agentleFS
Sign inStart free
0xOpCode0xOpCode/tele-harness/.agents/skills/create-db-schema/SKILL.md

create-db-schema

Skill1 starsChanged 49 days agoMITView on GitHub

Generates and updates database schemas for Telegram bot data models.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Follow these constraints when creating or updating database schemas:

    line 9
  2. Distinctive:

    Add cascade rules for user data deletion upon bot block updates.

    line 24

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Database Schema Protocol

Follow these constraints when creating or updating database schemas:

  1. Stack Alignment: Match the database tool specified in [TECH_STACK] and bot_manifest.md (e.g., PostgreSQL + Prisma, PostgreSQL + SQLAlchemy, SQLite + Peewee, Redis).
  2. Base User Model:
    • telegram_id: BigInt primary key or unique index. Telegram user IDs exceed 32-bit integers.
    • username: Nullable string.
    • first_name: String.
    • language_code: String, default 'en'.
    • created_at: Timestamp UTC.
  3. Session and FSM Model (if persistent FSM required):
    • key: Composite index (chat_id, user_id).
    • state: String representation of active node.
    • data: JSON field for conversational payload.
  4. Relations:
    • Index telegram_id across all foreign key relationships.
    • Add cascade rules for user data deletion upon bot block updates.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free