sesori-plan-maker

Prüfen · 67
Im Registry indexiert

Create or update practical, code-informed plans and trackers. Use ONLY when the user explicitly asks to make or change a plan or tracker. It may also self-invoke while planning a new feature, larger refactor, or other large effort that would benefit from multiple steps or PR spli

Verified installs0
Stars105
Version1.0.0
Qualität67/100 · Vielversprechend
Vertrauen67/100 · Nur Sandbox
Audit79/100 · Prüfung nötig

Asset-Profil

Coding- und Entwickler-Agents

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

Bereich ansehen

Szenario

Coding-Agents

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

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-maker

Wartung

Aktuell

Heute gepusht

Risiko

Prüfung nötig

Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.

GitHub-Qualität

105

67/100 Qualität · 75/100 Vertrauen

Abdeckungs-Tags

CodingCoding-AgentsCoding-Agentsagent-skill

Review-Notizen

Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights. · Quality score needs review

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
67

Useful candidate, but compare it with alternatives before adopting.

Vertrauen

Nur Sandbox
67

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

Audit

Prüfung nötig
79

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

Heute gepusht

Lizenz

NOASSERTION

Installieren

npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-maker

Installationssicherheit

Standard-Paket- oder Laufzeit-Installationspfad

Berechtigungsfläche

filesystem or document access, database access

Agent-Ergebnisse

Noch keine Agent-Ergebnisdaten

Dokumentation

Starker README/SKILL.md-Kontext

Risikoübersicht

Vor Produktion prüfen

  • Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.
  • Quality score needs review
  • Stars/forks activity: 105 stars, 6 forks; issue activity unavailable in current metadata

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

  • Coding-Agents-Workflows
  • Claude-Code-Teams
  • builders willing to evaluate younger projects
  • Inspect source files

Geeignete Agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Installationsentscheidung

Befehl
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-maker
Richtlinie
Prüfen
Menschliche Prüfung
Ja

Vertrauen und Risiko

Vertrauen
67/100
Audit
79/100
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-maker

Nicht verwenden, wenn

  • Teams, die ein vom Anbieter unterstütztes SLA benötigen
  • production agents without a repository review
  • Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.
  • Quality score needs review
  • Stars/forks activity: 105 stars, 6 forks; issue activity unavailable in current metadata

Agent-Sicherheit v2

59/100 · Vor Installation prüfen

Mit Berechtigungshinweisen geprüftPrüfen

Nutzbarer Kandidat, aber der Agent sollte Berechtigungs- und Auditnotizen vor der Installation anzeigen.

Vor der Installation in einem echten Arbeitsbereich ist menschliche Freigabe erforderlich.

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.

  • Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.

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-maker

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-maker in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sesori-plan-maker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-maker/install
Install command: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-maker
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-maker for this task. Review https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-maker/install, then install with: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-maker

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

67/100

Coding-Agents

Plattformen

Claude Code

Audit-Bericht

Prüfung nötig · 79/100

Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.

Audit-Bericht ansehenEval-Bericht ansehen

Agent-Entscheidungspanel

Fallback candidate for Coding agents

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

67
Bereitschaft
Prototyp
Phase

Rolle im Stack

Fallback-Kandidat

Primäre Eignung

Coding-Agents

Vertrauenslabel

Zuerst prototypisieren

Installationspfad

Befehl bereit

Verwenden wenn

  • Coding-Agents-Workflows
  • Claude-Code-Teams
  • builders willing to evaluate younger projects

Evidenz

  • recent repository activity
  • install command or GitHub repo available
  • Qualitätsprofil 67/100
  • 2 OpenAgentSkill-Interaktionen

zuerst prüfen

  • Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.

Implementierungspfad

  1. 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Coding-Agents-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.

67
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

Heute gepusht

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 detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.
  • Quality score needs review
  • Stars/forks activity: 105 stars, 6 forks; issue activity unavailable in current metadata
  • 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.

67
GitHub-Stars
105
Aktualität
Heute
Installationsbereit
Ja
Lizenz
NOASSERTION
Vor Installation prüfen: Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.

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-maker description: Create or update practical, code-informed plans and trackers. Use ONLY when the user explicitly asks to make or change a plan or tracker. It may also self-invoke while planning a new feature, larger refactor, or other large effort that would benefit from multiple steps or PR splits. Do not self-invoke for routine implementation, small fixes, or ordinary single-step work. ---

# Plan Maker

When this skill is loaded, turn a user's goal into a practical implementation plan grounded in the current codebase. Keep the process proportional to the work. Prefer a short useful plan over a large planning system.

## User Direction

The user has final authority. Do not reject a request merely because it is not planning work or is outside this skill's usual duty.

If a request is clearly outside planning and the user has not already acknowledged that, say so briefly and ask once whether they want you to proceed. If they confirm, or if they already explicitly told you to proceed despite the planning context, do the work without questioning the choice again. This includes implementation, tests, configuration, Git tasks, and plan updates when permitted by the active environment.

Follow the user's latest explicit instruction when it conflicts with an older plan or process preference. Explain concrete risks when useful, but do not use the role, a plan, or a reviewer as a reason to overrule a confirmed decision.

## Planning

- Inspect relevant repository instructions, code, tests, history, and external references before making assumptions. - Ask only questions that materially affect the result and cannot be answered from available context. Avoid exhaustive interviews and arbitrary checklists. - Make scope, current behavior, proposed changes, ownership/data flow, important compatibility concerns, and verification concrete enough to implement. - Scale detail to the task. A small change may need only a concise plan in chat; a multi-step effort may benefit from durable files under `.plan/active/<slug>/`. - When updating an existing plan, preserve its useful structure rather than forcing a new schema. Keep its tracker or execution state in sync when needed. - Do not invent stages, waves, PR boundaries, worktrees, or process artifacts unless they help the current work or the user asks for them. - When intentionally splitting any task across multiple PRs, require every PR title to use `<emoji> [<slug>] <description> [step <x>/<y>]`. For durable planned work, `<slug>` is exactly the plan directory name under `.plan`; do not invent a separate series slug. Without a durable plan, choose one stable, lowercase kebab-case slug. Fix the step order/total for the whole series, including each step's complexity emoji, and do not apply the slug/step wrapper to a single-PR task. - Target no more than 1,500 changed lines per PR as a soft cap, counting additions plus deletions, generated code, and tests. Prefer a coherent split before exceeding it; when a smaller independently valid PR is not practical, record the reason for the expected overage in the plan. - For durable planned work, the first PR step always raises the plan under `.plan/active/<slug>/` before implementation begins. The penultimate step reconciles and completes the affected feature documents under `docs/regression/`. The final step runs the level and matrix already recorded in `PLAN.md`, records the result, and retires the plan by moving it to `.plan/completed/<slug>/` only after that coverage passes. Include all three lifecycle steps in the fixed step total.

For a new durable plan, `PLAN.md` should normally capture the goal, scope, relevant current behavior, concrete implementation steps, verification, and material risks or decisions. Add a lightweight `TRACKER.md` or step files only when they will help execution.

The plan must identify affected regression feature documents, the highest coverage level needed for the delivered behavior, and any required plugin, platform, client, packaged, or external-service matrix. Follow the proof-boundary and retirement rules in `docs/regression/README.md`; choose enough coverage to prove every materially delivered behavior through its complete authoritative boundary, never a lower level merely because it is cheaper. Any reduction to the recorded matrix requires explicit user acceptance in `PLAN.md` before retirement.

## Evidence And Proportionality

### Prefer Elegant, Low-State Designs

- Before adding persistence or coordination, inspect existing fields, event shapes, and relevant Git history. Reuse a semantically adequate signal and narrow the product claim when needed rather than duplicating state solely to manufacture perfect provenance for a low-impact heuristic. - Treat every new mutable field, map, queue, registry, timer, subscription, dedupe set, pending state, and lifecycle hook as a new failure point with an ongoing maintenance cost. Count mutable parts explicitly before accepting a design, not only changed lines or PR size. - First find the narrowest existing owner that already knows the authoritative outcome. Prefer one post-success write at that seam over reconstructing intent later from events, payload shapes, timing, or backend-specific classifiers. - A backend-neutral behavior should not require custom production logic in each plugin unless the behavior genuinely depends on backend semantics. If a plan touches every plugin to infer the same product fact, treat that as a design alarm: look for a bridge-core action or normalized contract that already owns the fact, or narrow the promised behavior. - Prefer an honest product limitation over machinery that guesses unobservable provenance. Supporting fewer authoritative flows cleanly is better than claiming broad support through dedupe caches, correlation state, reconnect reconciliation, and plugin-specific heuristics. - Before finalizing a plan, include a complexity budget: name the new persistent and in-memory mutable parts, justify each one, and state which tempting pieces are deliberately not being added. If the feature's coordination machinery is larger than its primary behavior, redesign or ask the user before proceeding. - When review feedback adds mutable coordination one edge case at a time, stop and reconsider the root seam instead of accumulating guards. Do not let a sequence of locally valid findings turn a simple behavior change into a state machine without explicit user approval.

- Classify each planned safeguard as addressing an observed failure, an ordinary reachable user flow, or a theoretical interleaving. A reviewer suggestion or a test that can synthetically force a race is not by itself product evidence. - Before adding coordination, state the concrete flow, user/data consequence, and what happens if nothing changes. Account for existing ordering, retries, recovery, idempotency, and refresh behavior instead of assuming every transient state must be made impossible. - Require observed evidence or a plausible ordinary flow with meaningful impact before adding locks, lanes, registries, provisional states, lifecycle owners, compatibility paths, or exhaustive cross-repository filtering. Explicitly accept bounded transient or self-healing behavior when its impact is minor. - Prefer the coarsest simple mechanism that preserves the required invariant. Do not add per-resource concurrency, parallelism, or bypass closure when a small serialized domain boundary is sufficient and throughput is unproven. - Treat cross-cutting coordination as a scope alarm. If an unobserved safeguard grows into shared state across several owners/layers, materially exceeds its estimate, or becomes comparable in size to the primary feature, stop and ask the user whether that risk justifies the complexity before planning or applying more fixes. - Re-run this proportionality check when architecture review or PR feedback expands scope. Apply findings that protect the approved core behavior, but do not treat architectural completeness as a reason to implement increasingly defensive machinery around a low-impact theoretical edge. - For durable plans, record both the evidence level and any intentionally accepted risk. This keeps later reviewers from reopening a declined theoretical concern without new evidence.

## PR Complexity and Communication

Assign every planned or opened PR one implementation-complexity level represented by its fixed emoji:

- `🌱` — 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 describes implementation and review difficulty, not risk by itself. Choose it from the actual coupling, state transitions, migration/codegen, concurrency, compatibility, privacy/security, and verification burden; do not rate every PR in a series identically by default.

For a single-PR task, prefix the normal title with `<emoji>`. For a multi-PR task, place the emoji first: `<emoji> [<slug>] <description> [step <x>/<y>]`. Treat the emoji as part of the fixed exact title. If implementation evidence changes the estimate before the PR opens, update the plan/tracker title rather than knowingly publishing a stale rating.

Make every planned PR concrete enough that its eventual PR body can briefly and clearly state:

- **Complexity:** level plus a one-sentence rationale; - **What:** what the PR changes; - **Why:** why that change is needed now; - **Risk and test focus:** risk level, potentially impacted flows, screens, data, integrations, or functionality, and the highest-value checks; and - **Expected result:** what a reviewer should observe after running it, explicitly covering user-visible behavior, persisted/database changes, and pure internal/refactor effects as applicable.

Use an explicit `None` or `No user-visible/database change` rather than omitting a category. Keep these summaries proportional; they are an operational review aid, not a duplicate design document.

Whenever you create or materially update a PR yourself, render those categories as `## Complexity`, `## What`, `## Why`, `## Risk and test focus`, and `## Expected result`, followed by the relevant verification section. Use real multiline Markdown through `--body-file` or stdin.

## Cleanup Assessment

For every feature plan, actively inspect what the new behavior makes obsolete. Consider calculations and data generation, model fields, database columns, transport fields, caches, flags/settings, jobs/watchers/listeners, compatibility paths, UI state, tests, and documentation. Look for causal cleanup such as data that no longer needs to be generated, persisted, transported, or rendered.

Record one honest outcome in the plan:

- include small, safe, directly caused cleanup in the appropriate feature PR; - place a larger but valuable cleanup in its own coherent planned PR; - defer cleanup when migration, compatibility, rollout, or risk requires it and state the reason; or - state that no relevant cleanup was found.

Do not keep obsolete artifacts solely for auditing when Git history already preserves them. Cleanup is still not permission for speculative scope growth: preserve required wire/data compatibility, and explain approximate size and ask the user before planning a considerable refactor.

## Plan Review

Use `architecture-plan-review` only for architecture-bearing production plans, as defined by repository instructions. Ask a sub-agent to perform the review using the skill. Apply valid findings directly and do

Technische Details

Version
1.0.0
Lizenz
NOASSERTION
Letzte Aktualisierung
23. Aug. 2026
Veröffentlicht
23. Aug. 2026

Entscheidungsübersicht

Fallback-Kandidat

67
Bereit
Prototyp
Phase

recent repository activity

Audit

Installationsprüfung

Installations- und Adoptionsprüfung

79
Prüfung nötig
Sicherheit
80/100
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-maker, bereit für einen manuellen X-Post.

Kuratorenhinweis
sesori-plan-maker: Create or update practical, code-informed plans and trackers. Use ONLY when the user explicit...

105 stars

https://www.openagentskill.com/skills/sesori-ai-sesori-plan-maker?ref=x
X-Entwurf öffnen
Optionale Antwort mit Installationsbefehl
Listing + install path for sesori-plan-maker:
https://www.openagentskill.com/skills/sesori-ai-sesori-plan-maker?ref=x

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

Autor

S

sesori-ai

@sesori-ai

Plattform-Fit

Gesundheitssignale

GitHub-Stars
105
Qualitätswert
37/100
Letzter GitHub-Push
23. Aug. 2026
Framework-Hinweise
Unbekannt
OpenAgentSkill-Aufrufe
2
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

67
  • GitHub-Akzeptanz105 GitHub-StarsInfo
  • Star-/Fork-Aktivität105 Stars und 6 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarPrüfen
  • Aktuelle WartungHeute gepushtBestanden
  • LizenzklarheitNOASSERTIONBestanden
  • README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
  • Abhängigkeits-/Laufzeitrisikodatabase surfaceBestanden