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kibi

Kibi is a requirement-conformance layer for AI coding agents that keeps product intent connected to code and tests, and catches when implementations drift from it.

Install / Use

claude mcp add Looted -- npx -y github:Looted/kibi

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

84/100

Supported Platforms

Claude Code
Claude Desktop
Cursor
OpenAI Codex

Our assessment of kibi

kibi scores 84/100 on our quality scale, 2873rd of 4,603 Development & Engineering skills we index.

Its MCP Server is 20 KB long, well organised into 13 sections with 13 code examples: a thorough specification that gives an agent plenty to work with.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated today, so kibi is actively maintained.
  • It is released under AGPL-3.0, a copyleft license: you can use it, but modified versions you distribute must carry the same license.
  • Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-18. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

kibi compared with similar skills

All 4 of these similar skills score higher than kibi; compare them before choosing.

SkillScoreStarsUpdatedFormat
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Agent-Reachby Panniantong10098.7k2d agoCLAUDE.md
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headroomby headroomlabs-ai10075.6ktodayCLAUDE.md
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Frequently asked questions

How do I install kibi?
Run claude mcp add Looted -- npx -y github:Looted/kibi. The install tabs above show the steps for each supported agent.
Which AI agents does kibi work with?
It is written for Claude Code, Claude Desktop, Cursor and OpenAI Codex, as a MCP Server file. Other agents that read the same format can often use it too.
Is kibi safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is AGPL-3.0-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is kibi still maintained?
The repository was last updated today, so kibi is actively maintained.

Kibi Wordmark

Status: Beta CI Coverage Kibi requirement health License: AGPL-3.0-or-later X @kibi_dev

Prompt the intent. Kibi makes the agent remember it—and prove the implementation.

<img src="assets/terminal-demo.svg" width="820" alt="Animated terminal: Kibi refuses a contradicting requirement, flags an impossible scenario, an unproven requirement and untraced code, answers a knowledge-base search, and reminds the agent of a requirement before an edit">

<sub>Simplified from what Kibi reports in each case.</sub>

Kibi is an agent-native requirements compiler and enforcement layer. You describe product intent in natural language; the agent creates and maintains the structured requirements, scenarios, tests, semantic facts, and code links. Kibi then checks that the implementation remains coherent with that intent.

Unlike passive memory or retrieval systems, Kibi is designed to place itself in the agent's workflow. The agent does not have to remember to consult a ticket, board, or requirements folder: Kibi's hooks, tools, and validation gates continuously bring the relevant product context back into the work.

Documentation · Quick start · Kibi's own health report

Why Kibi

Most project knowledge is scattered across prompts, tickets, code, and conversations—and most AI agents eventually forget part of it. Kibi turns that knowledge into an enforceable, branch-local model:

  • Humans maintain intent, not artifacts — The prompt is the primary authoring interface. Agents own the routine work of creating and evolving requirements, scenarios, tests, facts, and symbol links; humans resolve genuine ambiguity and product decisions.
  • Memory is enforceable — Symbols need requirement ownership, requirements need complete semantics and scenarios, scenarios need tests, and proof-bearing tests need fresh execution evidence.
  • Prolog guards against drift — Typed properties, predicates, and safe rules let deterministic checks expose contradictions, unsupported invention, and incomplete semantics before they become accepted project knowledge.
  • E2E behavior is traceable — Kibi records what an end-to-end test proves, not merely which lines it happened to execute. You can navigate from a symbol to its requirement or from a test to the scenario and intent it verifies.
  • Intent survives branch changes — Each Git branch has its own KB snapshot, so feature context stays isolated and is there when you return.
  • Works across languages — TypeScript and JavaScript symbols are built in. The optional kibi-plugin-treesitter adds offline symbol extraction for Python, Go, Rust, Java, C#, PHP, C, C++, Bash, Ruby, and Terraform/HCL using pinned WASM grammars.
  • Optional UI design guard (experimental) — kibi-plugin-ui keeps React and Angular components on their agreed design patterns. Pixels, colours and spacing stay with your linter.
  • Keep knowledge local — KB state lives in your repository's .kb/ directory; the Kibi packages send no external telemetry or analytics. Only the documentation website counts visits, with cookieless Umami analytics.

Quick start

Kibi is meant to be set up and driven by your coding agent, so the recommended install is a prompt rather than a list of commands. Kibi requires Node.js 22+. SWI-Prolog is bundled: on Linux (x64 or arm64, glibc 2.28+) and macOS (Apple silicon or Intel) there is nothing else to install. On other platforms, such as Alpine/musl or native Windows (use WSL), install SWI-Prolog 9.0+ and put swipl on your PATH (details).

Recommended: let your agent set it up. Paste this into Claude Code, Cursor, Codex, OpenCode, or any coding agent that can run commands in your repository:

Set up Kibi (https://github.com/Looted/kibi) in this repository, then bootstrap its knowledge base.

1. Install: confirm Node.js 22+ is available. With the package manager this repository already uses, add kibi-core, kibi-cli and kibi-mcp as dev dependencies. Do not skip optional dependencies; the bundled SWI-Prolog runtime is one.
2. Initialize: run every `kibi` command through the package manager's local runner (npm: `npm exec -- kibi <command>`). Run `kibi init`; if it reports a problem, run `kibi doctor` and fix what it names. If this platform has no bundled SWI-Prolog, tell me what to install and stop.
3. Connect: register the project-local `kibi-mcp` server for the agent host you are running in, following https://looted.github.io/kibi/guide/connect-an-agent.html. Prefer project-scoped configuration, and ask me before installing a plugin or changing global settings. Until the kb_* tools are visible to you, use Kibi's CLI JSON routes instead.
4. Bootstrap: run `kibi skills load kibi-bootstrap --format markdown` and follow that skill exactly. It starts by asking me where product intent lives outside the code (issue trackers, wikis, specs) and which sources to trust; read them through the connectors you have and cite them. Show me the complete plan and its hash, and write nothing until I approve it.
5. Verify: run `kibi check` and `kibi status`, fix anything they report, and summarize what was added. Do not commit; I will review the changes.

What happens next:

  1. Setup. The agent installs the packages, runs kibi init, and connects itself to Kibi.
  2. Interview. It asks where your product intent already lives (issue trackers such as Jira or YouTrack, wikis, specs) and which of those sources to trust.
  3. Plan. It reads those sources through the connectors it has and drafts a bootstrap plan. Every requirement in the plan cites the ticket or page it came from. Open questions and conflicts it finds between sources are flagged for you rather than turned into requirements.
  4. Your approval. It shows you the plan and its hash. Nothing is written until you approve.
  5. Apply and check. It applies the plan, validates the result, then fills in what the plan could not write, such as scenarios from acceptance criteria and machine-checkable facts for the new requirements. It tells you what it added.

After that, work normally: prompt for features, fixes, and refactors, and the agent keeps requirements, scenarios, tests, and code links in step with the code.

<details> <summary>Manual installation</summary>

In your repository:

npm install --save-dev kibi-core kibi-cli kibi-mcp
npm exec -- kibi init

kibi init creates the .kb/ layout and installs the Git hooks that keep it in sync. It never overwrites a hook it did not write, and it does not infer product knowledge. Connect your coding agent, then ask it:

Bootstrap Kibi for this repository.

pnpm, Yarn, and Bun work the same way through their local runners. The installation guide has their equivalents, how Kibi finds SWI-Prolog, and package-manager caveats. npm exec -- kibi doctor tells you whether everything is in place.

</details>

Upgrading. After updating the Kibi packages, run kibi migrate (or ask your agent to). It shows what would change and applies nothing until you approve; the CLI reference covers each schema version.

Connect your coding agent

The setup prompt above does this step for you. To do it by hand: every client starts the same project-local kibi-mcp server (npx --no-install kibi-mcp, stdio, working directory = your repository). Optional plugins add bundled skills and hooks on top.

<details> <summary>Claude Code</summary>

Install the optional kibi-claude plugin from this repository's marketplace. It brings the MCP server, the bundled skills, and hooks that show the agent the linked requirements, what they must keep true, and the decision behind them before it reads or edits code, including through shell commands. The agent connection guide has the details:

claude plugin marketplace add Looted/kibi
claude plugin install kibi-claude@kibi

Without the plugin, register the server for the project:

claude mcp add --scope project kibi -- npx --no-install kibi-mcp
</details> <details> <summary>Cursor</summary>

Add Kibi to .cursor/mcp.json:

{
  "mcpServers": {
    "kibi": {
      "command": "npx",
      "args": ["--no-install", "kibi-mcp"]
    }
  }
}

The optional kibi-cursor plugin adds rules, bundled skills, commands, and advisory hooks that show the same requirement context as the Claude Code plugin before reads and edits of linked code. See the Cursor plugin guide.

</details> <details> <summary>Codex</summary>
codex mcp add kibi -- npx --no-install kibi-mcp

The optional kibi-codex plugin bundles Kibi skills, MCP configuration, and warning-only hooks that bring the linked requirement into the agent's context before it changes code. Add the Kibi repository marketplace, open Codex, then run /plugins, choose Kibi Plugins, and install kibi-codex:

codex plugin marketplace add Looted/kibi

The repository marketplace is not the official OpenAI Plugin Directory; self-serve plugin publishing is not available there yet. Manual MCP configuration remains fully supported.

</details> <details> <summary>OpenCode</summary>

Add Kibi to opencode.json. The optional kibi-opencode plugin adds prompt guidance (including what a requirement linked to the file being edited must keep true) and background maintenance:

{
  "mcp": {
    "kibi": {
      "type": "local",
      "enabled": true,
      "command": ["npx", "--no-install", "kibi-mcp"]
    }
  },
  "plugin": ["kibi-opencode"]
}
</details> <details> <summary>VS Code</summary>

Add Kibi to .vscode/mcp.json:

{
  "servers": {
    "kibi": {
      "type": "stdio",
      "command": "npx",
      "args": ["--no-install", "kibi-mcp"]
    }
  }
}
</details> <details> <summary>ZCode and other MCP clients</summary>

Any stdio MCP client works with command: npx, args: --no-install kibi-mcp. ZCode also has an optional plugin, installed from a local checkout, whose edit hook shows the same requirement context as the Claude Code plugin; see the ZCode plugin guide. Agents without MCP can use the same operations through the CLI's JSON routes.

</details>

What your agent gets

Kibi's skill subsystem gives the agent four bundled skills that teach it how to work with Kibi, so you do not paste a long system prompt, and a small set of MCP tools does the rest:

  • Plain-language answers. Ask "what governs checkout rounding?" and kb_search returns the current requirements, the tests and decisions behind them, and what Kibi's checks say about each.
  • A review of every change. kb_check on the files the agent touched quotes

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars10
CategoryDevelopment
Updated15h ago
Forks2

Languages

TypeScript

Trust signals

97/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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