feat: Improved coder agent that is now a graph-based agent
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# Coder
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An AI agent that assists you with your coding tasks.
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A graph-based implementation agent. Plans, implements, and runs build +
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tests in a bounded fix-loop until verified. Designed to be delegated to by
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the **[Sisyphus](../sisyphus/README.md)** agent.
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This agent is designed to be delegated to by the **[Sisyphus](../sisyphus/README.md)** agent to implement code specifications. Sisyphus
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acts as the coordinator/architect, while Coder handles the implementation details.
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Coder is a [graph agent](https://github.com/Dark-Alex-17/loki/wiki/Graph-Agents): its workflow is
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defined declaratively in `graph.yaml`, with verification and the
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implement-fix loop enforced as graph edges rather than prose.
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## Features
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## Workflow
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- 🏗️ Intelligent project structure creation and management
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- 🖼️ Convert screenshots into clean, functional code
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- 📁 Comprehensive file system operations (create folders, files, read/write files)
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- 🧐 Advanced code analysis and improvement suggestions
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- 📊 Precise diff-based file editing for controlled code modifications
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```
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analyze_request (llm + output_schema) plan + complexity extraction
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↓
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route_complexity (script) opt-out approval gate (complexity ≥ 7)
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↓
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gate_approval (approval, optional)
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↓
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implement (llm + fs tools) actual file edits
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↓
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verify_build (script)
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↓
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verify_tests (script)
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↓
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fix_loop_gate (script) back-edge to implement (bounded)
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↓
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end_success / end_rejected / end_failure
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```
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It can also be used as a standalone tool for direct coding assistance.
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End nodes emit one of three sentinel outcomes for the caller:
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## Pro-Tip: Use an IDE MCP Server for Improved Performance
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Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
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an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
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server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
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them), and modify the agent definition to look like this:
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- `CODER_COMPLETE` — build and tests passed.
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- `CODER_REJECTED` — user rejected the plan at the approval gate.
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- `CODER_FAILED` — fix-loop exhausted; build/tests still failing.
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## Tuning
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The agent's `project_dir` is exposed via the standard `variables:` block,
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so it accepts the runtime override flag:
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```sh
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# Invoke from inside the project (project_dir defaults to ".")
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cd /path/to/your/project
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loki -a coder "Add a foo() function..."
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# Or invoke from anywhere with an explicit override
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loki -a coder --agent-variable project_dir /path/to/your/project "Add..."
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```
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`graph.yaml` `initial_state` exposes:
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- `max_fix_attempts` (default `3`) — fix-loop budget before `end_failure`.
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Environment overrides honored by the script nodes:
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- `BUILD_CMD` — skip project-type detection for the build/check command.
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- `TEST_CMD` — skip detection for tests.
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- `CODER_AUTOAPPROVE=1` — bypass the approval gate (for non-interactive runs
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where complexity might trip the gate).
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## Pro-Tip: IDE MCP Server
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Modern IDEs (JetBrains, VS Code, Cursor, Zed, etc.) expose MCP servers
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that let LLMs use IDE tools directly. To wire one in, edit `graph.yaml`:
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```yaml
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# ...
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mcp_servers:
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- jetbrains # The name of your configured IDE MCP server
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- your-ide-mcp-server
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global_tools:
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# Keep useful read-only tools for reading files in other non-project directories
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# Keep read-only fs tools for files outside the IDE project
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- fs_read.sh
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- fs_grep.sh
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- fs_glob.sh
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# - fs_write.sh
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# - fs_patch.sh
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- execute_command.sh
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```
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# ...
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```
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Then add the MCP server's write/patch tools to the `implement` node's
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`tools:` whitelist.
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