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.

Eksperimental · TinjauPerlu ditinjauDihasilkan 11 Okt 2026Audit metadata heuristik
79
Audit
76
Kepercayaan
69
Kualitas
82
Keamanan
88
Maintain
92
Pasang

Trust Score OpenAgentSkill

76
Shortlist kuat

Trust Score OpenAgentSkill

The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.

Adopsi GitHub

Info

62

357 star GitHub

Aktivitas star/fork

Peringatan

57

357 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

88

1 bulan sejak push

Kejelasan lisensi

Lulus

86

MIT

Kelengkapan README/SKILL.md

Lulus

86

Metadata memuat konteks penggunaan dan alur kerja yang cukup

Risiko dependensi/runtime

Info

64

credential or environment access, database surface

Ketersediaan pemasangan

Lulus

92

npx skills add agentsope/SkillAlchemy --skill agentsop-bounded-loop

Keamanan perintah pemasangan

Lulus

92

Jalur pemasangan paket atau runtime standar

Cakupan izin

Info

62

secrets or environment access, database access

Bukti repositori

Lulus

86

https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-bounded-loop

Status peninjauan

Lulus

88

Data tinjauan AI tersedia

Hasil terbukti Agent

Info

54

Belum ada data hasil Agent

Pemeriksaan

Tinjauan pemasangan dan adopsi

7 Lulus · 5 Perlu ditinjau

Jalur pemasangan

92

Lulus

npx skills add agentsope/SkillAlchemy --skill agentsop-bounded-loop

Repositori

88

Lulus

https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-bounded-loop

Lisensi

86

Lulus

MIT

Pemeliharaan

88

Lulus

1 bulan sejak push

Tinjauan AI

88

Lulus

Approved with no listed issues

Kelengkapan README/SKILL.md

86

Lulus

Usable description available

Risiko dependensi

64

Periksa

credential or environment access, database surface

Keamanan perintah pemasangan

92

Lulus

Jalur pemasangan paket atau runtime standar

Cakupan izin

62

Periksa

secrets or environment access, database access

Aktivitas star/fork

57

Perbaiki

357 star dan 19 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Adopsi

68

Info

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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