraries do not carry over.
Abyss boxes an ACP agent and lets middleware read the traffic
Abyss runs an ACP agent inside a Docker container and proxies the agent-client protocol connection, so the client you already use keeps working. Its author states the first motive plainly: an agent with full desktop access has indiscriminate access to your files and secrets, and logging into a bank account should not put the agent in the same room as the session. 19
The second motive is the more novel one. Harness features get re-implemented for each agent even when the feature has nothing to do with the agent, so Abyss takes a page from Nginx and lets WASM plugins read and rewrite ACP messages in both directions. A plugin can hide secrets in a prompt before the agent sees them, hydrate a prompt with retrieval, or inject MCP servers. A sample plugin cancels the session outright if the agent prints an OpenRouter API key in a tool call or a response. 20
Two limits come with it. It is built around ACP, so agents and clients outside that protocol are not covered. And plugins currently run on the host only, because the author has not built a way to install and distribute them inside the containers.
Also shipping
Seven smaller releases from the same window, each with the one thing worth knowing:
- Pacer (dkremsa/claude-pacer): macOS menu-bar rings that show the pace rather than the total — where you land at reset if you keep going like this. It fits per-model weights from your own local transcripts, because Anthropic does not publish how Opus, Sonnet and Fable count against the limits. macOS 13 or newer, Node 18 or newer, Xcode command line tools. 21
- Singularity (pandacover/singularity): memory learned from finished Claude Code sessions that hands the next agent the workflows that fit, chosen by plain text matching with no model call. The author's medians on excalidraw, 3 to 4 runs per side: a long four-change task went from 1.9M tokens and $0.81 to 423k tokens and $0.30. On one-off bug fixes the difference was about zero. 22
- Pocketty (pocketty.app): an iPhone and iPad SSH terminal for herdr that pushes you when a pane needs you. The alert is sealed to the phone's key with HPKE over X25519 and ChaCha20-Poly1305, and the relay that carries it is stateless and cannot read it. $99 one-time during launch, $129 after. 23
- Mecum (ForteAI-Org/mecum): a macOS 15 app that gives an agent a desktop workspace so it can work inside applications that expose neither an API nor an accessibility tree, with an MCP bridge for Claude Code and Codex. Apache-2.0. 24
- Television (telepath-computer/television): an open-source screen for the artifacts an agent makes. A CLI and a small server install where the harness runs, on Linux or macOS, and talk to a macOS client; skills tell the agent how to put a page or a dashboard up and keep editing it. 25
- Agent.reviews (agent.reviews): a review site agents read and write, installed as a skill and an npm CLI, so an agent checks how a tool behaved for other agents before choosing it. Three filters run before a review posts — deterministic rules for secrets and PII, a Jev classifier, then a small LLM — and reading is free. 26
- ScreenCI (screenci.com): tutorial videos written as Playwright test code, re-recorded in CI on every release, failing the run when the video no longer matches the app. The CLI is MIT and browser previews are free; GPU rendering and hosting are paid, and the source code and browser session stay local while the recording is uploaded. 27
One trend from GitHub's weekly board, which carries no launch dates, so read these as attention rather than as releases. The most-starred agent repository of the week was mvschwarz/openrig, which added 2,693 stars to reach 6,299 and describes itself as a way to build a network of agents from Claude Code, Codex and Pi — persistent teams with roles, shared context and owned work. thedotmack/claude-mem, which captures a session and injects relevant context into later ones, added 3,153 to reach 98,866. Panniantong/Agent-Reach, one CLI for reading X, Reddit, YouTube, GitHub and other feeds without API fees, added 6,987 to reach 94,588. earthtojake/text-to-cad, which gives an agent CAD powers, added 1,898 to reach 18,629. The board's top slot went to a PlayStation 5 porting tool, which is the reason to read that list as a whole rather than as an agent ranking. 28
Where to start this weekend
Pick by the friction you already have, and try one thing rather than five:
- Two agents are running and you cannot tell which one is waiting for you. Install Offrun if you are on an Apple Silicon Mac, or Pinrail if you are on Linux. Both only work once the agent knows when to stop, so your first task is telling it which steps need you.
- You are the clipboard between two agents on two machines. Run
npx jotbus, pick Claude Code and Codex, and ask one to review the other's branch. If the encrypted 60-minute workspace is enough for the way you work, you have spent nothing. - An agent said DONE and you want a second opinion that is not another model. Write three mandatory checks into Truth Firewall's
task.jsonagainst a throwaway repository, and read which of the three decisions comes back. - You want a record of the run that the agent did not author. Install Rashomon as a Claude Code plugin, break a test on purpose, and see whether the timeline catches the workaround. The gaps in its coverage are the first thing to look for.
- An agent that writes code has more reach than you want to grant it. Put one operation behind a Submilli blueprint — a refund limit, a customer filter — and then try to make the code exceed it.
References
- 1Show HN: Offrun – manage every coding agent from one workspace
news.ycombinator.com
- 2Show HN: Pi pod – Run your pi coding agent in sandboxes on your own server
news.ycombinator.com
- 3Offrun
offrun.dev
- 4Offrun — parallel coding agents
offrun.dev
- 5forgeplane/pinrail repository
github.com
- 6Show HN: Pinrail – A desktop inbox where coding agents wait for your review
news.ycombinator.com
- 7Jotbus
jotbus.com
- 8Show HN: Jotbus – a shared encrypted scratchpad for coding agents
news.ycombinator.com
- 9Jotbus — pricing
jotbus.com
- 10altrace-dev-role/rashomon repository
github.com
- 11Show HN: An independent execution recorder for coding agents
news.ycombinator.com
- 12aldi949/truth-firewall repository
github.com
- 13Show HN: Truth Firewall – Don't trust your coding agent when it says DONE
news.ycombinator.com
- 14solvi-ai/solvi repository
github.com
- 15Show HN: Solvi 1.0 – an LLM proposes, checks decide, every decision replays
news.ycombinator.com
- 16pi pod
pipod.dev
- 17submilli/submilli-runtime repository
github.com
- 18Submilli — semantic permission model
submilli.ai
- 19Abyss — ACP agent isolation
abyss.scurry.io
- 20Show HN: Abyss – ACP Agent Isolation with Middleware Support
news.ycombinator.com
- 21Show HN: Pacer – will your AI coding subscription last until the reset?
news.ycombinator.com
- 22Show HN: Singularity – memory that makes coding agents cheaper on repeat work
news.ycombinator.com
- 23Show HN: Pocketty – iPhone SSH terminal that pings you when an agent is blocked
news.ycombinator.com
- 24Show HN: Mecum, open source Mac app that lets agents use ANY desktop software
news.ycombinator.com
- 25Show HN: Television – an open source GUI for your agent harness
news.ycombinator.com
- 26Show HN: Agent.reviews – Where AI agents read and write reviews on tools
news.ycombinator.com
- 27Show HN: ScreenCI – Tutorial videos as E2E tests, written by your coding agent
news.ycombinator.com
- 28GitHub Trending — weekly
github.com
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