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ucsandman
DashClaw
TypeScript2026–2026
ucsandman / DashClaw

DashClaw

Remote approvals, policy checks, and execution evidence for unattended AI agents.

2Distinct people
3Mentions
0Explicit recommenders
318GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Remote approvals, policy checks, and execution evidence for unattended AI agents.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week3 dated mentions

Observed mentions: 2026-03-13 13:08:09 UTC to 2026-09-07 13:37:54 UTC. Weeks start Monday, UTC.

012026-03-09 00:00:00 UTC to 2026-03-16 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsMar 92026-03-16 00:00:00 UTC to 2026-03-23 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-03-23 00:00:00 UTC to 2026-03-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-30 00:00:00 UTC to 2026-04-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-06 00:00:00 UTC to 2026-04-13 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-13 00:00:00 UTC to 2026-04-20 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-20 00:00:00 UTC to 2026-04-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-27 00:00:00 UTC to 2026-05-04 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-04 00:00:00 UTC to 2026-05-11 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-11 00:00:00 UTC to 2026-05-18 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-18 00:00:00 UTC to 2026-05-25 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-25 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-01 00:00:00 UTC to 2026-06-08 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-08 00:00:00 UTC to 2026-06-15 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJun 82026-06-15 00:00:00 UTC to 2026-06-22 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-22 00:00:00 UTC to 2026-06-29 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-29 00:00:00 UTC to 2026-07-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-06 00:00:00 UTC to 2026-07-13 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-13 00:00:00 UTC to 2026-07-20 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-20 00:00:00 UTC to 2026-07-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-27 00:00:00 UTC to 2026-08-03 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-03 00:00:00 UTC to 2026-08-10 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-10 00:00:00 UTC to 2026-08-17 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-17 00:00:00 UTC to 2026-08-24 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-24 00:00:00 UTC to 2026-08-31 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-31 00:00:00 UTC to 2026-09-07 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-09-07 00:00:00 UTC to 2026-09-14 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsSep 7

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Mar 92026-03-09 00:00:00 UTC2026-03-16 00:00:00 UTC110
Mar 162026-03-16 00:00:00 UTC2026-03-23 00:00:00 UTC110
Mar 232026-03-23 00:00:00 UTC2026-03-30 00:00:00 UTC000
Mar 302026-03-30 00:00:00 UTC2026-04-06 00:00:00 UTC000
Apr 62026-04-06 00:00:00 UTC2026-04-13 00:00:00 UTC000
Apr 132026-04-13 00:00:00 UTC2026-04-20 00:00:00 UTC000
Apr 202026-04-20 00:00:00 UTC2026-04-27 00:00:00 UTC000
Apr 272026-04-27 00:00:00 UTC2026-05-04 00:00:00 UTC000
May 42026-05-04 00:00:00 UTC2026-05-11 00:00:00 UTC000
May 112026-05-11 00:00:00 UTC2026-05-18 00:00:00 UTC000
May 182026-05-18 00:00:00 UTC2026-05-25 00:00:00 UTC000
May 252026-05-25 00:00:00 UTC2026-06-01 00:00:00 UTC000
Jun 12026-06-01 00:00:00 UTC2026-06-08 00:00:00 UTC000
Jun 82026-06-08 00:00:00 UTC2026-06-15 00:00:00 UTC000
Jun 152026-06-15 00:00:00 UTC2026-06-22 00:00:00 UTC000
Jun 222026-06-22 00:00:00 UTC2026-06-29 00:00:00 UTC000
Jun 292026-06-29 00:00:00 UTC2026-07-06 00:00:00 UTC000
Jul 62026-07-06 00:00:00 UTC2026-07-13 00:00:00 UTC000
Jul 132026-07-13 00:00:00 UTC2026-07-20 00:00:00 UTC000
Jul 202026-07-20 00:00:00 UTC2026-07-27 00:00:00 UTC000
Jul 272026-07-27 00:00:00 UTC2026-08-03 00:00:00 UTC000
Aug 32026-08-03 00:00:00 UTC2026-08-10 00:00:00 UTC000
Aug 102026-08-10 00:00:00 UTC2026-08-17 00:00:00 UTC000
Aug 172026-08-17 00:00:00 UTC2026-08-24 00:00:00 UTC000
Aug 242026-08-24 00:00:00 UTC2026-08-31 00:00:00 UTC000
Aug 312026-08-31 00:00:00 UTC2026-09-07 00:00:00 UTC000
Sep 72026-09-07 00:00:00 UTC2026-09-14 00:00:00 UTC110

What Hacker News says

3 sources
ucsandman·Mar 17, 2026Submission

Show HN: DashClaw – Intercept AI agent actions before they execute

I kept finding out what my agents did after the fact. Logs, traces, error reports. By then the action had already happened. I wanted a way to stop the action before it executes, present context to a human, and record the decision. That layer didn't exist, so I built it. DashClaw sits between your agents and their actions. Every action goes through a policy check before it runs. The agent waits until the decision comes back. What it does: - Guard policies defined in YAML. Conditions, thresholds, actions (allow / block / require_approval). Versioned, testable in CI via simulation endpoint. - Decision recording to Postgres before the action fires. Action, context, assumptions, policy applied, outcome. All org-scoped. - Human-in-the-loop over SSE with Redis broker. 10-min replay window so approvals survive disconnects. Agent holds pending unt
Read the rest
il decision or timeout. - CLI approval channel. `dashclaw approve <id>` from a second terminal. No browser needed. - Node and Python SDKs. Wraps existing calls. No framework lock-in. How the guard check works in practice: const decision = await claw.guard({ action_type: 'deploy', risk_score: 90 }); if (decision.decision === 'block') return; Claude Code integration via hooks. DashClaw intercepts tool calls via PreToolUse hooks before Claude Code executes them. High-risk tools get routed for terminal approval automatically. Works with LangChain, CrewAI, OpenAI tools, Anthropic tools, Autogen, or custom agents. - Quick Demo w/Docker: npx dashclaw-demo - End to End Demo: cd examples/openai-governed-agent && npm install && node index.js That runs a real agent, attempts a high-risk action, DashClaw intercepts it, and waits for your approval in the browser. Or you can run npm install -g @dashclaw/cli and approve it in the terminal via dashclaw approve <actionId> Stack: Next.js 15 (JS, no TS), Neon Postgres, Redis, NextAuth, Vercel. MIT licensed. Honest limitations: guard policies handle threshold and allowlist rules well. Contextual policies that reason over full conversation history are not there yet. Thinking about that as a separate eval layer rather than baking it into the guard runtime. Features in the Labs category are still in development, currently building out integrations and starting with Discord/Slack. GitHub: https://github.com/ucsandman/DashClaw Demo (fixture data, no login): https://dashclaw.io Happy to go deep on any part of the architecture.
1 points · Open discussion
ucsandman·Mar 13, 2026Submission

Show HN: DashClaw – intercept and audit AI agent decisions before they execute

Hi HN, I’ve been experimenting with autonomous agents for the past year, and I kept running into the same uncomfortable problem: Agents were making decisions I couldn’t fully see or justify. They could call tools, trigger actions, and make assumptions based on incomplete context. Once systems start touching real infrastructure, that becomes pretty scary. So I built DashClaw. DashClaw sits between an agent and the tools it wants to use. Instead of executing actions directly, agents call DashClaw first. DashClaw can: • evaluate the decision • apply policy rules • require approval • log reasoning and assumptions • record the final outcome The idea is to create a *decision trail* for agent systems so you can answer: Why did the agent think this was okay? What information did it rely on? Who approved the action? The project includes: • Nod
Read the rest
e and Python SDKs • a decision ledger for agent actions • policy guardrails before execution • a mission control dashboard for fleet activity • a self-hosted architecture It’s completely open source and designed to be lightweight enough to run locally with agent frameworks. I'm still figuring out what the right abstraction layer is for this kind of infrastructure, so I’d love feedback from people building agents. Repo: https://github.com/ucsandman/DashClaw
2 points · Open discussion

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