القائمة
<Brief description of what this skill does and when to invoke it. Should be ≤200 characters for clean harness rendering.>
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 | <skill-name> |
| description | <Brief description of what this skill does and when to invoke it. Should be ≤200 characters for clean harness rendering.> |
| license | Proprietary |
| compatibility | agentic-engineers framework v5.10+. Requires Python 3.11+ |
| metadata | {"author":"agentic-engineers","version":"1.0","category":"<category>","role":"<role>","model":"<model>","effort":"<effort>","thinking":false,"dependencies":[],"trigger":"on-demand","tdd_phase":"RED"} |
.
What it does:
Why it matters:
from src.skills.<skill_name> import <SkillClass>
# Initialize and run
skill = <SkillClass>()
result = skill.run(<args>)
print(result)
python src/skills/<skill-name>/scripts/<skill_name>.py \
--<arg1> <value1> \
--<arg2> <value2>
# In .github/workflows/ci.yml:
- name: <Skill Name>
run: python src/skills/<skill-name>/scripts/<skill_name>.py
Input: <What the skill consumes — file paths, environment vars, CLI args> Output: <What the skill produces — report, JSON, exit code, side-effects> Used by: Calls:
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
<param1> | str | ✅ | — | |
<param2> | int | ❌ | 10 | |
<param3> | bool | ❌ | false |
orchestration · validation · monitoring · optimization · observability ·
scaffolding · integration · queue · metrics · maintenance · hygiene · management · security
engineer · senior-engineer · lead-engineer · principal-engineer ·
security-engineer · quality-engineer · orchestrator
| Tier | Model | Recommended for |
|---|---|---|
| Haiku (fast/cheap) | claude-haiku-4.5 | engineer, orchestrator |
| Sonnet (balanced) | claude-sonnet-4.5, claude-sonnet-4.6 | senior, lead, quality |
| Opus (powerful) | claude-opus-4.7, claude-opus-4.8 | principal, security |
| OpenAI | gpt-4o-mini, gpt-4o, gpt-5-mini | special cases |
| Gemini | gemini-3.5-flash, gemini-3.1-pro-preview | special cases |
python -m pytest src/skills/<skill-name>/tests/ -v
# Expected: N tests, M% coverage
scripts/<skill_name>.py — Core implementation entry point---
handoff_type: DELEGATE
task_id: <YYYY-MM-DD-skill-name-task>
timestamp: <ISO8601>
role: <role>
model: <model>
effort: <effort>
scope: >
<What needs to be done — 1–3 sentences>
context:
- <key context item 1>
- <key context item 2>
---
---
handoff_type: HANDBACK
task_id: <YYYY-MM-DD-skill-name-task>
timestamp: <ISO8601>
status: success
deliverables:
- <file or artifact produced>
quality_score: 95
confidence: 0.95
tokens:
used: <N>
efficiency: 0.9
notes: "<What was done and any notable findings>"
---
Experiment orchestration framework with traffic allocation, statistical analysis, and early stopping detection. Use to test routing changes, model upgrades, and role assignments with Welch's t-test significance testing.
DEPRECATED — This skill is no longer maintained. Prometheus and Grafana infrastructure was never implemented. Use local JSON metrics analysis instead.
Scaffolds new SPEC-compliant agentic-engineers agents with a single call. Generates SKILL.md frontmatter, test scaffolds (TDD RED-phase), __init__.py, scripts/ layout, and DELEGATE/HANDBACK protocol templates. Use when creating any new automation agent, task handler, or operational tool. Validates role, model, effort, naming, and dependency graphs (circular dep detection) before writing files. Supports dry-run mode for planning without side effects.
Routine maintenance for Codex sessions: monitor queue state, close completed sub-agents, resume or escalate active work, and keep agent capacity available.
Automated cross-validation of protocol queue integrity. Scans all DELEGATEs/HANDBACKs, validates schema compliance, detects cycles, checks rate limits, generates compliance report. Enables self-referential protocol improvements.
Consolidates provider-specific AI costs into unified metrics across Anthropic, OpenAI, Google Gemini, GitHub Copilot, and Ollama. Enables apples-to-apples cost comparison and savings analysis.