parlant: Instructions file for Claude Code

CLAUDE.md

parlant CLAUDE.md is an instructions file for Claude Code from emcie-co/parlant. It costs 611 tokens per session, scanned A, original, Apache-2.0.

A set of coding instructions for the Parlant Python repository, an AI-agent framework for building controlled customer conversations.

In plain words
What is it for?
Use it when adding or reviewing features and tests in the Parlant codebase, especially code organized with separate core and adapter parts.
Why use it?
It helps contributors follow that project's architecture, typing rules, and testing conventions when changing code.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md.

This is emcie-co/parlant's own configuration. It tells Claude Code how to work on parlant itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything parlant configures →

About the project

Parlant is a framework for controlling how customer-facing AI agents use conversational context, rules, knowledge, and tools. It is for teams building consistent, compliant, traceable interactions in consumer and sensitive business settings.

emcie-co/parlant · 18,283 stars · on GitHub · parlant.io

Reuse

Borrowing it

Nothing to install: this file belongs to emcie-co/parlant. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/emcie-co/parlant/develop/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/emcie-co/parlant

Made for: Claude Code.

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Per session 611 This file is loaded in full into every session.
When invoked 611 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00611 $0.00611
Opus 5 $0.00305 $0.00305
Sonnet 5 $0.00122 $0.00122
Haiku 4.5 $0.00061 $0.00061

Measured 9d ago against content hash 3d1abc742592, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

parlant CLAUDE.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 9d 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.

CLAUDE.md · 41 lines

What it actually says

This is the main repo of Parlant (https://parlant.io).

Parlant is a Python based agent framework. Its core strengths:

  1. It allows you to create compliant and controlled AI agents for customer-facing use cases
  2. It provides many conversational management features out of the box
  3. It's built for enterprise, large-scale use cases, where SLAs, stability and security are paramount

The repo's structure follows the Hexagonal Architecture (Ports and Adapters) approach.

  • src/parlant
    • core: Core framework code
    • adapters: Implementations of interfaces using 3rd party tools
    • api: REST API layer using FastAPI. Uses modules from core/
  • tests: all tests for the project. Structure strives to mirror that which is under src/parlant.

General Coding Instructions:

  • Always ensure you stick to Hexagonal Architecture patterns in line with how they're used in this codebase.
  • Every time you add something, look for similar things in the codebase and ensure you follow the coding style.
  • We use MyPy on strict mode. Every parameter needs to be type-annotated. Every function's result too.
  • If you need to add a test for something, first say where you plan to add it and ask for confirmation.
  • We follow TDD. When you make a change, first create a failing test. Once it fails, implement just enough so it passes.
  • If you need to test classes/methods in sdk.py (or generally to test things that relate to engine behavior) make sure you inherit from SDKTest and understand how it works and how to use it.
  • Test names should go "testthat..." using clear names that explain the context, what is executed, and what is the expected result.
  • You can run tests using pytest. Make sure you run "uv run pytest tests/path/to/test/file.py" while also specifying the test name that you need to run.

Always follow this plan when asked to code a feature or fix a bug:

  1. Consider the codebase's structure
  2. Describe your implementation plan, including: a. What tests you will write (test names + files they would live in) b. Why do you think the tests would initially fail c. Where you would plan to implement the code that would make the tests pass
  3. Ask for plan confirmation. If you get feedback, revise your plan and ask for confirmation again until you get it.
  4. Implement the tests first. Ask for confirmation and code review.
  5. Once tests are approved, once again suggest your implementation plan for making them pass, and get plan review until confirmation.
  6. Once your implementation plan is confirmed, go ahead with implementing the code to pass them.
  7. Make sure to format all of the files you changed using ruff (it is installed in the environment).
  8. Run uv run python scripts/lint.py --mypy --ruff to ensure your code has no lint issues.
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. 9d ago First seen · 41 lines · 611 tokens per session scan A 3d1abc742592

Subscribe to this mod's changes

parlant CLAUDE.md is an instructions file published in the GitHub repository emcie-co/parlant (18,283 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 611 tokens to every session, about $0.0031 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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