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Autonomous AI coding agent — explores your codebase, diagnoses root causes, writes fixes, and runs tests. Supports Claude, Gemini, DeepSeek, and Kimi K2.

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    Readme

    Spryv Agent

    The autonomous coding agent that works with any model.

    Give Spryv a task. It explores your codebase, diagnoses the root cause, writes the fix, runs the tests, and reports back — without you steering every step. The full autonomy of Claude Code, with the freedom to use any model you choose.

    VS Code Marketplace npm License: MIT

    Why Spryv

    Model freedom — the thing the others don't give you

    Claude Code works only with Claude. Cursor locks you to their subscription. Spryv works with any OpenAI or Anthropic-compatible API — Claude, Gemini, DeepSeek, Kimi K2, any model on OpenRouter, Vertex AI, or a private self-hosted endpoint. Swap providers with a single flag. No lock-in, no walled garden, no subscription.

    spryv --provider deepseek "refactor the payment module"
spryv --provider gemini "fix the race condition in the auth flow"
spryv --provider openrouter "add rate limiting to the API"

    Full agent architecture — not a chat wrapper

    Spryv runs a structured loop modeled on how a senior engineer actually works:

    1. Explore — reads relevant files, maps call graphs, traces execution paths
    2. Plan — builds an explicit plan before touching anything; reasoning is visible
    3. Execute — implements changes through an architect review pass before applying each patch
    4. Verify — runs tests, confirms results, reports exactly what changed and why

    At every iteration it maintains a live state tree: confirmed facts, pending tasks, in-progress changes, sub-agent status. A health-check monitor detects loops and stalls and nudges the agent back on track.

    Sub-agents and skills — built-in extensibility

    Spawn parallel specialized sub-agents for exploration, planning, or code review. Each sub-agent gets its own context, tools, and iteration budget. Results merge back into the main session. Define custom agents and /slash-command skills in Markdown files — no code required.

    Three interfaces, one engine

    VS Code extension with a full chat panel, standalone Electron desktop app with a live state tree sidebar, and a CLI with phase-gated output. Same engine, same sessions, same capabilities across all three.

    Install

    VS Code

    ext install faisalsalamah.spryv

    Or install from the Marketplace / download .vsix from Releases.

    CLI (Node.js 18+)

    npm install -g @spryv/agent
spryv "fix the memory leak in the renderer"

    Desktop App (Windows)

    Download spryv-desktop-setup-v1.0.0-win.exe from Releases and run the installer.

    Quick Start

    spryv "add JWT auth to the API"                    # one-shot task
spryv --chat                                        # interactive mode
spryv --chat --resume <session-id>                  # resume a session
spryv --provider deepseek "fix the memory leak"    # switch provider
spryv --verbose "refactor the auth module"          # verbose output

    Capabilities
    Any model Any OpenAI or Anthropic-compatible API: Claude, Gemini, DeepSeek, Kimi K2, OpenRouter (100s of models), Vertex AI, private endpoints
    Tools Bash execution, file read/write/edit, grep, glob, AST search, vision, sub-agent spawn, skill invoke
    Sub-agents Parallel specialized agents; built-in: explore, planner, pr-review; fully customizable
    Skills User-invocable slash commands; built-in: /commit, /explain; define your own in Markdown
    MCP servers Connect any Model Context Protocol server
    Sessions Full persistence — resume, fork, or replay any past session
    Cost tracking Per-turn token metrics with cache hit rates and estimated cost per provider
    Interfaces VS Code extension, Electron desktop app, CLI

    Documentation
    Installation Setup for all platforms
    Configuration API keys, providers, model selection
    Sub-Agents Built-in agents and how to define custom ones
    Skills Built-in skills and how to define custom ones

    License

    MIT