adhd
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
Profil de l’actif
Agents de code et de développement
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scénario
Agents de code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Adéquation Agent
Claude Code + CLI + Codex
Compatible avec Codex, Claude Code, Cursor, CLI ou des Agents personnalisés.
Installer
Prêt
npx skills add darkroomengineering/cc-settings --skill adhd
Maintenance
À jour
2 jours depuis le dernier push
Risque
Revue nécessaire
Dependency or permission surface needs review
Qualité GitHub
42
63/100 Qualité · 73/100 Confiance
Tags de couverture
Notes de revue
Dependency or permission surface needs review · Permission surface may require sandboxing
Carte d’adoption Agent
Confiance, audit et préparation à l’installation en un coup d’œil
Ces scores combinent les métadonnées publiques du dépôt, les signaux de revue OpenAgentSkill, la fraîcheur de maintenance et la préparation à l’installation. Ils servent à présélectionner et ne remplacent pas la revue humaine.
Qualité
PrometteurUseful candidate, but compare it with alternatives before adopting.
Confiance
Sandbox uniquementCandidate utile avec des signaux de confiance incomplets ou mixtes. Gardez-la dans un espace isolé jusqu’à ce que la boucle de résultats confirme son adéquation.
Audit
Revue nécessaireRevue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Trust Score OpenAgentSkill v5
Revue humaine avant installation
Exécutez uniquement dans un sandbox et comparez les alternatives proches avant usage réel.
Stars
42 stars GitHub
Activité du dépôt
42 stars et 3 forks
Maintenance
2 jours depuis le dernier push
Licence
MIT
Installer
npx skills add darkroomengineering/cc-settings --skill adhd
Sécurité d’installation
Chemin d’installation standard de package ou runtime
Surface de permissions
shell or command execution, network or browser access
Résultats Agent
Pas encore de données de résultats Agent
Documentation
Contexte README/SKILL.md solide
Résumé des risques
Revoir avant production
- 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
Préparation à l’installation
Chemin d’installation disponible
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- La licence est déclarée
- Pas encore de preuve de résultat Agent-Proven
Métadonnées lisibles par Agent
Données de décision lisibles par machine pour ce skill.
Utilisez ce bloc ou le JSON intégré pour décider si un Agent doit installer ce skill, choisir une alternative ou demander d’abord une revue humaine.
Tâches adaptées
- workflows Agents de code
- Équipes Claude Code
- builders willing to evaluate younger projects
- Inspect source files
Agents adaptés
Décision d’installation
- Commande
- npx skills add darkroomengineering/cc-settings --skill adhd
- Politique
- Revoir
- Revue humaine
- Oui
Confiance et risque
- Confiance
- 65/100
- Audit
- 77/100
- Niveau de risque
- Revue nécessaire
Boucle de résultat
- Endpoint
- /api/agent/outcome
- ID d’événement
- resolve
- Résultats
- 5
Commande d’installation
npx skills add darkroomengineering/cc-settings --skill adhdNe pas utiliser quand
- Équipes qui nécessitent un SLA soutenu par le fournisseur
- production agents without a repository review
- Low GitHub adoption signal
- Indices de permissions à haut risque : exécution shell ou de commande
- Dependency or permission surface needs review
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Sécurité Agent v2
45/100 · Éviter l’installation automatique
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Élevé
Exécution shell ou de commande
Les métadonnées de la skill font référence à des workflows de terminal, CLI, shell, sous-processus ou exécution de commande.
Moyen
Browser automation
Skill may drive a browser or interact with web pages.
Moyen
Accès réseau
La skill récupère probablement des pages distantes, API, dépôts ou services externes.
Moyen
Accès à la base de données
La skill peut inspecter des schémas, interroger des bases de données ou travailler avec des stockages persistants.
- Indices de permissions à haut risque : exécution shell ou de commande
- Dependency or permission surface needs review
Cibles d’installation
Installer ce skill dans votre workflow Agent
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
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-adhdPlan de résolution Agent
Laissez un Agent vérifier la pertinence avant l’installation.
L’API Resolve renvoie la skill sélectionnée, des alternatives, la politique de sécurité, les notes d’audit, la cible d’installation et un prompt prêt à l’emploi.
Ouvrir JSON
/api/agent/resolve?task=Use%20adhd%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texte Resolve
/api/agent/resolve?task=Use%20adhd%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Relais d’installation
/api/skills/darkroomengineering-adhd/install
L’Agent doit vérifier
- 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.
Copier le 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.Relais Agent
Donnez à l’Agent le chemin d’installation, pas un autre annuaire.
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
Relais d’installation
/api/skills/darkroomengineering-adhd/install
Format texte LLM
/api/skills/darkroomengineering-adhd/install?format=text
Trouver des alternatives
/api/skills/search?q=adhd&limit=3
Prompt 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 adhdMétadonnées Registry
Profil lisible par Agent pour la sélection automatique de skills.
L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.
Manifest
/api/registry/manifest/darkroomengineering-adhd
Texte LLM
/api/registry/manifest/darkroomengineering-adhd?format=text
Alias d’installation
/api/registry/install/darkroomengineering-adhd
Recommander
/api/registry/recommend?task=Use%20adhd%20in%20an%20agent%20workflow&limit=3
Adéquation Agent
Agents de code
Tags de cas d’usage
Plateformes
Claude Code
Rapport d’audit
Revue nécessaire · 77/100
Revue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Panneau de décision Agent
Fallback candidate for Coding agents
Prototype with this skill first; keep a fallback candidate ready.
Rôle dans la pile
Candidate de secours
Pertinence principale
Agents de code
Libellé de confiance
Prototyper d’abord
Chemin d’installation
Commande prête
À utiliser lorsque
- workflows Agents de code
- Équipes Claude Code
- builders willing to evaluate younger projects
Preuves
- recent repository activity
- install command or GitHub repo available
- profil qualité 63/100
- 3 événements OpenAgentSkill
revoir d’abord
- Low GitHub adoption signal
Chemin d’implémentation
- 1Installez-le dans un Agent en sandbox et exécutez une tâche de Agents de code de bout en bout.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil de confiance
Sandbox uniquement
Candidate utile avec des signaux de confiance incomplets ou mixtes. Gardez-la dans un espace isolé jusqu’à ce que la boucle de résultats confirme son adéquation.
Adoption GitHub
Vérifier42 stars GitHub
Activité stars/forks
Vérifier42 stars et 3 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Validé2 jours depuis le dernier push
Clarté de licence
ValidéMIT
Signaux positifs
- Revue IA approuvée
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- Dépôt maintenu récemment
- La commande d’installation ne présente aucun motif de haut risque évident
- La boucle de résultats est prête mais nécessite la première exécution réelle de l’Agent
Réviser avant installation
- 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
- Pas encore de rapports de résultats Agent réels
- Une revue humaine est requise avant une installation sans surveillance
Action recommandée
Exécutez uniquement dans un sandbox et comparez les alternatives proches avant usage réel.
Profil qualité
Prometteur candidat pour les workflows Agent
Useful candidate, but compare it with alternatives before adopting.
Adéquation au workflow
Utilisez cette skill dans ces scénarios
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Adéquation au workflow
Ajouter à un workflow complet
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Liste d’alternatives
Comparer avant installation
Similar skills that may fit this task.
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Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Taste Skill: Anti-Slop Frontend
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Vue d’ensemble
--- 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.
Détails techniques
- Version
- 1.0.0
- Licence
- MIT
- Dernière mise à jour
- 20 août 2026
- Publié
- 20 août 2026
Instantané de décision
Candidate de secours
recent repository activity
Audit
Revue d’installation
Revue d’installation et d’adoption
- Sécurité
- 78/100
- Maintenance
- 100/100
- Installer
- 92/100
Preuves validées par Agent
Preuves validées par Agent
Rapports après resolve, revue, installation et une exécution limitée.
- Taux de réussite
- —
- Échec récent
- —
- Résultats
- 0
- Qualité de sortie
- —
- Échecs
- 0
- Non pertinent
- 0
- Installations
- 0
- Bloqué par le risque
- 0
- Configuration requise
- 0
- Production
- 0
Aucune donnée de résultat Agent pour l’instant. La première exécution peut signaler succès, besoin de configuration, blocage de risque, échec ou non-pertinence via /api/agent/outcome.
Installer
Ajouter au workflow Agent
Gratuit et open source. Examinez le rapport avant l’installation dans des Agents de production.
Boucle de croissance
Kit de partage
Brouillon guidé par scénario pour adhd, prêt pour une publication manuelle sur X.
adhd: Parallel divergent ideation — spawns N isolated generator agents under different cognitive fr... 42 stars https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x
Réponse facultative avec commande d’installation
Listing + install path for adhd: https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x Install: npx skills add darkroomengineering/cc-settings --skill adhd
Source de la fiche
Indexé par Registry
Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.
- Créateur
- darkroomengineering
- Indexé par
- Index communautaire OpenAgentSkill
L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.
Revendiquer ce skillRevendication du propriétaire
Revendiquer cette fiche de skill
Cette fiche Indexé par Registry est attribuée à darkroomengineering, mais n’est pas encore marquée officielle. Revendiquez-la pour ajouter un signal de propriétaire vérifié et rendre les futures mises à jour de lancement, d’installation et d’audit plus fiables.
Kit de backlinks créateur
Ajoutez les badges de preuve à votre README
Affichez la fiche canonique, les signaux actuels de confiance et d’audit, ainsi que de vraies preuves Agent-Proven là où les développeurs évaluent le dépôt.
[](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[](https://www.openagentskill.com/skills/darkroomengineering-adhd/audit)
[](https://www.openagentskill.com/skills/darkroomengineering-adhd)Auteur
darkroomengineering
@darkroomengineering
Tags
Adéquation plateforme
Signaux de santé
- Stars GitHub
- 42
- Score de qualité
- 35/100
- Dernier push GitHub
- 20 août 2026
- Indications de framework
- Inconnu
- Vues OpenAgentSkill
- 3
- Copies d’installation
- 0
- Clics sortants
- 0
Signal de communauté
Indiquez si ce skill semble utile à votre workflow Agent. Les retours agrégés améliorent le classement au fil du temps.
Confiance et sécurité
Sandbox uniquement
- Adoption GitHub42 stars GitHubVérifier
- Activité stars/forks42 stars et 3 forks; l’activité des issues n’est pas disponible dans les métadonnées actuellesVérifier
- Maintenance récente2 jours depuis le dernier pushValidé
- Clarté de licenceMITValidé
- Complétude README/SKILL.mdLes métadonnées incluent suffisamment de contexte d’usage et de workflowValidé
- Risque dépendances/runtimecommand execution surface, network or browser surfaceVérifier
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