How do I install the Forkmind skill?

Run npx skillmds@latest add ccplugins/forkmind in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Forkmind safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Forkmind?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Forkmind free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Forkmind?

ccplugins (@ccplugins) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Forkmind by ccplugins — Agent Skill

Name: Forkmind
Rating: 4.2 (5 reviews)
Author: ccplugins

Forkmind

Use when debugging, comparing, or regression-testing LLM / agent calls — when the user wants to capture LLM traffic, see a conversation as a branchable DAG, fork an alternative prompt or model from a past turn, or pin good outputs as baselines to catch drift. ForkMind is local-first (no cloud, no account) and proxies any OpenAI-compatible API, defaulting to free Ollama models. Trigger: "debug this prompt", "compare two models", "branch from that turn", "why did the LLM change its answer", "regression test my prompt", "capture LLM calls", "forkmind".

ccplugins Updated Sep 10, 2026

File contents

ForkMind

ForkMind treats AI context windows like a Git repo. It runs a local proxy that records every LLM call into .forkmind/ as a node in a DAG, serves a dashboard, and lets you branch alternative prompts/models from any historical turn.

When to reach for it

Situation	Why ForkMind
"This prompt sometimes regresses — catch it"	Pin baselines, re-run, diff drift
"Compare llama3 vs gpt-4o on the same turn"	Fork the node, swap model, re-run
"Why did the agent change its answer?"	Inspect the DAG: request/response, tokens, lineage
"Capture all LLM traffic during this task"	Point client at the proxy; everything is logged
Agent needs to recall its own past attempts	ForkMind MCP server exposes the history

Do NOT use for: production traffic logging at scale, hosted/cloud observability, or non-LLM HTTP debugging.

Run it

ForkMind runs straight from the git link — no npm registry needed:

# starts proxy + dashboard on :4500
npx github:medhovarsh/forkmind start

Then point any OpenAI-compatible client at the proxy:

baseURL: http://localhost:4500/v1
dashboard: http://localhost:4500

Free local default: install Ollama, ollama pull llama3. Any provider works (OpenAI, Anthropic, Groq, OpenRouter, Together, vLLM, LM Studio) by passing that provider's base URL + key through the proxy.

Core moves

Capture — route calls through :4500/v1; each call becomes a DAG node.
Branch — in the dashboard, "Fork from here" on any node → edit prompt / swap model / change params → re-run only that subtree.
Inspect — node inspector shows request, response, tokens, provenance, and whether the response was streamed.
Regression test — pin a known-good output as a baseline; re-run after a prompt tweak; ForkMind flags drift (wire into CI).

MCP for agents

Installed as the Claude Code plugin, ForkMind's MCP server is wired up automatically (forkmind server, launched via npx … forkmind mcp). An agent can query its own history mid-task — recall previous attempts, trace lineage, self-correct. No manual config needed.

Outside the plugin, add it to any MCP client by hand:

{
  "mcpServers": {
    "forkmind": { "command": "npx", "args": ["-y", "github:medhovarsh/forkmind", "mcp"] }
  }
}

Delegating heavy compares

For "compare model X vs Y" or "why did the answer change" tasks that would dump big transcripts into context, spawn the forkmind-debugger subagent. It runs the comparison in isolation and returns a compact verdict (winner, diff, drift), not raw logs.

Notes

Everything is plain JSON on disk under .forkmind/. No database, no telemetry.
Add .forkmind/ to .gitignore (the repo already does for its own checkout).
Full docs: https://github.com/Medhovarsh/forkmind#readme

---name: forkminddescription: Use when debugging, comparing, or regression-testing LLM / agent calls — when the user wants to capture LLM traffic, see a conversation as a branchable DAG, fork an alternative prompt or model from a past turn, or pin good outputs as baselines to catch drift. ForkMind is local-first (no cloud, no account) and proxies any OpenAI-compatible API, defaulting to free Ollama models. Trigger: "debug this prompt", "compare two models", "branch from that turn", "why did the LLM change its answer", "regression test my prompt", "capture LLM calls", "forkmind".---# ForkMindForkMind treats AI context windows like a Git repo. It runs a local proxy thatrecords every LLM call into `.forkmind/` as a node in a DAG, serves a dashboard,and lets you branch alternative prompts/models from any historical turn.## When to reach for it| Situation | Why ForkMind ||---|---|| "This prompt sometimes regresses — catch it" | Pin baselines, re-run, diff drift || "Compare llama3 vs gpt-4o on the same turn" | Fork the node, swap model, re-run || "Why did the agent change its answer?" | Inspect the DAG: request/response, tokens, lineage || "Capture all LLM traffic during this task" | Point client at the proxy; everything is logged || Agent needs to recall its own past attempts | ForkMind MCP server exposes the history |Do NOT use for: production traffic logging at scale, hosted/cloud observability,or non-LLM HTTP debugging.## Run itForkMind runs straight from the git link — no npm registry needed:```bash# starts proxy + dashboard on :4500npx github:medhovarsh/forkmind start```Then point any OpenAI-compatible client at the proxy:- `baseURL: http://localhost:4500/v1`- dashboard: `http://localhost:4500`Free local default: install [Ollama](https://ollama.com), `ollama pull llama3`.Any provider works (OpenAI, Anthropic, Groq, OpenRouter, Together, vLLM, LM Studio)by passing that provider's base URL + key through the proxy.## Core moves- **Capture** — route calls through `:4500/v1`; each call becomes a DAG node.- **Branch** — in the dashboard, "Fork from here" on any node → edit prompt / swap model / change params → re-run only that subtree.- **Inspect** — node inspector shows request, response, tokens, provenance, and whether the response was streamed.- **Regression test** — pin a known-good output as a baseline; re-run after a prompt tweak; ForkMind flags drift (wire into CI).## MCP for agentsInstalled as the Claude Code plugin, ForkMind's MCP server is wired upautomatically (`forkmind` server, launched via `npx … forkmind mcp`). An agentcan query its own history mid-task — recall previous attempts, trace lineage,self-correct. No manual config needed.Outside the plugin, add it to any MCP client by hand:```json{ "mcpServers": { "forkmind": { "command": "npx", "args": ["-y", "github:medhovarsh/forkmind", "mcp"] } }}```## Delegating heavy comparesFor "compare model X vs Y" or "why did the answer change" tasks that would dumpbig transcripts into context, spawn the **`forkmind-debugger`** subagent. It runsthe comparison in isolation and returns a compact verdict (winner, diff, drift),not raw logs.## Notes- Everything is plain JSON on disk under `.forkmind/`. No database, no telemetry.- Add `.forkmind/` to `.gitignore` (the repo already does for its own checkout).- Full docs: https://github.com/Medhovarsh/forkmind#readme

Frequently asked questions