ventrox
OfficialVentrox
Un agente de codificación choca contra el mismo muro muchas veces al día, y nadie lo ve.
Ventrox añade una llamada de herramienta al agente: qué intentó, qué falló, minutos perdidos.
El agente no puede leer los vents de vuelta; el servidor sella cada uno con sesión, proyecto, rama y hora.
Un revisor inicia VENTROX_SECRET=$(ventrox grant) claude y lista los vents agrupados por similitud aproximada, ordenados por recuento y minutos.
El muro que costó más minutos aparece primero.
Unas pocas cientos de líneas de Python, un archivo SQLite en tu directorio personal, dos comandos para instalar.
Nada sale por la red, y nada acaba en tu repositorio.
La agrupación es TF-IDF sobre n-gramas y se pierde los sinónimos; la redacción es una lista de expresiones regulares, con el mejor esfuerzo posible.
Límites: 20 vents por sesión, 5 por cada 10 minutos.
La idea proviene de la herramienta vent y vent-widget de Lovable.
Instalación
Instala Ventrox como herramienta global:
uv tool install git+https://github.com/Vetrox/ventrox.gitO clona e instala desde el checkout:
git clone https://github.com/Vetrox/ventrox && cd ventrox && uv tool install .Después ejecuta la configuración:
ventrox setupLa configuración copia las habilidades ventrox-report y ventrox-review a ~/.claude/skills/.
Después registra el servidor MCP con claude mcp add --scope user ventrox -- ventrox.
Related MCP server: todox MCP Server
Uso
Reportero: el agente llama a ventrox_vent con tried, failed y minutes_lost.
Escribe un vent por turno, y solo después de que la misma fricción se repita (dos fallos o más de 10 minutos).
Corrige un vent en la misma sesión con ventrox_edit.
El servidor acepta 20 vents por sesión y 5 vents por cada 10 minutos.
Revisor: inicia una sesión con un token de un solo uso:
VENTROX_SECRET=$(ventrox grant) claudeEl token es de un solo uso y válido durante 10 minutos. La sesión contiene entonces las herramientas de revisor. Llámalas en este orden:
ventrox_reclusteragrupa los vents abiertos por solapamiento de vocabulario.ventrox_clusterslista los grupos ordenados por recuento de abiertos y luego por minutos perdidos.ventrox_resolve_clustermarca un grupo comoresolvedowontfix.
Desinstalación
ventrox setup --remove
uv tool uninstall ventrox
rm -r ~/.local/share/ventrox # deletes all ventsHerramientas
Herramienta | Modo | Argumentos | Devuelve |
| reporter |
|
|
| reporter |
|
|
| reviewer |
| el vent, o |
| reviewer |
|
|
| reviewer | ninguno |
|
| reviewer | ninguno | recuento de |
| reviewer |
|
|
| reviewer |
|
|
Los campos de texto admiten de 1 a 4000 caracteres. minutes_lost va de 0 a 1440.
Variables de entorno
Variable | Propósito | Valor por defecto |
| Directorio de datos | sin definir |
| ID de sesión | generado por proceso |
| Token de concesión para una sesión de revisor; de un solo uso, válido 10 minutos | sin definir |
| Ruta a un archivo con ejemplos de proyecto | sin definir |
| Vents que el servidor acepta por sesión | 20 |
| Vents que el servidor acepta por cada 10 minutos | 5 |
Ubicación de los datos
El servidor elige la primera de $VENTROX_HOME, $XDG_DATA_HOME/ventrox y ~/.local/share/ventrox.
Todos los vents viven en vents.db en ese directorio.
El archivo es SQLite plano sin cifrado; solo los permisos de archivo lo protegen.
El servidor se niega a arrancar cuando el directorio de datos está dentro de un árbol de trabajo de git, y sale con el código 2.
Habilidades
ventrox-report le dice al agente cuándo una fricción cuenta como vent y qué deben contener los tres campos.
ventrox-review le dice a un revisor que ejecute recluster, clusters y luego resolve.
ventrox setup instala ambas.
Ejemplos de proyecto
Coloca un archivo .ventrox.md en la raíz del proyecto para añadir ejemplos específicos del proyecto de buenos vents.
Establece VENTROX_EXAMPLES a una ruta de archivo para añadir ejemplos para todos los proyectos.
El servidor añade ambos a la descripción de la herramienta ventrox_vent.
Desarrollo
uv sync
uv run pytest
uv run ventroxNo objetivos
Ventrox no sincroniza con un rastreador de incidencias. No tiene modo multiusuario. No registra trazas de llamadas de herramientas, solo los tres campos que escribe el agente. No abre ninguna conexión de red.
Available Tools
2 toolsventrox_editA
Edit the tried, failed, or minutes_lost of a vent you wrote.
Provide the vent ID. Validation rules match ventrox_vent. Returns ok (true or false). If the edit fails, we do not state the reason. Possible causes: wrong ID, wrong session, or validation error.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| tried | No | ||
| failed | No | ||
| minutes_lost | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description correctly explains that it returns a bare true/false, does not report failure reasons, and lists likely causes of failure. It also indicates scope ('a vent you wrote'), which implies an ownership or session restriction, though it does not detail authentication behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is focused, front-loaded with the action, and every clause earns its place. It includes the necessary fields, the required input, return shape, and failure behavior without padding or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description gives sufficient info to call it and interpret false results. The user session context is mentioned but not explained, and validation rules are deferred to a sibling tool, which is acceptable but not fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must clarify parameter meaning. It names all editable fields ('tried, failed, or minutes_lost') and the required id, covering the four parameters adequately even without per-property explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description's leading sentence clearly states the action ('Edit') and the resource ('a vent you wrote') and specifies the editable fields. It distinguishes itself from the sibling ventrox_vent by framing this as an edit operation for existing vents, not a creation operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the required input ('Provide the vent ID') and implies this is used to modify an existing vent instead of creating one. It does not explicitly name ventrox_vent as the alternative, but the context signals make the intended usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ventrox_ventA
Record friction you hit today.
A vent describes what blocked you. Write what you tried, what failed, and how many minutes you lost. Do not write fixes, workarounds, or lessons. We do not read vents back to you.
Write one vent per turn. Write a vent only after you hit the same friction again. Friction repeats when the same thing fails two times or more, or when one thing costs more than 10 minutes.
Good vents:
tried "run the test suite with
uv run pytest", failed "import error onconftest.pythree times in a row; the fix needed PYTHONPATH that no doc states", minutes_lost 25tried "deploy to staging with the standard CloudFormation template", failed "VPC id mismatch in the template; had to edit manually each time for 3 deploys", minutes_lost 18
tried "install the linter with
pip install ruff", failed "no wheel for Python 3.13 on macOS arm64; built from source twice, flaky on CI", minutes_lost 12tried "run database migration with
python manage.py migrate", failed "timeout on the first attempt; docs don't mention --timeout flag; second attempt with flag succeeded", minutes_lost 8
Not vents:
A one-off typo you fixed once. That is not repeated friction.
"How do I make the tests faster?" That is a question, not friction.
"Next time use pytest-xdist for parallel tests". That is a lesson or a fix, not what blocked you.
"Finished the feature, took 3 hours". That is a task-progress note, not friction.
| Name | Required | Description | Default |
|---|---|---|---|
| tried | Yes | ||
| failed | Yes | ||
| minutes_lost | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, and it does so thoroughly. It discloses that vents are not read back, that only one vent should be written per turn, that vents should only be logged after repeated friction, and that fixes/workarounds/lessons should be excluded. This goes well beyond a simple 'record friction' statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than average, but every section earns its place: a front-loaded purpose statement, eligibility thresholds, and illustrative good/bad examples. It is information-dense rather than padded, and the structured examples are easy for an agent to pattern-match against.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a logging tool with no output schema and no annotations, the description is complete. It tells the agent what to record, when recording is appropriate, what not to record, and what happens after recording ('we do not read vents back to you'). No critical operational detail appears to be missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must supply all parameter meaning. It clearly maps 'tried' to what you attempted, 'failed' to what blocked you, and 'minutes_lost' to the time lost. The examples reinforce this by showing realistic combinations, and the 'not vents' section clarifies what should not go into the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as recording friction: what you tried, what failed, and minutes lost. It gives strong examples of good and bad vents. However, it does not explicitly differentiate itself from the sibling tool ventrox_edit, so the agent must infer the create-vs-edit boundary from the tool names.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: write a vent only after the same friction repeats, with precise thresholds like two failures or more than 10 minutes lost. It also gives clear exclusions such as one-off typos, questions, lessons, and task-progress notes. It does not mention ventrox_edit as the alternative for editing existing vents, so the usage guidance is excellent for creation but not complete against its sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v0.1.0- First observed
ventrox_edit - First observed
ventrox_vent
TDQS
Scored across 2 tools
ventrox_vent is exclusively for recording a new friction event, while ventrox_edit explicitly modifies an existing vent's fields. There is no overlap or ambiguity between creating and editing.
Both tools share the ventrox_ prefix and use short action-style names, making the pattern predictable. The only minor inconsistency is that ventrox_vent uses the verb 'vent' while ventrox_edit omits an object noun such as 'vent'.
Two tools is slightly thin, but it matches the server's focused purpose of recording and correcting friction entries. Each tool is meaningful and there is no bloat.
The server covers creating and editing vents, which are the core operations for its purpose. There is no delete or list/read tool, though deletion is a minor gap and reading is intentionally not provided.
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