adhd

Revisar · 65
Indexado en Registry

Parallel divergent ideation — spawns N isolated generator agents under different cognitive frames (regulator, biology, speedrunner, 10-year-old, zero-budget), then a critic pass scores, clusters, prunes traps, and deepens the top 3. Use for open-ended design, architecture, naming

Verified installs0
Estrellas42
Versión1.0.0
Calidad63/100 · Prometedor
Confianza65/100 · Solo sandbox
Auditoría77/100 · Requiere revisión

Perfil del activo

Agents de programación y desarrollo

Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.

Ver categoría

Escenario

Agents de programación

I need a coding agent that can understand a repository, edit code, and review pull requests.

Afinidad con Agent

Claude Code + CLI + Codex

Funciona con Codex, Claude Code, Cursor, CLI o Agents personalizados.

Instalar

Listo

npx skills add darkroomengineering/cc-settings --skill adhd

Mantenimiento

Actual

2 días desde el último push

Riesgo

Requiere revisión

Dependency or permission surface needs review

Calidad de GitHub

42

63/100 Calidad · 73/100 Confianza

Etiquetas de cobertura

CodingAgents de programaciónDiseño y creatividadagent-skill

Notas de revisión

Dependency or permission surface needs review · Permission surface may require sandboxing

Tarjeta de adopción del Agent

Confianza, auditoría y preparación de instalación de un vistazo

Estas puntuaciones combinan metadatos públicos del repositorio, señales de revisión de OpenAgentSkill, actualidad de mantenimiento y preparación de instalación. Sirven para preseleccionar; no sustituyen la revisión humana.

Calidad

Prometedor
63

Useful candidate, but compare it with alternatives before adopting.

Confianza

Solo sandbox
65

Candidata útil con señales de confianza incompletas o mixtas. Manténgala en un espacio aislado hasta que el ciclo de resultados demuestre el ajuste.

Auditoría

Requiere revisión
77

Revisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.

Trust Score de OpenAgentSkill v5

Revisión humana antes de instalar

Ejecute solo en un sandbox y compare alternativas cercanas antes de usarla en trabajo real.

CodexClaude CodeCursorOpenAgentSkill CLI

Estrellas

42 estrellas de GitHub

Actividad del repositorio

42 estrellas y 3 forks

Mantenimiento

2 días desde el último push

Licencia

MIT

Instalar

npx skills add darkroomengineering/cc-settings --skill adhd

Seguridad de instalación

Ruta estándar de paquete o instalación en tiempo de ejecución

Superficie de permisos

shell or command execution, network or browser access

Resultados del Agent

Aún no hay datos de resultados del Agent

Documentación

Contexto sólido de README/SKILL.md

Resumen de riesgo

Revisar antes de producción

  • Financial research output is not financial advice; require human review before any live investment decision.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access

Preparación de instalación

Ruta de instalación disponible

  • La ruta de instalación está disponible
  • La evidencia del repositorio está disponible
  • La licencia está declarada
  • Aún no hay evidencia de resultados Agent-Proven

Metadatos legibles por Agent

Datos de decisión legibles por máquina para este skill.

Usa este bloque o el JSON integrado para decidir si un Agent debe instalar este skill, elegir una alternativa o pedir revisión humana primero.

Abrir JSON

Tareas adecuadas

  • flujos de Agents de programación
  • Equipos de Claude Code
  • builders willing to evaluate younger projects
  • Inspect source files

Agents adecuados

CodexClaude CodeCursorOpenAgentSkill CLICLI

Decisión de instalación

Comando
npx skills add darkroomengineering/cc-settings --skill adhd
Política
Revisar
Revisión humana

Confianza y riesgo

Confianza
65/100
Auditoría
77/100
Nivel de riesgo
Requiere revisión

Ciclo de resultados

Endpoint
/api/agent/outcome
ID del evento
resolve
Resultados
5

Comando de instalación

npx skills add darkroomengineering/cc-settings --skill adhd

No usar cuando

  • Equipos que necesitan un SLA con soporte del proveedor
  • production agents without a repository review
  • Low GitHub adoption signal
  • Indicios de permisos de alto riesgo: ejecución de shell o comandos
  • Dependency or permission surface needs review

Seguridad de Agent v2

45/100 · Evitar instalación automática

ExperimentalRevisar

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolver con API

Alto

Ejecución de shell o comandos

Los metadatos del skill hacen referencia a terminal, CLI, shell, subprocesos o flujos de ejecución de comandos.

Medio

Browser automation

Skill may drive a browser or interact with web pages.

Medio

Acceso a red

El skill probablemente consulta páginas remotas, API, repositorios o servicios externos.

Medio

Acceso a base de datos

El skill puede inspeccionar esquemas, consultar bases de datos o trabajar con almacenes persistentes.

  • Indicios de permisos de alto riesgo: ejecución de shell o comandos
  • Dependency or permission surface needs review

Destinos de instalación

Instala este skill en tu flujo de Agent

Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install darkroomengineering-adhd

Plan de resolución de Agent

Deja que un Agent valide el ajuste antes de instalar.

La API Resolve devuelve la skill elegida, alternativas, política de seguridad, notas de auditoría, destino de instalación y un prompt listo para usar.

Abrir plan de texto

Agent debe revisar

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copiar prompt

Task: Use adhd in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20adhd%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/darkroomengineering-adhd/install
Install command: npx skills add darkroomengineering/cc-settings --skill adhd
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Traspaso de Agent

Da al Agent la ruta de instalación, no otro directorio.

Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.

Abrir API de instalación

Prompt de Agent

Use adhd for this task. Review https://www.openagentskill.com/api/skills/darkroomengineering-adhd/install, then install with: npx skills add darkroomengineering/cc-settings --skill adhd

Metadatos del Registry

Perfil legible por Agent para seleccionar skills automáticamente.

La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Abrir Manifest

Afinidad con Agent

63/100

Agents de programación

Plataformas

Claude Code

Informe de auditoría

Requiere revisión · 77/100

Revisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.

Ver informe de auditoríaVer informe de evaluación

Panel de decisión de Agent

Fallback candidate for Coding agents

Prototype with this skill first; keep a fallback candidate ready.

63
Preparación
Prototipo
Etapa

Rol en la pila

Candidata de respaldo

Ajuste principal

Agents de programación

Etiqueta de confianza

Prototipar primero

Ruta de instalación

Comando listo

Úsalo cuando

  • flujos de Agents de programación
  • Equipos de Claude Code
  • builders willing to evaluate younger projects

Evidencia

  • recent repository activity
  • install command or GitHub repo available
  • perfil de calidad 63/100
  • 3 eventos de interacción de OpenAgentSkill

revisar primero

  • Low GitHub adoption signal

Ruta de implementación

  1. 1Instálalo en un Agent de sandbox y ejecuta una tarea de Agents de programación de principio a fin.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Perfil de confianza

Solo sandbox

Candidata útil con señales de confianza incompletas o mixtas. Manténgala en un espacio aislado hasta que el ciclo de resultados demuestre el ajuste.

65
Trust Score de OpenAgentSkill

Adopción en GitHub

Revisar

42 estrellas de GitHub

Actividad de stars/forks

Revisar

42 estrellas y 3 forks; la actividad de issues no está disponible en los metadatos actuales

Mantenimiento reciente

Aprobado

2 días desde el último push

Claridad de licencia

Aprobado

MIT

Señales positivas

  • Revisión de IA aprobada
  • La ruta de instalación está disponible
  • La evidencia del repositorio está disponible
  • Repositorio mantenido recientemente
  • El comando de instalación no muestra un patrón de alto riesgo evidente
  • El ciclo de resultados está listo, pero necesita la primera ejecución real de Agent

Revisar antes de instalar

  • Financial research output is not financial advice; require human review before any live investment decision.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access
  • GitHub adoption: 42 GitHub stars
  • Stars/forks activity: 42 stars, 3 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, network or browser surface
  • Permission surface: shell or command execution, network or browser access
  • Aún no hay informes reales de resultados del Agent
  • Se requiere revisión humana antes de una instalación desatendida

Acción recomendada

Ejecute solo en un sandbox y compare alternativas cercanas antes de usarla en trabajo real.

Perfil de calidad

Prometedor candidato para flujos de Agent

Useful candidate, but compare it with alternatives before adopting.

63
Estrellas de GitHub
42
Actualidad
hace 2 días
Listo para instalar
Licencia
MIT
Revisar antes de instalar: Low GitHub adoption signal

Ajuste de flujo

Usa esta skill en estos escenarios

Ajuste de flujo

Añadir a un flujo completo

Lista de alternativas

Compara antes de instalar

Similar skills that may fit this task.

Comparar todo

Resumen

--- name: adhd argument-hint: "[problem]" description: Parallel divergent ideation — spawns N isolated generator agents under different cognitive frames (regulator, biology, speedrunner, 10-year-old, zero-budget), then a critic pass scores, clusters, prunes traps, and deepens the top 3. Use for open-ended design, architecture, naming, API/SDK surface, and fuzzy debugging where the obvious answer is expensive to get wrong. Triggers "/adhd", "adhd mode", "brainstorm", "ideate", "widen the option space", "divergent ideas", "we keep landing on the same idea". Skip for lookups, syntax, bugs with a known root cause, or closed phrasing ("quick", "standard", "canonical", "textbook"). Use /oracle compare to evaluate options you already have — adhd generates the option space; use /plan-ceo-review to challenge whether to build at all. context: main license: MIT ---

# ADHD

Stop picking the textbook answer. The first three answers the model would give are the answers a senior engineer would give in thirty seconds. Correct. Forgettable. The interesting answers live past number three, in the awkward middle nobody walks into. This skill makes the model walk there.

## When to use vs siblings

- `/adhd` — **generate** the option space when you don't have candidates yet. - `/oracle` (compare mode) — **evaluate** options you already have. - `/plan-ceo-review` — challenge whether the thing should be built at all. - `/verify` — adversarially check a conclusion you've already reached.

They compose: `/adhd` to widen, `/oracle` to weigh the shortlist.

## Pre-flight (run before Phase 1)

This skill is expensive. About 10 Agent calls, 30 to 90 seconds wall clock, 5 to 10x a single answer. Do not pay that cost when a direct answer is better. Run this gate before Phase 1.

**Step 1. Explicit invocation check.**

If the user typed `/adhd` or explicitly asked for ADHD mode, "use the adhd skill", or "run ADHD on this", **SKIP the rest of this section and go straight to Phase 1**. The user opted in. Do not second-guess.

**Step 2. Self-judge (only if Step 1 did not match).**

Ask yourself three questions. If the answer to any is no, ABORT.

1. **Open-ended?** Would a senior engineer give multiple viable answers here, or is there one canonical answer? If canonical, abort. 2. **High-stakes?** Is the cost of the obvious answer being wrong actually high? Architecture decisions, public API surfaces, naming a real product, fuzzy bugs with no known root cause, schema design = yes. Side project at 11pm = no. 3. **Open phrasing?** Did the user avoid words like "quick", "standard", "canonical", "textbook", "just", "one-line"? If they used any of those, they want the direct answer. Abort.

If all three checks pass, proceed to Phase 1.

If any fails, ABORT and answer the question directly. Optionally append one sentence: *"If you want a wider exploration under parallel cognitive frames with explicit trap detection, run `/adhd <your problem>`."*

## The loop

Two strict phases. Mixing them kills idea quality, because the critic strangles the generator.

### Phase 1 — Diverge (no critic)

For the problem P:

1. Pick 5 cognitive frames from the table below. Bias toward engineering tags when the problem is code-shaped. Always include at least one wild frame to keep range.

2. Spawn 5 **parallel** Agent tool calls in ONE message. One per frame. Each Agent gets only: - the problem P - any context the user provided - the chosen frame's vantage prompt - a system instruction that forbids evaluation

The exact instruction to give each Agent:

> You are in DIVERGENT mode. You are a generator, not a critic. > Generate 6 short distinct ideas under this frame. Each idea is one > phrase or one sentence. Do not evaluate. Do not rank. Do not hedge. > The first three obvious answers everyone would give are banned. > Push past them into the awkward middle. > Output a JSON array only. No prose before or after. > `[{"text": "...", "rationale": "..."}, ...]`

3. **Critical invariant.** The Agent calls must be parallel and isolated. Do NOT serialize them. Do NOT pass one branch's output as context to another. Branches that see each other anchor each other and the whole method collapses to a wider single thought.

### Phase 2 — Focus (critic on)

After all branches return:

1. **Score.** Rate each idea on three axes 0 to 10: novelty (distance from the obvious default), viability (could it actually ship), fit (does it address the stated problem). For any idea that looks attractive but is a trap (hidden cost, false economy, will not scale, premature abstraction), flag it with a one-line reason.

2. **Cluster.** Group ideas into 3 to 6 clusters by their underlying angle, not by surface keywords. Label clusters by angle: "remove the server plays", "cache-shaped plays", "batched-window plays", "race-multiple- backends plays".

3. **Deepen the top 3.** Rank by weighted score (novelty 0.35 + viability 0.40 + fit 0.25), exclude traps, take top 3. For each, spawn one Agent call that produces: - a 4 to 8 sentence sketch of how the idea works - the load-bearing risk - the first concrete step a builder would take - 3 to 5 child ideas (variations, hybrids, unlocks)

Deepen Agent instruction:

> You are in FOCUS mode. Take one promising idea and connect dots. > Sketch how it would actually work in 4 to 8 sentences. Name the > load-bearing risk. Name the first concrete step a coder would take. > Then generate 3 to 5 sub-ideas that branch off (variations, > combinations with other domains, things this unlocks). > Output JSON only.

Scoring, clustering, and the final synthesis stay in the main session — that is judgment work and belongs on the session's top-tier model. The generator and deepen agents are fan-out subagents and inherit `CLAUDE_CODE_SUBAGENT_MODEL` (Sonnet), which fits the quota doctrine: roomy pools carry volume, the scarce pool does the judging.

## Frames

Pick 5 per run.

| Frame | Vantage prompt | Tags | |---|---|---| | **hardware engineer** | You think in latency, memory layout, and physical constraints. Re-ask this as a hardware/firmware problem. What does the bus topology, cache, timing budget tell you? | code, wild | | **regulator** | You audit systems for compliance and failure modes. What must be provable, traceable, or refusable here? | design, general | | **10-year-old** | You are a curious 10 year old who has never seen software. Describe naive but unencumbered approaches. Ignore convention. | general, wild | | **competitor trying to break it** | You are a hostile competitor or attacker. Generate approaches that exploit, fail, or sabotage the obvious solution. Then invert into ideas. | code, design | | **biology** | Transplant a mechanism from biology (immune systems, neural plasticity, cell signaling, evolution, gut flora). Force-fit it onto this engineering problem. | code, wild | | **logistics** | Steal mechanisms from logistics: queues, batching, just-in-time, hub-and-spoke, returns, last-mile. Apply them literally. | code, design | | **game design** | Approach this as a game designer. What are the loops, rewards, friction, save-states, speedrun tricks? Treat the user as a player. | design, general | | **markets** | Treat the problem as a market. Buyers, sellers, market-makers. What does an auction, a futures contract, a clearing house look like here? | design, wild | | **inversion** | Ask the OPPOSITE question. If goal is X, brainstorm how to guarantee NOT X. Then negate each answer back. | code, design, general | | **extreme: $0 budget, 1 hour** | No money, no team, one hour. What is the crudest version that still does the load-bearing thing? | code, general | | **extreme: infinite budget, 10 years** | Infinite compute, infinite engineers, a decade. What is the maximalist version? | design, wild | | **remove the load-bearing assumption** | Name the thing everyone treats as fixed (framework, database, request-response model, network). Imagine it is gone. What is possible? | code, design, wild | | **speedrunner** | You are a speedrunner. Find glitches, skips, out-of-bounds tricks, frame-perfect shortcuts. What is the abusive-but-legal path? | code, wild | | **ant colony** | No central planner. Many dumb agents, local rules, pheromone trails. How does the problem solve itself emergently? | code, wild | | **3am on-call** | You are the on-call engineer woken at 3am when this breaks. What design would let you not get paged? | code, design |

### Picking frames

For code-shaped problems: pick 4 frames tagged `code` or `design`, plus 1 tagged `wild`. For open product or strategy problems: a mix from all tags. Vary the picks across sessions so the same problem produces different candidate sets when re-run.

## Output shape

After Phase 2, render in this order. Do not collapse it into a wall of prose. The structure is the point.

1. **Brief.** One or two lines confirming the problem and any reframe used. 2. **Wide set.** Full pool grouped by cluster. Each cluster labeled by underlying angle. Each idea is one short phrase. Show score chips like `[N7 V8 F9]` next to each. 3. **Converge.** A 2 to 4 idea shortlist. State why each is on the list. Mark the non-obvious-but-viable pick explicitly with ★. List traps separately, each with the one-line reason it is a trap. 4. **Focus.** The 3 deepened branches. For each: the sketch, the load- bearing risk, the first concrete step, and the child ideas. 5. **Provocation.** One wildcard question or idea that opens a new direction the user can push into if nothing landed.

## Anti-patterns

These are how this skill goes wrong. Watch for them.

- **Convergence disguised as divergence.** Ten minor variations of one idea is not breadth. If every candidate shares the same underlying assumption, you have not diverged. You have decorated. - **Weird-for-weird's-sake with no convergence.** A pile of 30 unsorted absurdities is as useless as one safe answer. Always converge. - **Walls of equally-weighted prose.** Cluster, label, pull out the best. Structure is half the value. - **Refusing to commit.** After diverging, take a position on what is actually promising. "Here are 20 ideas, you decide" is a cop-out. Generate wide, but converge with a real opinion. - **Skipping the isolation invariant.** If you simulate parallel branches by writing them sequentially in one context, you have not done ADHD. You have done a wider single thought. The Agent tool gives each branch a fresh context. Use it.

## Calibration

- **How many ideas?** Scale to stakes. Quick "name this function" = 3 frames × 4 ideas. "How should I position this product" = 5 frames × 8 ideas. Default is 5 × 6 = 30. - **How weird?** Read the room. Serious strategy work: flag the wild cards clearly so they do not read as unserious. Open brainstorming or play: let it run loose. Absurd ideas earn their place by seeding viable ones. - **When to stop diverging?** Stop when new candidates start repeating the shape of existing ones. The space is mapped. Do not pad to hit a number.

## Cost

5 diverge + 1 score + 1 cluster + 3 deepen ≈ 10 Agent calls per run. About 5 to 10x a single-shot answer. Not for every keystroke. For decision points where the cost of the obvious answer is high. Diverge/deepen agents run on the Sonnet subagent pool, so the Opus/Fable cost of a run is one synthesis pass.

## Attribution

Ported from [`UditAkhourii/adhd`](https://github.com/UditAkhourii/adhd) (MIT). Upstream ships the same loop as an npm CLI (`adhd-agent`) plus evals and a source spec on divergent ideation; this port keeps the skill-only form (no install) and adds the cc-settings sibling-skill routing and subagent model notes.

Detalles técnicos

Versión
1.0.0
Licencia
MIT
Última actualización
20 ago 2026
Publicado
20 ago 2026

Resumen de decisión

Candidata de respaldo

63
Listo
Prototipo
Etapa

recent repository activity

Auditoría

Revisión de instalación

Revisión de instalación y adopción

77
Requiere revisión
Seguridad
78/100
Mantenimiento
100/100
Instalar
92/100
Abrir auditoría completaVer informe de evaluación

Evidencia probada por Agent

Evidencia probada por Agent

Informes de resultados tras resolver, revisar, instalar y una ejecución limitada.

0
Probado
Needs first agent runAuto-instalación: revisar primeroÚltimo: Desconocido
Tasa de éxito
Fallo reciente
Resultados
0
Calidad de salida
Fallidos
0
No relevante
0
Instalaciones
0
Bloqueado por riesgo
0
Configuración necesaria
0
Producción
0

Aún no hay datos de resultados de Agent. La primera ejecución puede informar éxito, configuración necesaria, bloqueos de riesgo, fallo o irrelevancia mediante /api/agent/outcome.

Instalar

Añadir al flujo de Agent

Gratis y de código abierto. Revisa el informe antes de instalar en Agents de producción.

Bucle de crecimiento

Kit para compartir

X

Borrador basado en un caso para adhd, listo para publicar manualmente en X.

Nota del curador
adhd: Parallel divergent ideation — spawns N isolated generator agents under different cognitive fr...

42 stars

https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x
Abrir borrador de X
Respuesta opcional con comando de instalación
Listing + install path for adhd:
https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x

Install: npx skills add darkroomengineering/cc-settings --skill adhd

Fuente de la ficha

Indexado por Registry

Reclamable

Esta ficha se indexó desde fuentes públicas y no está marcada como oficial hasta que se apruebe una reclamación de mantenedor.

Indexado por
Índice comunitario de OpenAgentSkill

La atribución enlaza al repositorio público o al perfil del creador. Los creadores pueden reclamar la ficha para actualizar las señales de propiedad.

Reclamar este skill

Reclamación del propietario

Reclamar esta ficha de skill

Esta ficha Indexado por Registry se atribuye a darkroomengineering, pero aún no está marcada como oficial. Reclámala para añadir una señal de propietario verificado y hacer más fiables futuras actualizaciones de lanzamiento, instalación y auditoría.

Kit de enlaces para creadores

Añade las insignias de evidencia a tu README

Muestra la ficha canónica, las señales actuales de confianza y auditoría, y evidencia real de Agent-Proven donde los desarrolladores evalúan el repositorio.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=listed&label=Listed)](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=trust&label=Trust)](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=audit&label=Audit)](https://www.openagentskill.com/skills/darkroomengineering-adhd/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/darkroomengineering-adhd)

Autor

D

darkroomengineering

@darkroomengineering

Etiquetas

Afinidad con plataforma

Señales de salud

Estrellas de GitHub
42
Puntuación de calidad
35/100
Último push de GitHub
20 ago 2026
Pistas del framework
Desconocido
Vistas de OpenAgentSkill
3
Copias de instalación
0
Clics externos
0

Señal de comunidad

Comparte si este skill resulta útil para tu flujo de Agent. Los comentarios agregados mejoran la clasificación con el tiempo.

Confianza y seguridad

Solo sandbox

65
  • Adopción en GitHub42 estrellas de GitHubRevisar
  • Actividad de stars/forks42 estrellas y 3 forks; la actividad de issues no está disponible en los metadatos actualesRevisar
  • Mantenimiento reciente2 días desde el último pushAprobado
  • Claridad de licenciaMITAprobado
  • Completitud de README/SKILL.mdLos metadatos incluyen suficiente contexto de uso y flujo de trabajoAprobado
  • Riesgo de dependencias/runtimecommand execution surface, network or browser surfaceRevisar