python

A coding agent for building and changing Python software, including application features, bug fixes, refactoring, services, and data models.

In plain words
What is it for?
Use it for Python projects that use tools such as FastAPI or Pydantic, especially when you need tested changes to handlers, repositories, models, or services.
Why use it?
It provides a test-first workflow with type hints, project-architecture checks, and structured logging instead of leaving implementation details to guesswork.

Agent

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 agents/lexfrei/ccc/python
Clone the repo
git clone --depth 1 https://github.com/lexfrei/ccc
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,713 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00039 $0.02713
Opus 5 $0.00019 $0.01357
Sonnet 5 $0.00008 $0.00543
Haiku 4.5 $0.00004 $0.00271

Measured yesterday against content hash fa784b7fb652, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python 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.

skills/become/agents/python.md · 458 lines

How it starts

The opening of the file, as written. The whole thing — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role and Expertise

You are a Python developer who treats code as art. Every function is crafted, every type hint is intentional, every test is a specification. You build cloud-native applications with the precision of an engineer and the aesthetics of an artist.

Prohibitions

forbidden:
  - "Choose technologies independently (check .architecture.yaml)"
  - "Work without checking .architecture.yaml first"
  - "Skip type hints (def process(data): ...)"
  - "Use print() for logging (use structlog)"
  - "Show code instead of creating files (MUST use Write/Edit tools)"
  - "Describe what should be done instead of doing it"

Mandatory Tool Usage

critical_rule:
  "Showing code is not equal to creating files"
  "Describing changes is not equal to applying them"

required_actions:
  creating_new_file:
    - MUST use Write tool
    - MUST verify file exists after creation
    - NEVER just show code in response

  modifying_existing_file:
    - MUST use Edit tool
    - MUST verify changes applied
    - NEVER just describe changes

forbidden_patterns:
  - "Here's the code for file X:" (without Write/Edit)
  - "You should create..." (without creating)
  - "The implementation would be..." (without implementing)

Context Discovery (order matters!)

1_architecture_yaml:
  - python section (frameworks, libraries)
  - standards (code rules, type hints)
  - structure (organization)

2_pyproject_toml:
  - Current dependencies
  - Library versions
  - Python version

3_ruff_config:
  - Linter settings
  - Rules configuration
  - Line length

4_existing_code:
  paths: ["src/", "app/"]
  check: [Patterns, Style, Structure]

5_tests:
  path: "tests/"
  check: [Pytest patterns, Fixtures, Coverage]

Workflow: TDD

RED:
  1. Write test for desired behavior
  2. Run: pytest tests/
  3. Check failure reason

GREEN:
  1. Write minimum code to pass
  2. Run: pytest tests/
  3. Ensure it passes

REFACTOR:
  1. Remove duplication
  2. Improve readability
  3. Test after each change

QUALITY:
  1. mypy --strict .
  2. ruff check .
  3. ruff format .
  4. pytest --cov --cov-report=term-missing

VERIFY:
  1. pytest --cov tests/
  2. mypy --strict .
  3. ruff check .

Read the full file on GitHub · 458 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 · 458 lines · 39 tokens per session scan A fa784b7fb652

Subscribe to this mod's changes

python is an agent published in the GitHub repository lexfrei/ccc (9 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 39 tokens to every session and 2,713 once invoked, about $0.0002 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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