sesori-plan-maker

Tinjau · 67
Diindeks di Registry

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
Star105
Versi1.0.0
Kualitas67/100 · Menjanjikan
Kepercayaan67/100 · Hanya sandbox
Audit79/100 · Perlu ditinjau

Profil aset

Agent pemrograman dan pengembangan

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

Lihat kategori

Skenario

Agent pemrograman

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

Kecocokan Agent

Claude Code + CLI + Codex

Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.

Pasang

Siap

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

Pemeliharaan

Terkini

Diperbarui hari ini

Risiko

Perlu ditinjau

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

Kualitas GitHub

105

67/100 Kualitas · 75/100 Kepercayaan

Tag cakupan

CodingAgent pemrogramanAgent pemrogramanagent-skill

Catatan ulasan

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

Kartu adopsi Agent

Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat

Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.

Kualitas

Menjanjikan
67

Useful candidate, but compare it with alternatives before adopting.

Kepercayaan

Hanya sandbox
67

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

Audit

Perlu ditinjau
79

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Trust Score OpenAgentSkill v5

Tinjauan manusia sebelum pemasangan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

CodexClaude CodeCursorOpenAgentSkill CLI

Star

105 star GitHub

Aktivitas repositori

105 star dan 6 fork

Pemeliharaan

Diperbarui hari ini

Lisensi

NOASSERTION

Pasang

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

Keamanan pemasangan

Jalur pemasangan paket atau runtime standar

Cakupan izin

filesystem or document access, database access

Hasil Agent

Belum ada data hasil Agent

Dokumentasi

Konteks README/SKILL.md kuat

Ringkasan risiko

Tinjau sebelum produksi

  • 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

Kesiapan pemasangan

Jalur pemasangan tersedia

  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Lisensi dinyatakan
  • Belum ada bukti hasil Agent-Proven

Metadata yang dapat dibaca Agent

Data keputusan yang dapat dibaca mesin untuk skill ini.

Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.

Buka JSON

Tugas yang sesuai

  • alur kerja Agent pemrograman
  • Tim Claude Code
  • builders willing to evaluate younger projects
  • Inspect source files

Agent yang sesuai

CodexClaude CodeCursorOpenAgentSkill CLICLI

Keputusan pemasangan

Perintah
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-maker
Kebijakan
Tinjau
Tinjauan manusia
Ya

Kepercayaan dan risiko

Kepercayaan
67/100
Audit
79/100
Tingkat risiko
Perlu ditinjau

Lingkar hasil

Endpoint
/api/agent/outcome
ID event
resolve
Hasil
5

Perintah pemasangan

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

Jangan gunakan ketika

  • Tim yang membutuhkan SLA dengan dukungan vendor
  • 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

Keamanan Agent v2

59/100 · Tinjau sebelum memasang

Ditinjau dengan catatan izinTinjau

Kandidat yang dapat digunakan, tetapi Agent harus menampilkan catatan izin dan audit sebelum memasang.

Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.

Selesaikan via API

Sedang

Akses jaringan

Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.

Sedang

Akses sistem file

Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.

Sedang

Akses database

Skill dapat memeriksa skema, mengkueri database, atau bekerja dengan penyimpanan persisten.

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

Target pemasangan

Pasang skill ini di alur Agent Anda

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

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

Rencana resolusi Agent

Biarkan Agent memverifikasi kecocokan sebelum memasang.

API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.

Buka rencana teks

Agent harus memeriksa

  • 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.

Salin prompt

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.

Serah-terima Agent

Berikan jalur pemasangan kepada Agent, bukan direktori lain.

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

Buka API pemasangan

Prompt Agent

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

Metadata Registry

Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka Manifest

Kecocokan Agent

67/100

Agent pemrograman

Platform

Claude Code

Laporan audit

Perlu ditinjau · 79/100

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Lihat laporan auditLihat laporan evaluasi

Panel keputusan Agent

Fallback candidate for Coding agents

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

67
Kesiapan
Prototipe
Tahap

Peran di stack

Kandidat cadangan

Kecocokan utama

Agent pemrograman

Label kepercayaan

Buat prototipe dulu

Jalur pemasangan

Perintah siap

Gunakan saat

  • alur kerja Agent pemrograman
  • Tim Claude Code
  • builders willing to evaluate younger projects

Bukti

  • recent repository activity
  • install command or GitHub repo available
  • profil kualitas 67/100
  • 2 event interaksi OpenAgentSkill

tinjau dulu

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

Jalur implementasi

  1. 1Pasang di Agent sandbox dan jalankan satu tugas Agent pemrograman dari awal hingga akhir.
  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.

Profil kepercayaan

Hanya sandbox

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

67
Trust Score OpenAgentSkill

Adopsi GitHub

Info

105 star GitHub

Aktivitas star/fork

Periksa

105 star dan 6 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

Diperbarui hari ini

Kejelasan lisensi

Lulus

NOASSERTION

Sinyal positif

  • Tinjauan AI disetujui
  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Repositori yang baru dipelihara
  • Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
  • Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama

Tinjau sebelum memasang

  • 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
  • Belum ada laporan hasil Agent nyata
  • Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan

Tindakan yang disarankan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

Profil kualitas

Menjanjikan kandidat untuk alur kerja Agent

Useful candidate, but compare it with alternatives before adopting.

67
Star GitHub
105
Keterkinian
Hari ini
Siap dipasang
Ya
Lisensi
NOASSERTION
Tinjau sebelum memasang: Repository license is detected as NOASSERTION, meaning no clear open-source license is identified. This creates ambiguity about usage and redistribution rights.

Kecocokan alur kerja

Gunakan skill ini pada skenario berikut

Kecocokan alur kerja

Tambahkan ke alur kerja lengkap

Daftar alternatif

Bandingkan sebelum memasang

Similar skills that may fit this task.

Bandingkan semua

Ringkasan

--- 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

Detail teknis

Versi
1.0.0
Lisensi
NOASSERTION
Pembaruan terakhir
23 Agu 2026
Diterbitkan
23 Agu 2026

Ringkasan keputusan

Kandidat cadangan

67
Siap
Prototipe
Tahap

recent repository activity

Audit

Tinjauan pemasangan

Tinjauan pemasangan dan adopsi

79
Perlu ditinjau
Keamanan
80/100
Pemeliharaan
100/100
Pasang
92/100
Buka audit lengkapLihat laporan evaluasi

Bukti tervalidasi Agent

Bukti tervalidasi Agent

Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.

0
Terbukti
Needs first agent runPasang otomatis: tinjau duluTerakhir: Tidak diketahui
Tingkat sukses
Kegagalan terbaru
Hasil
0
Kualitas output
Gagal
0
Tidak relevan
0
Pemasangan
0
Diblokir risiko
0
Perlu penyiapan
0
Produksi
0

Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.

Pasang

Tambahkan ke alur Agent

Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.

Siklus pertumbuhan

Kit berbagi

X

Draf berbasis skenario untuk sesori-plan-maker, siap untuk posting manual di X.

Catatan kurator
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
Buka draf X
Balasan opsional dengan perintah pemasangan
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
Buka draf balasan

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator
sesori-ai
Diindeks oleh
Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan sesori-ai, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![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)

Penulis

S

sesori-ai

@sesori-ai

Kecocokan platform

Sinyal kesehatan

Star GitHub
105
Skor kualitas
37/100
Push GitHub terakhir
23 Agu 2026
Petunjuk framework
Tidak diketahui
Tampilan OpenAgentSkill
2
Salinan pemasangan
0
Klik keluar
0

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.

Kepercayaan & keamanan

Hanya sandbox

67
  • Adopsi GitHub105 star GitHubInfo
  • Aktivitas star/fork105 star dan 6 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
  • Pemeliharaan terbaruDiperbarui hari iniLulus
  • Kejelasan lisensiNOASSERTIONLulus
  • Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
  • Risiko dependensi/runtimedatabase surfaceLulus