u/No-Childhood-2502

I got tired of Claude Code silently hitting rate limits, so I decided to build something to address the issue.

Imagine you’re 40 minutes into a refactor. Claude is running tools and making progress, then suddenly, everything stops. The session has reached its rate limit without any warning—no alert saying you’re at 95%, just a complete halt. The usage bars are visible in the UI, but the model itself remains unaware of them.

I discovered that Anthropic has a usage API, and Claude Code already possesses hooks to make it work. This led me to create agent-baton, which reads the usage API and installs hooks to make Claude aware of its limits.

Here are the three hooks you can initiate with one command (baton init):

1. SessionStart: Fetches usage data and injects it so Claude knows from the first message how much has been used.
2. UserPromptSubmit: Performs a time-to-live (TTL) aware check that avoids overwhelming the API. It uses smart caching—checking every 15 minutes when usage is low and once a minute when it's nearing the limit.
3. PreToolUse: This is the crucial one; it checks usage mid-task to prevent the scenario where you “started at 93% and ran out of capacity mid-execution,” catching the problem within 1-2 tool calls.

When the warning threshold is reached, it prompts an interactive question using Claude Code's built-in AskUserQuestion tool:

"Claude 5-hour usage is at 91% — you're in the warning zone."

Options include:

• Continue this task
• Write a handoff document
• Switch to lightweight mode

It also handles full agent handoffs by writing a structured markdown handoff and passing work to Cursor, Codex, or Gemini.

You can install it with the following command:

npm install -g u/codeprakhar25/agent-baton && baton init

For more details, visit the GitHub repository.

Have been obsessed with the field of code security for weeks, and I started with how, if we trace the autonomous code by agents, capturing the prompt that drove it, the intent behind it, and the context the agent had.

I built agentdiff, it hooks into all major coding agents and works with the git hooks, no additional changes- configure & init!

I didn't expect this, but PR review agents got noticeably better once they had access to the traces. More context on what changed and why = fewer false positives, better suggestions.

Opensource here: https://github.com/codeprakhar25/agentdiff

Have been obsessed with the field of code security for weeks, and I started with how, if we trace the autonomous code by agents, capturing the prompt that drove it, the intent behind it, and the context the agent had.

I built agentdiff, it hooks into all major coding agents and works with the git hooks, no additional changes- configure & init!

I didn't expect this, but PR review agents got noticeably better once they had access to the traces. More context on what changed and why = fewer false positives, better suggestions.

Opensource here: https://github.com/codeprakhar25/agentdiff

I released agentdiff today, line-level attribution for AI-generated code, all things code security. Have been working on it for weeks!

When Claude Code or Cursor commits to your repo, git blame tells you the agent's name. It doesn't get you what prompt drove it, what files it had in context, or what it never saw. AgentDiff works on the same, it hooks into your coding agent and captures all of that as a tamper-proof trace — per line, per session, pushed with your code.

I didn't expect this but: PR review agents got noticeably better once they had access to the traces. More context on what changed and why = fewer false positives, better suggestions (More on the PR on agentdiff).

Opensource. Would appreciate some feedback/discussions, and contributions!
https://github.com/codeprakhar25/agentdiff

I have been working with code security for some weeks, and thought of whether tracing each line of the codebase could be helpful for the agent, with capturing the prompt that drove it, and the intent behind it!

Tested on the PR attached, and awesome to see the report and how the greptile agent worked.