multi-agent-runtime-engineering
multi-agent-runtime-engineering is an Agent runtime & coordination infrastructure skill for AI agents, published by brucesongs in the kali-claw repository on GitHub. Skillspace rates multi-agent-runtime-engineering B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Runtime engineering discipline for agent systems — structured JSON memory schemas, memory-driven convergence rules, shared-memory multi-agent coordination via POSIX flock + atomic write + version vector, anti-pattern prevention, and topology selection. Solidifies the engineering patterns of SCEN-007 (shared-memory multi-agent exploit dev) and SCEN-MEMORY-SCHEMA (structured memory foundation) into a reusable knowledge base. Inspired by MopMonk Agent three招 (扫地僧, CyberGym 73.1%, China
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 39
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.