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.
npx agentmods add skills/pipecat-ai/pipecat/docstringnpx skills add pipecat-ai/pipecat --skill docstringgit clone --depth 1 https://github.com/pipecat-ai/pipecatWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00013 | $0.01737 |
| Opus 5 | $0.00006 | $0.00869 |
| Sonnet 5 | $0.00003 | $0.00347 |
| Haiku 4.5 | $0.00001 | $0.00174 |
Grade A, and why
docstring 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 2d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document a Python module or class using Google-style docstrings following project conventions. The argument can be a class name or a module path.
Instructions
-
Determine what to document based on the argument:
If a module path is provided (e.g.
src/pipecat/audio/vad/vad_analyzer.py):- Use that file directly
If a class name is provided (e.g.
VADAnalyzer):- Search for
class ClassNameinsrc/pipecat/ - If multiple files contain that class name, list all matches with their file paths, ask the user which one they want to document, and wait for confirmation
-
Once the file is identified, read the module to understand its structure:
- Identify all classes, functions, and important type aliases
- Understand the purpose of each component
-
Apply documentation in this order:
- Module docstring (at top, after imports)
- Class docstrings
__init__methods (always document constructor parameters)- Public methods (not starting with
_) - Dataclass/config classes with field descriptions
-
Skip documentation for:
- Private methods (starting with
_) - Simple dunder methods (
__str__,__repr__,__post_init__) - Very simple pass-through properties
- Already documented code - If a class, method, or function already has a complete docstring that follows the project style, do not modify it. A docstring is complete if it has:
- A one-line summary
- Args section (if it has parameters)
- Returns section (if it returns something meaningful)
- Only add or improve documentation where it is missing or incomplete
- Private methods (starting with
Module Docstring Format
"""[One-line description of module purpose].
[Optional: Longer explanation of functionality, key classes, or use cases.]
"""
Example:
"""Neuphonic text-to-speech service implementations.
This module provides WebSocket and HTTP-based integrations with Neuphonic's
text-to-speech API for real-time audio synthesis.
"""
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.
- 2d ago First seen · 258 lines · 13 tokens per session scan A 47b935d9881d
docstring is a skill published in the GitHub repository pipecat-ai/pipecat (14,971 stars, last pushed 4d ago), licensed BSD-2-Clause. It adds 13 tokens to every session and 1,737 once invoked, about $0.0001 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 2026-08-30.
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