Skill Agent Architect
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Please follow https://skillhub.cn/install/skillhub.md to install @org-02qudk26/architect1.
About this skill
Problem
In Claude Code and Codex ecosystems, skill packages often become too broad, overlap with existing agents, or consume context budgets that make routing brittle. Editing prompts alone usually misses the structural issue: agent failures are often context-architecture failures.
How It Works
Architect treats skill creation and refinement as an engineering workflow:
- CREATE: follows UNDERSTAND → ENVISION → ANALYZE → DESIGN → GENERATE → VALIDATE to produce a complete package with SKILL.md, reference files, capability summaries, collaboration contracts, and explicit input/output boundaries.
- IMPROVE / COMPRESS: scores health and overlap first, then compresses context while preserving behavioral, structural, integration, and routing equivalence.
- EVOLVE: handles self-improvement only through INTROSPECT → DIAGNOSE → PRESCRIBE → MUTATE → VERIFY → PERSIST, with rollback snapshots and budget approvals.
It front-loads capability fit, collaboration boundaries, and topology choices, rather than blaming failures on prompt wording. For multi-agent designs, it checks for formal topology before allowing loosely coupled agent stacks.
Boundaries
This skill is not a replacement for task-chain orchestration, product delivery, or application architecture analysis. If overlap exceeds 30%, compression exceeds 20%, routing changes materially, or Level C self-modification is involved, confirmation is required. Validation, health scoring, and equivalence checks must not be skipped.
Use Cases
- Before adding a code-review skill to Claude Code, run gap analysis, overlap detection, and naming evaluation.
- When a skill is context-heavy, compute token budgets, compress section by section, and verify four-axis equivalence.
- Before wiring agents into Nexus, check input/output partners, routing compatibility, and formal topology to avoid a bag of agents.
- After a major skill redesign, run the 16-item checklist, health score, and rollback snapshot before delivery.
Best For
- Claude Code skill maintainers: want new skills that are verifiable, compressible, and non-overlapping.
- Multi-agent project leads: need to replace loose agent stacks with Nexus-compatible formal topology.
- Platform engineers: need to evaluate context cost, input/output boundaries, and validation checklists.
- AI engineering managers: need to review self-evolution for safety levels, rollback snapshots, and approval budgets.
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