The terminal coding assistant with real agent handoffs.

linkerassistant is an open-source CLI tool that integrates directly with your repository, letting you delegate complex refactoring and tasks to autonomous agents seamlessly.

CA DuRBUSkrjM7dS2XWy4tTjW8XivYM4t14J6xSzDH4pump
~ / dev / project — bash
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linkerassistant init
Initializing linkerassistant environment...
✓ Workspace configured successfully.
linkerassistant task "Refactor the auth middleware to use JWT"
Analyzing repository structure...
Found relevant files: src/auth.js, src/middleware.js
Spawning agent session [id: auth-refactor-99a]
...
✓ Agent completed task. Diff ready for review.
linkerassistant diff
Showing unified diff for workspace changes...
_
CORE PHILOSOPHY

Real repo. Real workflow. Real builders.

Built for environments where code quality and execution context actually matter.

v1.0 PRODUCTION READY
Go 1.26 BUILT WITH GO
GPL 3.0 OPEN SOURCE
FEATURES

Built around repository work, explicit permissions, and real agent handoffs.

LinkerAssistant isn't just a chatbot in your terminal. It's a structured workflow engine that delegates tasks to autonomous agents while keeping you firmly in control.

No hidden context

Agents only see what they explicitly need to. You control the scope of files passed to the model.

You control execution

Terminal commands are proposed by the agent, but never executed without your explicit Y/n approval.

Built for real codebases

Handles massive monorepos using advanced AST parsing and syntax-aware chunking.

Always interruptible

If the agent goes off track, send a SIGINT, correct the prompt, and resume seamlessly.

ARCHITECTURE

Every part of the workflow is a first-class surface.

Diff-based applies

Changes are staged as unified diffs, letting you review exactly what changed before committing.

Context awareness

Automatically pulls in imported files and type definitions relevant to the current task.

Permission boundaries

Strict sandboxing prevents agents from accessing environment variables or sensitive files.

History tracking

Every prompt, diff, and command execution is logged locally in `.linker/history`.

Local filesystem

Reads and writes directly to your disk. No remote syncing or cloud workspace required.

LSP integration

Leverages your local Language Server Protocol to detect compilation errors before applying.

Custom commands

Define custom scripts that the agent can invoke to run tests or linters automatically.

CI/CD pipelines

Run LinkerAssistant in headless mode to review PRs or automate boilerplate updates.

WORKFLOW

From trust to resume, in five steps.

The lifecycle of an autonomous task delegation.

01

TASK DELEGATION

Define the goal in natural language. LinkerAssistant parses the intent.

02

CONTEXT GATHERING

The agent reads relevant files and constructs a mental model of the codebase.

03

EXECUTION

Code is generated and shell commands are formulated to complete the task.

04

REVIEW & APPROVE

You inspect the generated diffs and approve terminal executions.

05

APPLY & RESUME

Changes are written to disk. The agent yields control back to you.

COMPARISON

The terminal coding assistant, as a real workflow.

Feature LinkerAssistant Standard AI Agents
Code edits Unified diff review Blindly overwrites files
Execution model Prompt -> Plan -> Await Y/N Auto-executes everything
Context boundaries Explicit file inclusion Sends entire directory
Environment Your local terminal Cloud container
Extensibility Custom shell scripts Hardcoded capabilities
DOCS

Everything important is already documented.

FAQ

Questions that come up once you start using it for real work.

Can I use my own API keys?
Yes. LinkerAssistant supports OpenAI, Anthropic, and local LLMs via Ollama. You configure your keys in the `.linker/config.yml` file, and they never leave your machine.
Does it send code telemetry?
No. LinkerAssistant is fully open-source and privacy-first. The only network requests made are the direct API calls to your chosen LLM provider.
What models are supported?
Currently, we support GPT-4, Claude 3.5 Sonnet, and any OpenAI-compatible endpoint (like local Llama 3). We recommend Claude 3.5 Sonnet for the best coding performance.
How is context managed?
You can explicitly pass files via the CLI (`linkerassistant task -f src/main.go "..."`) or let the agent use its read tools to explore the workspace autonomously.
Can it run terminal commands?
Yes, the agent can propose terminal commands (like running tests or grep). However, it will always pause and wait for your explicit confirmation before executing them.
Does it modify files directly?
By default, it generates a unified diff and presents it to you. You can review the diff and apply it, or configure it to auto-apply if you prefer a faster workflow.
GET STARTED

Open the repo. Read the docs.
Run it locally.

The codebase is open source and available on GitHub. Stop copy-pasting code.
Start delegating workflows.

Read documentation