---
id: "169511ec-2ef2-4a9d-901f-cf71faba472a"
name: standard-release-process-8890d4557b09
description: "General SOP for common requests related to space, india, mathematics."
version: "0.1.3"
tags:
  - "space"
  - "india"
  - "mathematics"
  - "antenna"
  - "wi"
  - "fi"
  - "lavender"
  - "it"
  - "used"
  - "economy"
  - "economic"
  - "that"
triggers:
  - "Use when the user asks for a process or checklist."
  - "Use when you want to reuse a previously mentioned method/SOP."
examples:
  - input: "Break this into best-practice, executable steps."
---

# Standard release process

General SOP for common requests related to space, india, mathematics.

## Prompt

Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>):
1) Offline OpenAI-format conversation source.
2) Title: a3f4c42a82286d328d2fd1d4add07c95.json#conv_1
3) Use the user questions below as the PRIMARY extraction evidence.
4) Use the full conversation below as SECONDARY context reference.
5) In the full conversation section, assistant/model replies are reference-only and not skill evidence.
6) Primary User Questions (main evidence):
7) what the interesting stories last 2 year that a YouTube video can be made on that
8) what the interesting stories last 2 year in india  that a YouTube video can be made on that
9) The tensions between India and China on the border in Ladakh and political and economic implications of the conflict.
10) hey I have bachelor in math and I want to pursue in space tech what should I pursue and from where

For each step, include: action, checks, and failure rollback/fallback plan.
Output format: for each step number, provide status/result and what to do next.

## Triggers

- Use when the user asks for a process or checklist.
- Use when you want to reuse a previously mentioned method/SOP.

## Examples

### Example 1

Input:

  Break this into best-practice, executable steps.


---
Source attribution: ECNU-ICALK
Original project: https://github.com/ECNU-ICALK/AutoSkill
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: ECNU-ICALK
Original project: https://github.com/ECNU-ICALK/AutoSkill
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Education & Research, Project & Program Management
Roles: Data Analyst, Project Manager, Researcher
Specialties: Specialty not specified
Tools: Tool not specified
Country applicability: India
Classification basis: Source catalog labels
Instruction SHA-256: 67cd1f859e25181977b199b6eb2a1fc26a695731e4487b6c55458d84ea548cf2