Laporan audit skill
agentsop-bounded-loop Laporan audit.
Universal discipline for any LM-driven loop — agent retries, plan-act-observe, multi-agent handoffs, optimiser passes, test-fix cycles. Encodes the one rule every framework documents quietly and every team relearns expensively: the LM in the loop is NEVER a reliable terminator. Termination must be provided by an explicit counter + exit predicate + stagnation signal + escalation path that live OUTSIDE the LM's control. This is a tool- level, framework-agnostic skill. It maps onto LangGraph (recursion_limit + state counter + interrupt), CrewAI (max_iter + max_rpm + human_input), Claude / OpenAI SDKs (max_iterations + tool_use_budget), DSPy (declared evaluation budget), Aider (REPL + explicit retry cap), and AutoGen (max_consecutive_auto_reply). Search keywords: infinite loop, recursion limit, recursion_limit, GraphRecursionError, max iterations, max_iter, agent stuck, agent won't stop, runaway agent, ReAct loop not terminating, agent repeating itself.
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
357 star GitHub
Aktivitas star/fork
Peringatan57
357 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus88
1 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, database surface
Ketersediaan pemasangan
Lulus92
npx skills add agentsope/SkillAlchemy --skill agentsop-bounded-loop
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Info62
secrets or environment access, database access
Bukti repositori
Lulus86
https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-bounded-loop
Status peninjauan
Lulus88
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add agentsope/SkillAlchemy --skill agentsop-bounded-loop
Repositori
88
https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-bounded-loop
Lisensi
86
MIT
Pemeliharaan
88
1 bulan sejak push
Tinjauan AI
88
Approved with no listed issues
Kelengkapan README/SKILL.md
86
Usable description available
Risiko dependensi
64
credential or environment access, database surface
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
62
secrets or environment access, database access
Aktivitas star/fork
57
357 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
68
357 star GitHub
Peringatan
- Quality score needs review
- Stars/forks activity: 357 stars, 19 forks; issue activity unavailable in current metadata
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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