graphify
Skill0 starsChanged 3 months agoMITView on GitHub
Convierte cualquier codebase en un grafo de conocimiento queryable usando AST parsing. Elimina context rot, reduce tokens 70%, permite preguntas sobre la arquitectura del código. Ejecuta /graphify en cualquier proyecto.
- Installs packages
115 other projects use a version of this.
Adopted by
Most recently taken up by
- thistleknot/skillstheir own version, first seen Nov 8, 2026
- ever-works/skillstheir own version, first seen Nov 8, 2026
- rylsherdamz-rgb/stellar-forgetheir own version, first seen Nov 8, 2026
- brebuilds/claude-skillstheir own version, first seen Nov 8, 2026
- GstMirabal/Token-Optimized-Agent-Pipelinetheir own version, first seen Nov 8, 2026
- MMACABRE/SKILLStheir own version, first seen Nov 8, 2026
Used with
Projects with it also use remotion-maps, remotion-saas and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
OpenAISkillremotion-maps
Remotion Map animation knowledge
Also in 4 projects that use this
OpenAISkillremotion-saas
Build an app with Remotion
Also in 4 projects that use this
royaluniondesign-sysSkilldeployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications.
Also in 4 projects that use this
mstuder-slalomSkilldjango-verification
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
Also in 3 projects that use this
ttmouseSkillprompt-master
提示词主控 - 智能选择合适的领域skill并生成提示词,支持自动领域分类和调度
Also in 4 projects that use this
seikaikyoSkilldoubt-driven-development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
Also in 6 projects that use this
Other versions115 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 115
- safishamsi/graphify★ 144ksame name
- Graphify-Labs/graphify★ 144ksame name
- zaxbysauce/opencode-swarm★ 519same name
- ZaxbyHub/opencode-swarm★ 518same name
- nandyalu/trailarr★ 486same name
- bdfinst/agentic-dev-team★ 302same name
- cin12211/orca-q★ 225same name
- sammcj/agentic-coding★ 169same name
- EBISPOT/ols4★ 106same name
- buildomator/buildomator★ 102same name
105 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- belentani-magicSkill
- debugging-wizardSkill
- deep-researchSkill
- gsap-animationsSkill
- network-text-analysisSkill
- skill-security-auditorSkill
- token-optimizerSkill
- workflow-orchestratorSkill
- writing-skillsSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 113 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Elimina context rot: No necesitas re-leer archivos en cada sesión
“Common” is measured: kept by at least 6 in 10 of the 113 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Graphify - Knowledge Graph for Codebases
Qué hace
Toma tu codebase completo (código, docs, configs, SQL schemas) y lo convierte en un grafo de conocimiento consultable. Cada función, clase, import, y relación se extrae como nodo y arista del grafo.
Por qué es revolucionario
- Elimina context rot: No necesitas re-leer archivos en cada sesión
- Reduce tokens 70%: Solo Consultas lo relevante, no archivos enteros
- Preguntas arquitectónicas: "¿Cómo se conecta el módulo A con B?"
- Dependencies visuales: Ve qué archivos dependen de qué
Setup automático
# Instalar graphify
pip install graphify
# En cualquier proyecto:
graphify init
# Esto crea:
# .graphify/
# ├── graph.json (el grafo de conocimiento)
# ├── metadata.json (stats del proyecto)
# └── config.json (configuración)Uso en MiMoCode
Generar grafo de un proyecto
import tree_sitter
from graphify import GraphBuilder
builder = GraphBuilder()
builder.scan_directory("./src")
graph = builder.build()
# Guardar grafo
graph.save(".graphify/graph.json")
# Consultar
results = graph.query("¿Qué funciones usan la base de datos?")
for node in results:
print(f"{node.file}:{node.line} - {node.name}")Preguntas que puedes hacer
/graphify "¿Qué archivos dependen de database.py?"
/graphify "¿Qué rutas API existen?"
/graphify "¿Qué clases heredan de BaseModel?"
/graphify "¿Qué funciones son públicas vs privadas?"
/graphify "¿Cuál es el flujo de una petición HTTP?"Integración con workflows
# Auto-graphify on save
def on_file_save(filepath):
if filepath.endswith('.py'):
builder.update_file(filepath)
graph.save(".graphify/graph.json")
# Query from any skill
def get_relevant_context(query, graph, max_tokens=2000):
nodes = graph.query(query)
return format_nodes_for_context(nodes, max_tokens)Beneficios medidos
- Tokens ahorrados: 60-90% en sesiones de coding
- Velocidad: Respuestas 3x más rápidas (sin leer archivos innecesarios)
- Precisión: Elimina hallucinations sobre el codebase
- Memoria: Persiste entre sesiones (no se olvida del código)
Archivos generados
.graphify/
├── graph.json # El grafo completo
├── metadata.json # Stats: files, functions, classes
├── config.json # Configuración
├── queries/ # Consultas cacheadas
└── snapshots/ # Versiones del grafoDoes it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

