القائمة
company-kb — Company Knowledge Base Skill. Use when relevant to this domain.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | company-kb |
| description | company-kb — Company Knowledge Base Skill. Use when relevant to this domain. |
| domain | core |
| tags | ["company","infrastructure","memory","self-improvement"] |
| persona | {"name":"Domain Expert","title":"Master of Company Kb","expertise":["Core Excellence","Best Practices","Professional Standards"],"philosophy":"Excellence is not a skill, it's an attitude.","credentials":["Industry leader","Practiced professional","Thought leader"],"principles":["Quality first","Continuous improvement","Evidence-based","Customer focused"]} |
Trigger phrases:
"company kb"
"User asks about company info, procedures, history, products, team"
"Agent needs to look up internal documentation"
"Storing new company knowledge for future recall"
User asks about company info, procedures, history, products, team
Agent needs to look up internal documentation
Storing new company knowledge for future recall
Paijo asks about anything related to BerkahKarya operations
Company Kb is a foundational core infrastructure skill that provides system foundation capabilities for the agent ecosystem.
| Rationalization | Reality |
|---|---|
| "I will add monitoring later" | Without monitoring, you cannot detect failures. Add it from day one. |
| "One model is enough" | Different tasks need different models. Route intelligently. |
| "Premature optimization" | Infrastructure decisions are hard to change later. Design for scale early. |
# Example: Model routing
ROUTES = {
"code": ["claude-sonnet-4-20250514", "gpt-4o"],
"vision": ["gemini-2.5-pro", "gpt-4o"],
"fast": ["gemini-2.5-flash", "gpt-4o-mini"],
}
def route_request(task: str, prompt: str):
models = ROUTES.get(task, ROUTES["fast"])
for model in models:
try:
return call_model(model, prompt)
except Exception:
continue
raise RuntimeError("All models failed")
Enforce staged execution discipline on large tasks: written stage plan, parallel sub-agent delegation, failable verification at each stage, and skeptical self-review before delivery. Use when tasks span multiple files, multiple sources, or multiple sessions. Also triggers on "do this thoroughly", "be systematic", "deep work mode", "be thorough".
Write production-quality code from specs — reads requirements, researches patterns, implements with tests, and iterates until verification passes. Use when implementing features, fixing bugs with known root causes, or building new modules.
Ship code to production through a controlled pipeline with verification gates and rollback plans. Use when deploying features, managing CI/CD, running database migrations, or performing post-incident hotfix recovery.
Investigate topics deeply with cross-referenced sources and produce evidence-backed findings. Use when evaluating technologies before adoption, analyzing competitors, or investigating bug root causes across docs and issues.
Read code changes with adversarial intent to find bugs, security holes, logic errors, and performance traps. Use when reviewing PRs, auditing refactoring for regressions, or running pre-deploy safety checks.
Detect and fix code style violations, enforce project conventions, and ensure consistent formatting across the codebase. Use when cleaning lint errors before PRs, migrating linters, or bulk-applying new rules.