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Selvedge

Remember the approaches your coding agent already rejected

Your coding agent can read the code and still miss why you rejected an earlier approach. Selvedge preserves that context: explicitly record decisions, rejected paths, reasons, and when to reconsider them; retrieve the history through MCP or a Python CLI before trying again. Records live in local SQLite. MIT-licensed, no account, and no LLM calls by Selvedge. Try the built-in demo in a temporary database, then connect it to your coding workflow.

Top comment

I'm Mason, the maintainer of Selvedge.

Bring one repeat bug.

If your coding agent keeps revisiting a bug or an approach you've already rejected, bring one example to the Selvedge pilot. I'll help you record the reason and check whether a fresh coding session can retrieve it. This is a small, free, voluntary trial—not a request for a testimonial or a promise to fix the bug. Failed lookups and confusing setup are useful feedback too.

Talk to me and join the pilot: https://github.com/masondelan/selvedge/discussions/49

Reply there with your coding agent and a short, non-identifying project label. The discussion is public; please keep private code and customer information out, and read the notes-sharing details before participating.

A fresh coding session can read your code and still miss why you rejected an earlier approach. That missing context can send an agent back down a path you already explored.

Selvedge makes those decisions retrievable. Developers and agents explicitly record what was tried, why it was rejected, and what would justify reconsidering it. Later sessions can look up that context through MCP or the CLI before choosing their next step.

A concrete example from the built-in demo: reject storing raw API keys because a database leak would expose usable credentials, record the hashed-key approach, and say when to revisit the decision. A later lookup retrieves the rejection and its reason.

The workflow is simple:

1. Record the decision, rejected approach, reason, and reconsideration conditions.

2. Query prior_attempts when similar work comes up.

3. Reconsider the old decision when its assumptions change.

Records live in local SQLite. Selvedge is MIT-licensed, requires no account or subscription, and makes no LLM calls itself. Recording is explicit: you or your agent decide what to preserve.

Try it:

uv tool install --upgrade selvedge

selvedge demo

The demo uses a temporary database without modifying your project. It records a rejection and retrieves it through a fresh database connection.

Quickstart: https://selvedge.sh/start/quickstart/

Source: https://github.com/masondelan/selvedge

What decision does your coding agent keep forgetting, and what context would have helped it?

About Selvedge on Product Hunt

“Remember the approaches your coding agent already rejected”

Selvedge was submitted on Product Hunt and earned 2 upvotes and 2 comments, placing #145 on the daily leaderboard. Your coding agent can read the code and still miss why you rejected an earlier approach. Selvedge preserves that context: explicitly record decisions, rejected paths, reasons, and when to reconsider them; retrieve the history through MCP or a Python CLI before trying again. Records live in local SQLite. MIT-licensed, no account, and no LLM calls by Selvedge. Try the built-in demo in a temporary database, then connect it to your coding workflow.

On the analytics side, Selvedge competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Selvedge performed against the three products that launched closest to it on the same day.

Who hunted Selvedge?

Selvedge was hunted by Mason D. 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.

Reviews

Selvedge has received 1 review on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.

For a complete overview of Selvedge including community comment highlights and product details, visit the product overview.