linkedin.asisaga.com python.instructions.md

A set of Python coding rules covering formatting, type annotations, documentation, and asynchronous code, where tasks can run without blocking each other.

In plain words
What is it for?
Use it to guide Python workflows, function signatures, docstrings, async operations, and pytest-asyncio configuration.
Why use it?
It gives contributors consistent expectations for writing and reviewing Python code, especially code that uses asynchronous SDK calls.

Instructions file for GitHub Copilot

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/asisaga/linkedin.asisaga.com/python
Clone the repo
git clone --depth 1 https://github.com/ASISaga/linkedin.asisaga.com

Made for: GitHub Copilot.

Per session 737 This file is loaded in full into every session.
When invoked 737 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00737 $0.00737
Opus 5 $0.00368 $0.00368
Sonnet 5 $0.00147 $0.00147
Haiku 4.5 $0.00074 $0.00074

Measured yesterday against content hash 77ec2a6e1b80, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linkedin.asisaga.com python.instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/instructions/python.instructions.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Coding Standards

Style & Formatting

  • Follow PEP 8 conventions (4-space indentation, 88-char line limit)
  • Use type hints on all function signatures (-> dict, List[str], etc.)
  • Use from __future__ import annotations at the top of each module
  • Write Google-style docstrings for public functions and classes
  • Use double-quoted strings consistently

Async Patterns

All workflows are async functions using await:

@app.workflow("workflow-name")
async def my_workflow(request: WorkflowRequest) -> Dict[str, Any]:
    agents = await request.client.list_agents()
    status = await request.client.start_orchestration(...)
    return {"orchestration_id": status.orchestration_id, "status": status.status.value}
  • Always await SDK calls — they are all coroutines
  • Use asyncio_mode = "auto" (configured in pyproject.toml) for pytest-asyncio
  • Avoid blocking I/O in async functions

Type Hints

from typing import Any, Dict, List, Callable

async def select_c_suite_agents(client: AOSClient) -> List[AgentDescriptor]: ...
async def my_workflow(request: WorkflowRequest) -> Dict[str, Any]: ...
  • Use Dict, List, Any from typing for Python 3.10 compatibility
  • Use Callable[[ArgType], ReturnType] for function parameters

Imports

Order: stdlib → third-party → local, with blank lines between groups:

from __future__ import annotations

import logging
from typing import Any, Dict, List

from aos_client import AOSApp, WorkflowRequest

Logging

Use the module-level logger — never use print():

logger = logging.getLogger(__name__)
logger.info("Orchestration started: %s", orchestration_id)

Error Handling

Raise ValueError with descriptive messages when required agents are unavailable:

if not agent_ids:
    raise ValueError("No matching agents available in the catalog")

Testing

pip install -e ".[dev]"
pytest tests/ -v                              # Run all tests
pytest tests/ -v -k "test_name"              # Run specific test
pylint src/                                   # Lint

Read the full file on GitHub · 104 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 104 lines · 737 tokens per session scan A 77ec2a6e1b80

Subscribe to this mod's changes

linkedin.asisaga.com python.instructions.md is an instructions file published in the GitHub repository ASISaga/linkedin.asisaga.com (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 737 tokens to every session, about $0.0037 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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