Laporan audit skill
research-proposal Laporan audit.
Use when the user has a research proposal (problem + proposed methodology + planned experiments) and wants it iteratively strengthened until it clears a passing grade. ScholarEval grades the proposal against the literature (Soundness + Contribution), a Judge scores that feedback 0-100 on a fixed rubric, and a Reviser rewrites the proposal to fix the worst points without diluting the research question; loops until the grade passes or the budget is hit. Not for generating a proposal from scratch, and not for running a literature survey on its own.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopsi GitHub
Info62
163 star GitHub
Aktivitas star/fork
Peringatan57
163 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Info76
4 bulan sejak push
Kejelasan lisensi
Lulus86
MIT
Kelengkapan README/SKILL.md
Lulus86
Metadata memuat konteks penggunaan dan alur kerja yang cukup
Risiko dependensi/runtime
Info64
credential or environment access, network or browser surface
Ketersediaan pemasangan
Lulus92
npx skills add gaasher/Agent-Loop-Skills --skill research-proposal
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Gagal34
secrets or environment access, filesystem or document access
Bukti repositori
Lulus86
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/research-proposal
Status peninjauan
Info66
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add gaasher/Agent-Loop-Skills --skill research-proposal
Repositori
88
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/research-proposal
Lisensi
86
MIT
Pemeliharaan
76
4 bulan sejak push
Tinjauan AI
55
The skill instructs agents to retrieve and use literature content, but does not explicitly warn against prompt injection from retrieved web pages or paper snippets. A malicious source could attempt to steer agent behavior.
Kelengkapan README/SKILL.md
86
Usable description available
Risiko dependensi
64
credential or environment access, network or browser surface
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
34
secrets or environment access, filesystem or document access
Aktivitas star/fork
57
163 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
68
163 star GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Peringatan
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- The skill instructs agents to retrieve and use literature content, but does not explicitly warn against prompt injection from retrieved web pages or paper snippets. A malicious source could attempt to steer agent behavior.
- The skill relies on executing an external Python script (`lit_search.py`) and WebFetch fallbacks; there is no explicit sandboxing or validation of the script path or downloaded content.
- The SKILL.md is long and dense; some users may need more concrete examples of the full loop execution to avoid misconfiguration.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, filesystem or document access
- Stars/forks activity: 163 stars, 19 forks; issue activity unavailable in current metadata
- Permission surface: secrets or environment access, filesystem or document access
Metode
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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