deep-research
Exa-powered deep research producing an evidence-backed findings.md report. Load for research tasks, architectural investigations, and vendor, library, or technology comparisons.
Profil aset
Agent pemrograman dan pengembangan
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Skenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Kecocokan Agent
Claude Code + OpenAI Agents + Cursor
Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.
Pasang
Siap
npx skills add vanillagreencom/kendex --skill deep-research
Pemeliharaan
Terkini
Diperbarui hari ini
Risiko
Perlu ditinjau
Quality score needs review
Kualitas GitHub
63
65/100 Kualitas · 76/100 Kepercayaan
Tag cakupan
Catatan ulasan
Quality score needs review · GitHub adoption: 63 GitHub stars
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
MenjanjikanUseful candidate, but compare it with alternatives before adopting.
Kepercayaan
Hanya sandboxKandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Audit
Perlu ditinjauTinjauan 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.
Star
63 star GitHub
Aktivitas repositori
63 star dan 23 fork
Pemeliharaan
Diperbarui hari ini
Lisensi
MIT
Pasang
npx skills add vanillagreencom/kendex --skill deep-research
Keamanan pemasangan
Jalur pemasangan paket atau runtime standar
Cakupan izin
shell or command execution, filesystem or document access
Hasil Agent
Belum ada data hasil Agent
Dokumentasi
Konteks README/SKILL.md kuat
Ringkasan risiko
Tinjau sebelum produksi
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 23 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.
Tugas yang sesuai
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
- Sumber pencarian
Agent yang sesuai
Keputusan pemasangan
- Perintah
- npx skills add vanillagreencom/kendex --skill deep-research
- Kebijakan
- Tinjau
- Tinjauan manusia
- Ya
Kepercayaan dan risiko
- Kepercayaan
- 68/100
- Audit
- 79/100
- Tingkat risiko
- Perlu ditinjau
Lingkar hasil
- Endpoint
- /api/agent/outcome
- ID event
- resolve
- Hasil
- 5
Perintah pemasangan
npx skills add vanillagreencom/kendex --skill deep-researchJangan gunakan ketika
- Tim yang membutuhkan SLA dengan dukungan vendor
- Lingkungan berkompliansi tinggi tanpa tinjauan keamanan internal
- No OpenAgentSkill engagement data yet
- Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
- Quality score needs review
Skill alternatif
Last30days Skill
53.5K Star
npx skills add mvanhorn/last30days-skill -g
Skill alternatif
Academic Research Skills
38.4K Star
npx skills add Imbad0202/academic-research-skills
Skill alternatif
GPT Researcher
28.0K Star
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Star
npx skills add Alibaba-NLP/DeepResearch
Keamanan Agent v2
47/100 · Hindari pemasangan otomatis
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Tinggi
Eksekusi shell atau perintah
Metadata skill merujuk terminal, CLI, shell, subprocess, atau alur kerja eksekusi perintah.
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.
- Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
- Quality score needs review
Target pemasangan
Pasang skill ini di alur Agent Anda
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
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 vanillagreencom-deep-researchRencana 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 JSON
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/vanillagreencom-deep-research/install
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 deep-research in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20deep-research%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vanillagreencom-deep-research/install
Install command: npx skills add vanillagreencom/kendex --skill deep-research
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.
Serah-terima pemasangan
/api/skills/vanillagreencom-deep-research/install
Format teks LLM
/api/skills/vanillagreencom-deep-research/install?format=text
Cari alternatif
/api/skills/search?q=deep-research&limit=3
Prompt Agent
Use deep-research for this task. Review https://www.openagentskill.com/api/skills/vanillagreencom-deep-research/install, then install with: npx skills add vanillagreencom/kendex --skill deep-researchMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/vanillagreencom-deep-research
Teks LLM
/api/registry/manifest/vanillagreencom-deep-research?format=text
Alias pemasangan
/api/registry/install/vanillagreencom-deep-research
Rekomendasikan
/api/registry/recommend?task=Use%20deep-research%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
Agent riset
Tag use case
Platform
Claude Code, OpenAI Agents, Cursor
Laporan audit
Perlu ditinjau · 79/100
Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Panel keputusan Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Peran di stack
Kandidat cadangan
Kecocokan utama
Agent riset
Label kepercayaan
Buat prototipe dulu
Jalur pemasangan
Perintah siap
Gunakan saat
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
Bukti
- recent repository activity
- install command or GitHub repo available
- profil kualitas 65/100
tinjau dulu
- No OpenAgentSkill engagement data yet
Jalur implementasi
- 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil kepercayaan
Hanya sandbox
Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Adopsi GitHub
Periksa63 star GitHub
Aktivitas star/fork
Periksa63 star dan 23 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
LulusDiperbarui hari ini
Kejelasan lisensi
LulusMIT
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
- Quality score needs review
- GitHub adoption: 63 GitHub stars
- Stars/forks activity: 63 stars, 23 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.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
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.
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.
Daftar alternatif
Bandingkan sebelum memasang
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Ringkasan
--- name: deep-research description: "Exa-powered deep research producing an evidence-backed findings.md report. Load for research tasks, architectural investigations, and vendor, library, or technology comparisons." license: MIT user-invocable: true argument-hint: "report [query] --output findings.md" dependencies: optional: [decider] metadata: author: vanillagreen source: kendex repository: "https://github.com/vanillagreencom/kendex" bugs: "https://github.com/vanillagreencom/kendex/issues" version: "1.1.0" tags: [research] ---
# Deep Research
> **Problem with this skill?** Run `kendex report` — it files to the owning repo automatically. Do not hand-file.
Evidence-backed research reports: architectural investigations, vendor and library comparisons, technology choices, and workflow-owned `findings.md` reports.
In Pi with the `web_research` tool active, use that tool, passing `outputPath` when creating a report. In every other harness — Pi without it, Claude Code, Codex, OpenCode, Cursor — run `scripts/deep-research` with `EXA_API_KEY` set.
## Rules
- Exa is the research source. Substitute a general web search only when Exa is unavailable and the user approves the fallback. - Write `findings.md` to the path the caller requested, exactly. - Cite sources for material claims, and keep `findings.md` human-readable: provider payloads live in the sidecar JSON (`findings.raw.json` beside the report by default), never inline. Sanitize evidence excerpts so headings from source pages do not render as headings. - Once the report and its sidecar exist, run `validate` and stop. Do not add local reproduction, benchmarks, tests, code inspection, or implementation unless the caller asked for local validation on top of the research. - A missing `EXA_API_KEY` fails with setup instructions. The value may be a key or a 1Password `op://vault/item/field` reference when the `op` CLI is installed and signed in. - One findings format serves every mode: the mode changes depth and source volume, not the required sections. Record mode and source counts in `## Research Metadata`.
## Running
```bash skills/deep-research/scripts/deep-research report "question" --mode standard --output path/to/findings.md skills/deep-research/scripts/deep-research report --query-file prompt.txt --context-glob 'context-*.md' --mode full --output findings.md skills/deep-research/scripts/deep-research json "question" --output raw.json skills/deep-research/scripts/deep-research validate findings.md findings.raw.json skills/deep-research/scripts/deep-research doctor ```
`deep-research help` lists every flag. Exa `/search` caps the settings behind them: `numResults` 1-100, `text.maxCharacters` 1-10000, `additionalQueries` at most 10.
| Mode | Exa type | Results | Text cap | Timeout | Synthesis | |---|---|---:|---:|---:|---| | `lite` | `deep-lite` | 15 | 10k chars/result | 5 min | Not requested — evidence brief only | | `standard` | `deep-reasoning` | 50 | 10k chars/result | 10 min | Requested via `outputSchema` | | `full` | `deep-reasoning` | 100 | 10k chars/result | 30 min | Requested, per query |
`standard` is the default; `lite` suits fast spikes, `full` strategic or high-risk decisions. Explicit `--type`, `--num-results`, and `--text-max-characters` override a mode's defaults.
`--additional-query` (repeatable) reaches Exa as `additionalQueries` within the single request under `lite` and `standard`, and as one request per query with URLs deduped across responses under `full`; the sidecar records which, as `provider-additional-queries` or `local-fan-out`.
`--include-domain` is a hard host filter, not a quality filter: `--include-domain github.com` admits every repo on it and excludes everything else. Name authoritative projects and organizations in the query text when quality is what you want, and audit the returned source list either way.
## Validation
```bash skills/deep-research/scripts/deep-research validate path/to/findings.md path/to/findings.raw.json ```
Prints `{ok, errors, warnings, mode, synthesis, queryCount}` and exits 0 when there are no errors. It checks structure: required sections present, sidecar parses, query-expansion metadata self-consistent, and a synthesized answer present for the modes that requested one.
It cannot judge content. Read for these yourself:
- Claims the cited sources contradict — spot-check material numbers (complexity classes, benchmark results) against the source text in the sidecar. - Off-topic sources that share an acronym or name with the subject. - Recommendations with no claim-level support in Evidence and Sources. - Results generalized past what the source established.
## Findings format
`templates/findings.md` carries exactly the sections `validate` requires, in order. `Key Findings` holds distinct claims, not a restatement of the summary.
Detail teknis
- Versi
- 1.0.0
- Lisensi
- MIT
- Pembaruan terakhir
- 23 Agu 2026
- Diterbitkan
- 23 Agu 2026
Ringkasan keputusan
Kandidat cadangan
recent repository activity
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 83/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- 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
Draf berbasis skenario untuk deep-research, siap untuk posting manual di X.
deep-research: Exa-powered deep research producing an evidence-backed findings.md report. Load for research... 63 stars https://www.openagentskill.com/skills/vanillagreencom-deep-research?ref=x
Balasan opsional dengan perintah pemasangan
Listing + install path for deep-research: https://www.openagentskill.com/skills/vanillagreencom-deep-research?ref=x Install: npx skills add vanillagreencom/kendex --skill deep-research
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- vanillagreencom
- Sumber
- vanillagreencom/kendex
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim pemilik
Klaim listing skill ini
Listing Diindeks Registry ini dikaitkan dengan vanillagreencom, 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.
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research/audit)
[](https://www.openagentskill.com/skills/vanillagreencom-deep-research)Penulis
vanillagreencom
@vanillagreencom
Kecocokan platform
Sinyal kesehatan
- Star GitHub
- 63
- Skor kualitas
- 36/100
- Push GitHub terakhir
- 23 Agu 2026
- Petunjuk framework
- Tidak diketahui
- Tampilan OpenAgentSkill
- 0
- 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
- Adopsi GitHub63 star GitHubPeriksa
- Aktivitas star/fork63 star dan 23 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
- Pemeliharaan terbaruDiperbarui hari iniLulus
- Kejelasan lisensiMITLulus
- Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
- Risiko dependensi/runtimeCakupan eksekusi perintahInfo
Skill terkait
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
53.5K StarAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarGPT Researcher
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28.0K StarDeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
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