LLM Wiki Knowledge Graph
Egonex-AI/Understand-Anything
Detects a Karpathy-pattern LLM wiki and builds an interactive knowledge graph with entities, implicit relationships and topic clusters.
Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation.
Install Graph
$ npx skills add ThinkfleetAI/memmesh --skill graph -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ThinkfleetAI/memmesh graph --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/ThinkfleetAI/memmesh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .claude/skills/graph && 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 "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .claude/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graphType 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 ThinkfleetAI/memmesh --skill graph -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ThinkfleetAI/memmesh graph --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .agents/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .agents/skills/graph && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .agents/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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 ThinkfleetAI/memmesh --skill graph -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ThinkfleetAI/memmesh graph --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .cursor/skills/graph && 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 "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .cursor/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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/ThinkfleetAI/memmesh.git --path integrations/memmesh-plugin/skills/graph--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 ThinkfleetAI/memmesh --skill graph -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ThinkfleetAI/memmesh graph --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .gemini/skills/graph && 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 "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .gemini/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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 ThinkfleetAI/memmesh graphInstalls 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 ThinkfleetAI/memmesh --skill graph -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .github/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .github/skills/graph && 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 "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .github/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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 ThinkfleetAI/memmesh --skill graph -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ThinkfleetAI/memmesh graph --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkfleetAI/memmesh.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/integrations/memmesh-plugin/skills/graph .opencode/skills/graph && 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 "graph" agent skill from https://github.com/ThinkfleetAI/memmesh/tree/main/integrations/memmesh-plugin/skills/graph into .opencode/skills/graph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graph", 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
graph- GitHub stars
- 419
- Token cost
- ~611 tokens
- SKILL.md length
- 199 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation.
- Questions no single stored fact answers
- SKILL.md covers Multi-hop reasoning, Point-in-time — what did we…, Anticipatory retrieval… and Building the graph
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- See how knowledge about an entity changed over time
What it does
Graph is an agent skill from ThinkfleetAI/memmesh. Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation. Use for questions no single stored fact answers, or to see how knowledge about an entity changed over time.
Its SKILL.md is about 610 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Knowledge Management, covering Knowledge graphs. The repository describes itself as: Persistent, self-improving memory for AI agents. Local-first Rust memory engine with MCP support. The licence is Apache-2.0.
When your agent uses it
- Questions no single stored fact answers
- See how knowledge about an entity changed over time
Example prompts
- “what did we believe on date X”
- “/graph”
What it can do on your machine
Read from SKILL.md and the folder at commit bba48f8. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are jsonc).
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
Graph loads about 611 tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 199 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 ThinkfleetAI/memmesh at commit bba48f8, republished under its Apache-2.0 licence (© ThinkfleetAI). 199 words, ~611 tokens.
Download SKILL.mdSave it as
.claude/skills/graph/SKILL.md (or your agent's skills folder).- name
- graph
- description
- Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation. Use for questions no single stored fact answers, or to see how knowledge about an entity changed over time.
graph
⚙️ Graph reasoning requires MemMesh hosted mode. Building the graph works locally:
memory_extract_pending→memory_commit_extractionpopulate typed entities/edges. Multi-hop reasoning/traversal (memory_graph_reason,memory_query_graph,memory_prefetch_related) runs on the hosted engine — set yourmm-API key. If those return "unknown tool" on a local install, say so and usesearchover the extracted entities instead.
MemMesh links memories into a knowledge graph whose edges are bi-temporal
(each has valid_from / valid_to). That enables answers a flat store can't
give.
Multi-hop reasoning
Answer questions that require chaining edges — "who acquired the company Sarah founded":
{ "name": "memory_graph_reason",
"arguments": { "anchorEntityId": "<entity id>", "maxHops": 3, "maxPaths": 20 } }Returns ranked paths (scored by edge weight × recency). The anchor is an entity id — resolve names to ids via a graph query first.
Point-in-time — what did we believe then?
{ "name": "memory_query_graph",
"arguments": { "subjectId": "<entity id>", "asOf": "2026-01-01T00:00:00Z" } }Omit asOf for the current view. This reconstructs the graph as it stood on any
date — the bi-temporal record, not just the latest state.
Anticipatory retrieval (spreading activation)
Given the memories a session is working with, surface what's most likely needed next:
{ "name": "memory_prefetch_related", "arguments": { "seedMemoryIds": ["<id>","<id>"], "limit": 10 } }Building the graph
Edges come from client-LLM extraction — the engine hands you a prompt, your own model extracts entities/edges, you commit them (zero engine-side LLM cost):
{ "name": "memory_extract_pending", "arguments": { "projectId": "<repo>", "limit": 10 } }
// run each prompt through your model, then:
{ "name": "memory_commit_extraction", "arguments": { "memoryId": "…", "contentHash": "…", "entities": [...], "edges": [...] } }Run this loop until extract_pending returns empty to fully populate the graph
for reasoning.
© ThinkfleetAI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in integrations/memmesh-plugin/skills/graph of ThinkfleetAI/memmesh.
Open the folder on GitHubat commit bba48f8
Compare with similar skills
Graph 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 |
|---|---|---|---|---|---|---|
| Graph this skillThinkfleetAI/memmesh | 419 | — | ~611 | Automated safety check: Pass | Apache-2.0 | |
| LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything | 85k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Obsidian Canvas BoardsAgriciDaniel/claude-obsidian | 15k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Ontology1mancompany/OneManCompany | 438 | 2 repos | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Graphagenticnotetaking/arscontexta | 3.5k | 1 repos | ~4.9k | Automated safety check: Notes | MIT | |
| Knowledge Graphgnomeria/usbtree | 688 | — | ~1.5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Graph
What does Graph do?
Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation. Graph is an agent skill from ThinkfleetAI/memmesh. Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation.
When should I use Graph?
Graph fits situations like: questions no single stored fact answers; see how knowledge about an entity changed over time.
How do I install Graph in Claude Code?
Run `npx skills add ThinkfleetAI/memmesh --skill graph -a claude-code`. Or copy the skill folder (integrations/memmesh-plugin/skills/graph in ThinkfleetAI/memmesh) into .claude/skills/graph in your project. Claude Code loads it when a task matches its description.
How do I install Graph in Codex?
Run `npx skills add ThinkfleetAI/memmesh --skill graph -a codex`. Or copy the skill folder (integrations/memmesh-plugin/skills/graph in ThinkfleetAI/memmesh) into .agents/skills/graph in your project. Codex loads it when a task matches its description.
Can I use Graph 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 ThinkfleetAI/memmesh --skill graph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/graph, .gemini/skills/graph, .github/skills/graph and .opencode/skills/graph in your project.
What does Graph need to run?
SKILL.md names no scripts, command-line tools or credentials: Graph is instructions for the agent only.
Does Graph 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 Graph 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 Graph use?
Graph is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Graph use?
About 611 tokens (SKILL.md is roughly 2.4k 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 Graph?
Skills that share tags, products or a category with Graph: LLM Wiki Knowledge Graph (Egonex-AI/Understand-Anything, 85k stars), Obsidian Canvas Boards (AgriciDaniel/claude-obsidian, 15k stars), Ontology (1mancompany/OneManCompany, 438 stars) and Graph (agenticnotetaking/arscontexta, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Graph?
ThinkfleetAI (a GitHub organization) maintains it in ThinkfleetAI/memmesh, which has 419 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on August 25, 2026.
Source: ThinkfleetAI/memmesh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.