Show HN: Keen Code – an agentic-engineered coding agent
4 by mochow13 | 1 comments on Hacker News.
Hello community! I am here to share a coding agent I have built solo from scratch using agentic engineering. Written in Go, it's a proper coding agent, has features you expect from a useful agent for your daily work, with a minimal and simple UI. I have named it Keen Code. The repo is here: https://ift.tt/SYeDs6y Even though it started as an experiment, it is now a full-fledged coding agent for real software engineering work. It supports multiple providers, skills, MCPs, multi-agent orchestration through subagents, automatic compaction, etc. I have been using it for real production-grade work myself, and also for developing itself. Notably, I have worked on two separate ideas in this coding agent: 1. Turn Memory In a multi-turn conversation, tool outputs are removed, only tool call traces are retained. Within a single agent loop, agent sees full tool results but in the next turn, it doesn't see the tool results anymore. The greatest benefit of this approach is that a lot of tool results that are not needed in following turns don't occupy the context. As a result, context window in a multi-turn conversation with Keen Code fills up much slowly compared to other agents. This is why you will regularly see context window coming down from 20% to 1% at the beginning of a new agent turn. Of course, this approach has its pros and cons. If agent requires tool result from a previous call, it doesn't have them. But my idea is that tool calls like read, bash, web_fetch are cheap. Do you need to refer to some earlier file you read? Read again. In fact, Claude Code or Codex frequently re-read a file, even though it has read the same file before. I have plans for more effort in this area. I have a few additional ideas to explore and possibly optimise this approach further. If you want to read about it: https://mochow13.github.io/keen-code/docs/turn-memory.html 2. Skill-Driven MCP Another idea I have implemented is skill-driven MCPs. The goal is similar to what Anthropic did with tool-search-tool: optimise context. In this idea, each MCP server receives a skill. But this skill is not typical "guidance" skill for MCP server usage, rather generated by Keen. Details here: https://mochow13.github.io/keen-code/docs/mcp-skills.html The big advantage is that no server is pre-loaded completely with tool schemas by default. The agent only receives skill frontmatter for the server. If a server is needed, agent loads the full skill file which lists the tools with descriptions. Then agent reads the specific schema file for the particular tool it wants to invoke. The drawback is that each MCP call requires file read operation. But everything is locally saved upon discovery, so it's totally fine. --- Apart from the above two, I am exploring and playing with other well-known context optimisation ideas like hashline edits. If the above ideas interest you, please do check it out! Here is the CLI usage guideline: https://mochow13.github.io/keen-code/docs/cli-usage.html Since the project is open-source, issues and contributions are more than welcome!
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New Show Hacker News story: Show HN: Graph2agent; Mermaid diagrams, explained for agents
Show HN: Graph2agent; Mermaid diagrams, explained for agents
3 by alexandroskyr | 0 comments on Hacker News.
During the implementation of a huge high performance service. In order to keep context small (mainly for humans) I kept the specs into mermaid diagrams. When communicating with humans; diagrams were easy to follow and to remember. But when I asked the agent to implement what's in the diagram, most of the times it failed. So I came into conclusion that agents are good into writing mermaid diagrams but they are not good into reading them. I built graph2agent in order to deterministically (without inference :) ) convert mermaid diagrams into digestible rich text for agents. examples: https://ift.tt/YBW1y8f... This gave us 50% error reduction for any class of diagrams and 80% error reduction for sequence diagrams specifically. Also Input tokens increased on avg by 8% (which is expected) but Reasoning tokens dropped by almost 50%. You can use it either with MCP so agents can call it with any mermaid diagram, and also can put it in pre-commit jobs and run it on every PR so all diagrams are agent ready! I hope you like it! Let me know your thoughts!
3 by alexandroskyr | 0 comments on Hacker News.
During the implementation of a huge high performance service. In order to keep context small (mainly for humans) I kept the specs into mermaid diagrams. When communicating with humans; diagrams were easy to follow and to remember. But when I asked the agent to implement what's in the diagram, most of the times it failed. So I came into conclusion that agents are good into writing mermaid diagrams but they are not good into reading them. I built graph2agent in order to deterministically (without inference :) ) convert mermaid diagrams into digestible rich text for agents. examples: https://ift.tt/YBW1y8f... This gave us 50% error reduction for any class of diagrams and 80% error reduction for sequence diagrams specifically. Also Input tokens increased on avg by 8% (which is expected) but Reasoning tokens dropped by almost 50%. You can use it either with MCP so agents can call it with any mermaid diagram, and also can put it in pre-commit jobs and run it on every PR so all diagrams are agent ready! I hope you like it! Let me know your thoughts!
New ask Hacker News story: Tell HN: Old.reddit.com Requires Login
Tell HN: Old.reddit.com Requires Login
12 by comprev | 4 comments on Hacker News.
It's finally happened... a sad day for the internet :( Edit: For me anyway in UK using Starlink
12 by comprev | 4 comments on Hacker News.
It's finally happened... a sad day for the internet :( Edit: For me anyway in UK using Starlink
New ask Hacker News story: Ask HN: Should a coding client import another client's rules by default?
Ask HN: Should a coding client import another client's rules by default?
2 by ryanmerket | 0 comments on Hacker News.
An AI coding client automatically reads ~/.codex/AGENTS.md and ~/.claude/CLAUDE.md. These are personal instruction files inside competing coding clients' configuration directories, outside the project selected by the user. Their complete contents are added to the first model request and sent to the client's servers by default. At startup, the client displays a brief notice saying it is including the other clients' personal rules. It does not ask permission first. A command-line option disables the behavior. The configuration guide says: "Your machine-wide user rules always load." It requires users to trust a workspace before loading project instruction files. The machine-wide files load automatically. I tested this by placing a harmless canary instruction in ~/.codex/AGENTS.md. The client followed it during a default run. It did not follow it when foreign personal context was disabled. These files can contain internal coding standards, infrastructure references, project details, or credentials someone pasted and forgot about. Is the startup notice enough disclosure? Does describing the behavior in the documentation amount to consent? Would you expect one coding client to read files from another vendor's configuration directory and send them with the first request?
2 by ryanmerket | 0 comments on Hacker News.
An AI coding client automatically reads ~/.codex/AGENTS.md and ~/.claude/CLAUDE.md. These are personal instruction files inside competing coding clients' configuration directories, outside the project selected by the user. Their complete contents are added to the first model request and sent to the client's servers by default. At startup, the client displays a brief notice saying it is including the other clients' personal rules. It does not ask permission first. A command-line option disables the behavior. The configuration guide says: "Your machine-wide user rules always load." It requires users to trust a workspace before loading project instruction files. The machine-wide files load automatically. I tested this by placing a harmless canary instruction in ~/.codex/AGENTS.md. The client followed it during a default run. It did not follow it when foreign personal context was disabled. These files can contain internal coding standards, infrastructure references, project details, or credentials someone pasted and forgot about. Is the startup notice enough disclosure? Does describing the behavior in the documentation amount to consent? Would you expect one coding client to read files from another vendor's configuration directory and send them with the first request?
New ask Hacker News story: Ask HN: How do you go from writing code to deploying with agents?
Ask HN: How do you go from writing code to deploying with agents?
3 by sakuraiben | 1 comments on Hacker News.
Been doing hardcode agent driven coding for the past year. I feel like I now have to test all my code locally with agents reviewing them and ideally testing them. Unfortunately I feel like the traditional CI/CD testing is starting to feel like a formality. Would love to know what everyone is doing, and if I'm not the only one making a mistake.
3 by sakuraiben | 1 comments on Hacker News.
Been doing hardcode agent driven coding for the past year. I feel like I now have to test all my code locally with agents reviewing them and ideally testing them. Unfortunately I feel like the traditional CI/CD testing is starting to feel like a formality. Would love to know what everyone is doing, and if I'm not the only one making a mistake.