Gitnexus Guide
aws-samples/sample-kolya-br-proxy
A skill your agent uses when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference.
High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support.
Install Knowledge Layer
$ npx skills add study8677/repobrain --skill knowledge-layer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install study8677/repobrain knowledge-layer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .claude/skills/knowledge-layer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .claude/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add study8677/repobrain --skill knowledge-layer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install study8677/repobrain knowledge-layer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .agents/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .agents/skills/knowledge-layer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .agents/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add study8677/repobrain --skill knowledge-layer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install study8677/repobrain knowledge-layer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .cursor/skills/knowledge-layer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .cursor/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/study8677/repobrain.git --path engine/repobrain_engine/skills/knowledge-layer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add study8677/repobrain --skill knowledge-layer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install study8677/repobrain knowledge-layer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .gemini/skills/knowledge-layer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .gemini/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install study8677/repobrain knowledge-layerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add study8677/repobrain --skill knowledge-layer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .github/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .github/skills/knowledge-layer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .github/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add study8677/repobrain --skill knowledge-layer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install study8677/repobrain knowledge-layer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/study8677/repobrain.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/engine/repobrain_engine/skills/knowledge-layer .opencode/skills/knowledge-layer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "knowledge-layer" agent skill from https://github.com/study8677/repobrain/tree/main/engine/repobrain_engine/skills/knowledge-layer into .opencode/skills/knowledge-layer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-layer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
knowledge-layer- GitHub stars
- 1.3k
- Token cost
- ~324 tokens
- SKILL.md length
- 103 words
- Files
- 3
- Skills in repo
- 5
- Repo updated
- First seen
- Licence
- MIT
At a glance
High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support.
- Tasks that involve Knowledge graphs
- SKILL.md covers Purpose, Inputs, Outputs and Boundaries, plus 2 more sections
- Runs Python scripts from its folder
What it does
Knowledge Layer is an agent skill from study8677/repobrain. High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support. Exposes refreshfilesystem and askfilesystem for building and querying the knowledge graph.
Its SKILL.md is about 320 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `__init__.py` and `tools.py`).
It sits in Knowledge Management, covering Knowledge graphs. It works with Model Context Protocol. The repository describes itself as: 🧠 RepoBrain (formerly Antigravity) — Give your repo a brain. ChatGPT for your codebase: works in Claude Code, Cursor, Codex, Windsurf & more. The licence is MIT.
When your agent uses it
- Tasks that involve Knowledge graphs
Example prompts
- “/knowledge-layer”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit ed8a5d0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Knowledge Layer loads about 324 tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 103 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from study8677/repobrain at commit ed8a5d0, republished under its MIT licence (© study8677). 103 words, ~324 tokens.
Download SKILL.mdSave it as
.claude/skills/knowledge-layer/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- knowledge-layer
- description
- High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support. Exposes `refresh_filesystem` and `ask_filesystem` for building and querying the knowledge graph.
Knowledge Layer Skill
Purpose
Provide a high-level deployment wrapper over RepoBrain core, with graph-first knowledge injection and all-file support (code, docs, data, media metadata).
Inputs
refresh_filesystem(workspace=".", quick=False)ask_filesystem(question, workspace=".")
Outputs
- Refresh writes graph-first artifacts under
.repobrain/:knowledge_graph.jsonknowledge_graph.mdknowledge_graph.mmddocument_index.mddata_overview.mdmedia_manifest.md- plus existing
conventions.mdandstructure.md
- Ask returns a grounded answer with source paths.
Boundaries
- Skill is a wrapper layer only; no standalone runtime.
- Core Hub/Agent/Pipeline architecture remains the source of truth.
Compatibility
- Existing commands (
rb-refresh,rb-ask,rb-mcp) remain valid. - High-level aliases can be disabled with
RB_ENABLE_LAYER_ALIASES=0.
Degrade Strategy
- If graph artifacts are unavailable, ask falls back to
structure.mdandconventions.mdcontext.
© study8677, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in engine/repobrain_engine/skills/knowledge-layer of study8677/repobrain.
- SKILL.md
- __init__.py
- tools.py
Open the folder on GitHubat commit ed8a5d0
Compare with similar skills
Knowledge Layer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Knowledge Layer this skillstudy8677/repobrain | 1.3k | — | ~324 | Automated safety check: Pass | MIT | |
| Gitnexus Guideaws-samples/sample-kolya-br-proxy | 106 | 10 repos | ~867 | Automated safety check: Pass | MIT-0 | |
| Sage Wikixoai/sage-wiki | 620 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Remnic Entitiesjoshuaswarren/remnic | 217 | — | ~612 | Automated safety check: Pass | MIT | |
| Memex Best Practicesiamtouchskyer/memex | 142 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Askagenticnotetaking/arscontexta | 3.5k | 1 repos | ~5.7k | Automated safety check: Pass | MIT |
Similar skills
- Official
Sage Wiki
xoai/sage-wiki
Reference skill for sage-wiki — local-first knowledge graph with MCP server, REST API, compiled wiki, and Obsidian-compatible output.
Remnic Entities
joshuaswarren/remnic
Browse entities in the Remnic knowledge graph and surface their facts and relationships.
Memex Best Practices
iamtouchskyer/memex
Zettelkasten best practices for building a high-quality knowledge graph.
Ask
agenticnotetaking/arscontexta
Query the bundled research knowledge graph for methodology guidance.
Infranodus
infranodus/skills
Text network analysis and knowledge graphs via the InfraNodus MCP server: analyze text structure, find content gaps, generate research questions and ideas, compare texts, optimize content for…
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Categories
Questions about Knowledge Layer
What does Knowledge Layer do?
High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support. Knowledge Layer is an agent skill from study8677/repobrain. High-level deployment wrapper over RepoBrain core with graph-first knowledge injection and all-file support.
When should I use Knowledge Layer?
Knowledge Layer fits situations like: tasks that involve Knowledge graphs.
How do I install Knowledge Layer in Claude Code?
Run `npx skills add study8677/repobrain --skill knowledge-layer -a claude-code`. Or copy the skill folder (engine/repobrain_engine/skills/knowledge-layer in study8677/repobrain) into .claude/skills/knowledge-layer in your project. Claude Code loads it when a task matches its description.
How do I install Knowledge Layer in Codex?
Run `npx skills add study8677/repobrain --skill knowledge-layer -a codex`. Or copy the skill folder (engine/repobrain_engine/skills/knowledge-layer in study8677/repobrain) into .agents/skills/knowledge-layer in your project. Codex loads it when a task matches its description.
Can I use Knowledge Layer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add study8677/repobrain --skill knowledge-layer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knowledge-layer, .gemini/skills/knowledge-layer, .github/skills/knowledge-layer and .opencode/skills/knowledge-layer in your project.
What does Knowledge Layer need to run?
Going by SKILL.md and its folder, Knowledge Layer needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Knowledge Layer access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Knowledge Layer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Knowledge Layer use?
Knowledge Layer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Knowledge Layer use?
About 324 tokens (SKILL.md is roughly 1.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Knowledge Layer?
Skills that share tags, products or a category with Knowledge Layer: Gitnexus Guide (aws-samples/sample-kolya-br-proxy, 106 stars), Sage Wiki (xoai/sage-wiki, 620 stars), Remnic Entities (joshuaswarren/remnic, 217 stars) and Memex Best Practices (iamtouchskyer/memex, 142 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Knowledge Layer?
study8677 (a GitHub user) maintains it in study8677/repobrain, which has 1,325 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on September 9, 2026.
Source: study8677/repobrain on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.