sesori-plan-worker

Prüfen · 61
Im Registry indexiert

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.

Verified installs0
Stars105
Version1.0.0
Qualität66/100 · Vielversprechend
Vertrauen61/100 · Nur Sandbox
Audit76/100 · Prüfung nötig

Asset-Profil

Coding- und Entwickler-Agents

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

Bereich ansehen

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

CodingGitHub automationautomationagent-skill

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

Vielversprechend
66

Useful candidate, but compare it with alternatives before adopting.

Vertrauen

Nur Sandbox
61

Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.

Audit

Prüfung nötig
76

Maschinenlesbare 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.

CodexClaude CodeCursorOpenAgentSkill CLI

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.

JSON öffnen

Geeignete Aufgaben

  • Workflow-Automatisierung-Workflows
  • Claude-Code-Teams
  • builders willing to evaluate younger projects
  • Move data between tools

Geeignete Agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

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-worker

Nicht 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

ExperimentellPrüfen

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

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

Per API auflösen

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.

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 sesori-ai-sesori-plan-worker

Agent-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.

Textplan öffnen

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.

Installations-API öffnen

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-worker

Registry-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 öffnen

Agent-Fit

65/100

Workflow-Automatisierung

Plattformen

Claude Code

Audit-Bericht

Prüfung nötig · 76/100

Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.

Audit-Bericht ansehenEval-Bericht ansehen

Agent-Entscheidungspanel

Fallback candidate for Workflow automation

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

65
Bereitschaft
Prototyp
Phase

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

  1. 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Workflow-Automatisierung-Aufgabe vollständig aus.
  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.

Vertrauensprofil

Nur Sandbox

Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.

61
OpenAgentSkill Trust Score

GitHub-Akzeptanz

Info

105 GitHub-Stars

Star-/Fork-Aktivität

Prüfen

105 Stars und 6 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar

Aktuelle Wartung

Bestanden

1 Tage seit dem letzten Push

Lizenzklarheit

Bestanden

NOASSERTION

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.

66
GitHub-Stars
105
Aktualität
vor 1 Tagen
Installationsbereit
Ja
Lizenz
NOASSERTION
Vor Installation prüfen: Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.

Workflow-Eignung

Diese Skill in diesen Szenarien nutzen

Workflow-Eignung

Zum vollständigen Workflow hinzufügen

Alternativen-Shortlist

Vor Installation vergleichen

Similar skills that may fit this task.

Alle vergleichen

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

65
Bereit
Prototyp
Phase

recent repository activity

Audit

Installationsprüfung

Installations- und Adoptionsprüfung

76
Prüfung nötig
Sicherheit
77/100
Wartung
100/100
Installieren
92/100
Vollständiges Audit öffnenEval-Bericht ansehen

Von Agent belegte Evidenz

Von Agent belegte Evidenz

Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.

0
Belegt
Needs first agent runAuto-Installation: zuerst prüfenLetzter: Unbekannt
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

X

Szenariobasierter Entwurf für sesori-plan-worker, bereit für einen manuellen X-Post.

Kuratorenhinweis
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
X-Entwurf öffnen
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
Antwortentwurf öffnen

Quelle des Eintrags

Registry-indexiert

Beanspruchbar

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 beanspruchen

Eigentümeranspruch

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.

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

Autor

S

sesori-ai

@sesori-ai

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

61
  • 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