sesori-plan-worker
Execute plans and multi-step PR series end to end. Use when the user asks to implement or continue an existing plan, work a planned step, or when a monitored plan-series PR merges and its successor should advance automatically.
Asset-Profil
Coding- und Entwickler-Agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Szenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent-Fit
Claude Code + CLI + Codex
Geeignet für Codex, Claude Code, Cursor, CLI oder benutzerdefinierte Agents.
Installieren
Bereit
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Wartung
Aktuell
1 Tage seit dem letzten Push
Risiko
Prüfung nötig
Permission surface may require sandboxing
GitHub-Qualität
105
66/100 Qualität · 69/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
Agent-Adoptionskarte
Vertrauen, Audit und Installationsbereitschaft auf einen Blick
Diese Werte kombinieren öffentliche Repository-Metadaten, OpenAgentSkill-Reviewsignale, Wartungsaktualität und Installationsbereitschaft. Sie helfen bei der Vorauswahl, ersetzen aber keine menschliche Prüfung.
Qualität
VielversprechendUseful candidate, but compare it with alternatives before adopting.
Vertrauen
Nur SandboxNützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
Audit
Prüfung nötigMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Menschliche Prüfung vor Installation
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Stars
105 GitHub-Stars
Repository-Aktivität
105 Stars und 6 Forks
Wartung
1 Tage seit dem letzten Push
Lizenz
NOASSERTION
Installieren
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
filesystem or document access, network or browser access
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Starker README/SKILL.md-Kontext
Risikoübersicht
Vor Produktion prüfen
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: filesystem or document access, network or browser access
Installationsbereitschaft
Installationspfad verfügbar
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Lizenz ist angegeben
- Noch keine Agent-Proven-Ergebnisbelege
Agent-lesbare Metadaten
Maschinenlesbare Entscheidungsdaten für diesen Skill.
Nutze diesen Block oder das eingebettete JSON, um zu entscheiden, ob ein Agent diesen Skill installieren, eine Alternative wählen oder zuerst menschliche Prüfung anfordern soll.
Geeignete Aufgaben
- Workflow-Automatisierung-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
- Move data between tools
Geeignete Agents
Installationsentscheidung
- Befehl
- npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
- Richtlinie
- Prüfen
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 61/100
- Audit
- 76/100
- Risikoebene
- Prüfung nötig
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-workerNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- production agents without a repository review
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- No OpenAgentSkill engagement data yet
- Permission surface may require sandboxing
Agent-Sicherheit v2
56/100 · Vor Installation prüfen
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Mittel
Netzwerkzugriff
Die Skill ruft wahrscheinlich Remote-Seiten, APIs, Repositories oder externe Dienste ab.
Mittel
Dateisystemzugriff
Die Skill kann Projektdateien, Dokumente, generierte Artefakte oder den lokalen Arbeitsbereich lesen oder schreiben.
Mittel
Datenbankzugriff
Die Skill kann Schemata prüfen, Datenbanken abfragen oder mit persistenten Speichern arbeiten.
- Permission surface may require sandboxing
Installationsziele
Diesen Skill im Agent-Workflow installieren
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
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 sesori-ai-sesori-plan-workerAgent-Auflösungsplan
Lass einen Agent die Eignung vor der Installation prüfen.
Die Resolve API liefert die beste Skill, Alternativen, Sicherheitsrichtlinien, Auditnotizen, Installationsziel und einen direkt nutzbaren Prompt.
JSON öffnen
/api/agent/resolve?task=Use%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve-Text
/api/agent/resolve?task=Use%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Installationsübergabe
/api/skills/sesori-ai-sesori-plan-worker/install
Agent sollte prüfen
- 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.
Prompt kopieren
Task: Use sesori-plan-worker in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-worker/install
Install command: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent-Übergabe
Gib dem Agent den Installationspfad, nicht noch ein Verzeichnis.
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
Installationsübergabe
/api/skills/sesori-ai-sesori-plan-worker/install
LLM-Textformat
/api/skills/sesori-ai-sesori-plan-worker/install?format=text
Alternativen finden
/api/skills/search?q=sesori-plan-worker&limit=3
Agent-Prompt
Use sesori-plan-worker for this task. Review https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-worker/install, then install with: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-workerRegistry-Metadaten
Agent-lesbares Profil für die automatische Skill-Auswahl.
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Manifest
/api/registry/manifest/sesori-ai-sesori-plan-worker
LLM-Text
/api/registry/manifest/sesori-ai-sesori-plan-worker?format=text
Installationsalias
/api/registry/install/sesori-ai-sesori-plan-worker
Empfehlen
/api/registry/recommend?task=Use%20sesori-plan-worker%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Workflow-Automatisierung
Plattformen
Claude Code
Audit-Bericht
Prüfung nötig · 76/100
Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
Agent-Entscheidungspanel
Fallback candidate for Workflow automation
Prototype with this skill first; keep a fallback candidate ready.
Rolle im Stack
Fallback-Kandidat
Primäre Eignung
Workflow-Automatisierung
Vertrauenslabel
Zuerst prototypisieren
Installationspfad
Befehl bereit
Verwenden wenn
- Workflow-Automatisierung-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
Evidenz
- recent repository activity
- install command or GitHub repo available
- Qualitätsprofil 66/100
zuerst prüfen
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- No OpenAgentSkill engagement data yet
Implementierungspfad
- 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Workflow-Automatisierung-Aufgabe vollständig aus.
- 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.
Vertrauensprofil
Nur Sandbox
Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
GitHub-Akzeptanz
Info105 GitHub-Stars
Star-/Fork-Aktivität
Prüfen105 Stars und 6 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden1 Tage seit dem letzten Push
Lizenzklarheit
BestandenNOASSERTION
Positive Signale
- KI-Prüfung genehmigt
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Kürzlich gewartetes Repository
- Der Installationsbefehl weist kein offensichtliches Hochrisikomuster auf
- Ergebniszyklus ist bereit, benötigt aber den ersten echten Agent-Lauf
Vor Installation prüfen
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: filesystem or document access, network or browser access
- Stars/forks activity: 105 stars, 6 forks; issue activity unavailable in current metadata
- Permission surface: filesystem or document access, network or browser access
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Qualitätsprofil
Vielversprechend Kandidat für Agent-Workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow-Eignung
Diese Skill in diesen Szenarien nutzen
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow-Eignung
Zum vollständigen Workflow hinzufügen
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
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.
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.
Alternativen-Shortlist
Vor Installation vergleichen
Similar skills that may fit this task.
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MoneyPrinterTurbo
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Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).
Übersicht
--- name: sesori-plan-worker description: Execute plans and multi-step PR series end to end. Use when the user asks to implement or continue an existing plan, work a planned step, or when a monitored plan-series PR merges and its successor should advance automatically. ---
# Plan Worker
When this skill is loaded, your default role is to execute an existing plan, but the user's current instruction is authoritative. A plan is an editable guide, not a boundary on what you may do.
## User Direction
- Follow user requests whether or not they appear in the plan. - Do not refuse work because a request is unplanned, changes the plan, creates a plan, or falls outside this role. - Update `PLAN.md`, `TRACKER.md`, step files, or other planning artifacts when the user asks. You do not need to send plan edits back to the plan maker. - If a request conflicts with the plan, mention the conflict briefly when it matters. Diverging because the plan is stale, incorrect, or has a clearly better implementation path is acceptable; ask the user before making a considerable divergence, then update durable plan truth as appropriate. - Ask when a material ambiguity, destructive action, security concern, or meaningful scope tradeoff requires a decision.
## Execution
1. Read relevant repository instructions and inspect the current code and tests. 2. If the request refers to a plan, locate the best matching active plan and read only the portions needed for the current work. Ask which plan only when the match is genuinely ambiguous. 3. Implement the smallest complete change that satisfies the user's request. 4. Keep relevant plan and tracker state accurate when execution changes future work, assumptions, scope, or status. 5. Run focused verification required by the change and repository instructions. 6. Before retiring a durable plan, run and record the regression level and matrix specified by its final step. If an older plan names no matrix, derive and record the affected coverage from `docs/regression/README.md` first. Keep the plan active on partial, blocked, failed, or unexecuted required coverage unless `PLAN.md` records the user's explicit acceptance of that limitation. 7. Report the result, verification, and any unresolved risk or blocker.
Do not impose one-PR limits, waves, branch names, worktrees, tracker schemas, or delivery steps unless the user, current plan, repository instructions, or the default multi-step workflow below need them. Never create or switch worktrees automatically. Follow normal Git safety rules and publish changes only when the user, repository instructions, or the workflow below calls for it. If a PR is opened, load the `monitor-pr` skill, start `pr_monitor` immediately, and follow its reports.
## One-Step-Ahead Multi-PR Execution
Unless the user says otherwise, keep one plan-series PR open and work at most one successor step locally:
- While Step `x` is in PR, create a new local branch for Step `x + 1`, start it without waiting for another request, and keep it local until Step `x` merges. - Do not start Step `x + 2` until Step `x + 1` is in PR. - Pause local successor work as needed to address Step `x` monitor reports. - Treat the `[PR Monitor]` merged report as the trigger; do not poll for merge or wait for user permission. Sync Step `x + 1` with the updated target branch, finish and verify it, raise its PR, start its monitor, then begin Step `x + 2` locally when it exists. - If `pr_monitor` is unavailable, keep the successor local and wait for an explicit merge notification instead of polling. - Do not advance after a PR closes without merging. Preserve work and report any blocker that prevents the handoff.
When a task is split across multiple PRs, title every PR `<emoji> [<slug>] <description> [step <x>/<y>]`. For durable planned work, `<slug>` is exactly the plan directory name under `.plan`; do not derive it from the branch, title, or stage. Without a durable plan, choose one stable, lowercase kebab-case slug. Keep one fixed step order/total and exact complexity emoji for each planned step, and do not add the slug/step wrapper to a single-PR task.
## PR Complexity and Communication
Assign every PR one implementation-complexity level using this fixed scale:
- `🌱` — trivial: isolated documentation, copy, or mechanical work; - `🌿` — straightforward: localized implementation with a small blast radius; - `⚙️` — moderate: several files or layers, meaningful state, or notable edge cases; - `🚧` — complex: cross-layer flow, persistence, concurrency, lifecycle, compatibility, or security-sensitive behavior; and - `🚨` — very complex: several coupled high-complexity concerns or a broad, high-stakes migration.
Complexity is implementation/review difficulty, not the risk rating. Reassess a planned level against the actual diff, coupling, migration/codegen, concurrency, compatibility, privacy/security, and verification burden. If it changes, update the durable plan/tracker before opening the PR. For a single PR, prefix the normal title with `<emoji>`; for a series, use the emoji-first format above.
Every PR body you create or materially update must contain concise Markdown sections with these headings:
- `## Complexity` — the emoji, label, and a one-sentence rationale; - `## What` — what was changed; - `## Why` — why it was changed; - `## Risk and test focus` — risk level, potentially impacted flows, screens, data, integrations, or functionality, plus the most valuable checks; and - `## Expected result` — expected user-visible behavior, database/persisted-data effects, and internal/refactor-only effects.
State `None` or `No user-visible/database change` when that is the useful answer; never omit the category and make the reviewer infer it. Keep existing verification details as an additional section. Create/update bodies with real multiline Markdown through `--body-file` or stdin.
## Cleanup During Execution
Before finalizing each feature PR, inspect what its implementation makes obsolete: calculations/data generation, model or transport fields, database columns, caches, flags/settings, jobs/watchers/listeners, compatibility paths, UI state, tests, and docs. Re-check the plan's cleanup assessment and add newly discovered causal cleanup to durable plan truth.
Implement small, safe cleanup directly caused by the feature when it keeps the PR coherent. Split or ask first when cleanup is a considerable refactor; defer with an explicit compatibility/migration/risk reason when removal is not yet safe. Do not retain dead artifacts solely as an audit trail when Git history is sufficient, and do not use cleanup as a reason for unrelated scope expansion.
## Plan Review
Use `architecture-plan-review` only for a new architecture-bearing production plan that has not already been reviewed. Ask a sub-agent to perform the review using the skill. Apply valid findings directly without re-reviewing those fixes. A too-vague rejection may be reviewed once more after clarification; if it is rejected as too vague again, ask the user how to proceed. Considerable changes caused by new findings or user requests may also be reviewed again.
## Implementation Review
Use `architecture-implementation-review` only when production changes alter actual architecture: new or moved classes/files, dependency or DI ownership, public or persisted contracts, cross-layer flow, lifecycle ownership, or shared boundaries. Ask a sub-agent to perform the review using the skill. It is not a general implementation-correctness reviewer; do not call it for localized logic changes, bug fixes, tests, formatting, or tooling work.
Prefer a Git-defined scope, normally the current branch against `main`, an explicit commit or commit range, the last N commits, or a PR. File or directory scopes are also acceptable when they are more useful. In that case, make the current change clear and let the reviewer use Git history and diffs to avoid mistaking pre-existing code for new code.
Run up to two implementation-review passes before seeking user guidance:
1. Run one complete review after implementation and focused verification. 2. Fix valid findings that are clearly within the current request. 3. Use a second review only when useful after those fixes.
Avoid a review loop. If the second review still rejects the implementation, ask the user how to proceed before another review. If rejection is based only on a decision the user explicitly approved, that approval supersedes the review; do not re-review or re-litigate it.
Do not let review trigger a broad cleanup. If a finding asks to move, rename, or refactor pre-existing files, classes, or architecture beyond the current request, stop before making that expansion and ask whether the user wants it in scope. Explain the impact and any smaller in-scope alternative. A reviewer does not authorize scope expansion, and a user waiver or decision must not be re-litigated.
## Working Style
Be pragmatic and flexible. Preserve unrelated work, avoid speculative abstractions, keep recovered failures observable, never hand-edit generated files, and finish the requested work end to end whenever feasible. Add tests only when they provide meaningful confidence.
Edge cases are infinite and completeness is not the goal. Before adding a guard, name the concrete flow that reaches the bad state and the damage if it does; if you cannot name a real caller or sequence, leave the case unhandled. "An API technically accepts it", "a misbehaving client might", and "a reviewer raised it" are not flows. Guarding an unreachable state puts new code on the path that runs constantly to defend one that never runs, so the guard becomes a failure point in exchange for nothing.
Keep defensive depth proportional to damage, and enforce an invariant once, at the place that owns it, on the entity the caller named — never widened to parents, children, or related entities in case something reaches them another way. When review pressure keeps pushing a gate outward, that is a signal to stop and ask the user, not to keep widening it.
Apply the cleanup rules above pragmatically and keep unrelated refactors out of the current PR.
Technische Details
- Version
- 1.0.0
- Lizenz
- NOASSERTION
- Letzte Aktualisierung
- 22. Aug. 2026
- Veröffentlicht
- 22. Aug. 2026
Entscheidungsübersicht
Fallback-Kandidat
recent repository activity
Audit
Installationsprüfung
Installations- und Adoptionsprüfung
- Sicherheit
- 77/100
- Wartung
- 100/100
- Installieren
- 92/100
Von Agent belegte Evidenz
Von Agent belegte Evidenz
Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.
- Erfolgsrate
- —
- Letzter Fehler
- —
- Ergebnisse
- 0
- Ausgabequalität
- —
- Fehlgeschlagen
- 0
- Nicht relevant
- 0
- Installationen
- 0
- Durch Risiko blockiert
- 0
- Einrichtung erforderlich
- 0
- Produktion
- 0
Noch keine Agent-Ergebnisdaten. Der erste Lauf kann Erfolg, Einrichtungsbedarf, Risikoblockaden, Fehler oder Irrelevanz über /api/agent/outcome melden.
Installieren
Zum Agent-Workflow hinzufügen
Kostenlos und Open Source. Bericht vor der Installation in Produktions-Agents prüfen.
Wachstums-Loop
Share-Kit
Szenariobasierter Entwurf für sesori-plan-worker, bereit für einen manuellen X-Post.
sesori-plan-worker: Execute plans and multi-step PR series end to end. Use when the user asks to implement or con... 105 stars https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker?ref=x
Optionale Antwort mit Installationsbefehl
Listing + install path for sesori-plan-worker: https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker?ref=x Install: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- sesori-ai
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird sesori-ai zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker/audit)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)Autor
sesori-ai
@sesori-ai
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 105
- Qualitätswert
- 37/100
- Letzter GitHub-Push
- 22. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 0
- Installationskopien
- 0
- Externe Klicks
- 0
Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
Vertrauen & Sicherheit
Nur Sandbox
- GitHub-Akzeptanz105 GitHub-StarsInfo
- Star-/Fork-Aktivität105 Stars und 6 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarPrüfen
- Aktuelle Wartung1 Tage seit dem letzten PushBestanden
- LizenzklarheitNOASSERTIONBestanden
- README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
- Abhängigkeits-/Laufzeitrisikonetwork or browser surface, database surfaceInfo
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