Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

ctx

Search the coding agent history already on your machine

Details

External ID
48763462
Source
HN
Company
—
Product
Kctx
Website domain
github.com
Launched
July 2, 2026
Cohort
—
Upvotes
65
Upvotes percentile
0.8739545997610514
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Coding agents don't have long-term memory.But you do have months of full-fidelity agent transcripts stored on your machine.A simple solution that goes a long way: ingest those transcripts and logs into a structured SQLite database, then search them with ranked text match. Everything is fully local and doesn't require anything fancy like a graph database or hosted memory service.This is the idea behind ctx, a Rust CLI that handles the ingestion and searching.We give our agents a skill that tells them to reference past sessions before working in an area. Usually we do this through an "Agent History Research Subagent" whose job is just to prepare a short brief covering any relevant history before the task begins.A real example: sometimes our test suite runs would fail because disk was full on the runner. The correct approach was to run the cleanup runbook, but the root cause of the failure was not clear to the agents, so they would think it was a test regression and go down the wrong rabbit hole debugging. When the agent searched history, it realized this failure had been encountered before and found the right workaround immediately. That got the agent onto the right cleanup path, and later we improved the log output so the same failure would be clearer next time. It's a boring story, but it's real agent productivity.Another nice use case is quickly generating session transcripts for sharing. You can exclude the noisy intermediate messages, so the transcript shows the important parts of the session more cleanly. Try attaching a session transcript to your next PR so your teammate and their agent can review the provenance and prompting behind the change.If you're up for an additional challenge, ask your agent to "exhaustively review all agent history in this repo and find where the SDLC is struggling or isn't agent-native". Using past sessions to recursively improve the agentic SDLC is a loop that we're using a lot today.If you try it out, please let us know what you think!

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Agent / copilot
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
search coding agent history locally
Manually corrected
False

Could you build this?

Yes Parsing local JSON/text agent logs into a local SQLite database with FTS5 for ranked full-text search is a quintessential weekend vibe-coding project.

Discussion

20 comments analyzed.

Competitors mentioned: Shelley (agent harness with sqlite storage), AgentKanban (human-in-loop VS Code integration), GPTZero (AI detection platform)

Concerns raised: AI-generated or AI-edited content quality and authenticity, Stale history leading to outdated context in agent actions, Token efficiency and cost of context retrieval, Ambiguity around what constitutes LLM usage (editing/polishing vs writing)

Feature requests: Native support for Shelley integration, Arbitrary SQL queries on stored context, Semantic search on structured corpus, Open source components

Competitors

Other products that read as similar to this one — 348 launches clear the similarity bar, closest 8 shown.

Attention rank: #38 of 349 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 240 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.