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Argus
See what Claude Code actually did, and what it cost
See what Claude Code actually did. Argus tails the transcripts Claude Code already writes into a local SQLite archive and serves a dashboard on localhost: which tools ran, what each sub-agent was told, which turn blew the budget. Per-turn cost and tokens, alerts when a tool starts failing, full-text search over every prompt and reply. Sessions stay after Claude Code rotates its logs. Nothing leaves your machine. The only network call is an optional price refresh. pip install argus-code
Hi Product Hunt, I'm Krish. I built Argus because there was no local observability tool for the coding agents we actually use all day.
We have good tracing for LLM API calls. Claude Code, the tool most of us spend the most hours in, is a black box. It writes a full transcript of every session to ~/.claude, every turn, tool call and sub-agent, and then tells you almost nothing about it. When a session goes sideways you can't see which tool call did it, what a sub-agent was told, or what happened inside a workflow.
Argus reads those transcripts into a SQLite archive on your machine and serves a dashboard on localhost:
- Every session turn by turn, with the tool calls inside each turn and their errors.
- Every sub-agent, including ones inside workflows: the exact task it was given, its tools, its own timeline.
- Tool error rates, with a detector that flags a tool the day it starts failing.
- Tokens and estimated cost per turn. Tokens exact, costs estimated.
- Opt-in full-text search across prompts, replies, thinking and tool output.
- A permanent archive. Claude Code rotates its logs; Argus keeps what it has ingested.
Nothing is uploaded. It binds to 127.0.0.1, has no telemetry, and the only network call is an optional price refresh.
pip install argus-code
argus start
MIT, code on GitHub. Claude Code first; ingest is adapter-based so other agents can follow.
What can't you see about your agents today that you wish you could? That's the question shaping the next version.
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About Argus on Product Hunt
“See what Claude Code actually did, and what it cost”
Argus was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #156 on the daily leaderboard. See what Claude Code actually did. Argus tails the transcripts Claude Code already writes into a local SQLite archive and serves a dashboard on localhost: which tools ran, what each sub-agent was told, which turn blew the budget. Per-turn cost and tokens, alerts when a tool starts failing, full-text search over every prompt and reply. Sessions stay after Claude Code rotates its logs. Nothing leaves your machine. The only network call is an optional price refresh. pip install argus-code
Argus was featured in Open Source (68.8k followers), Developer Tools (519k followers), Artificial Intelligence (478.1k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 246.4k products, making this a competitive space to launch in.
Who hunted Argus?
Argus was hunted by Krish Bhimani. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Argus stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Krish Bhimani