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How to turn on long-term memory and skill evolution for a recurring topic with Poirot

Set the advanced feature flags so Poirot remembers past findings and improves its skills.

Short answer: Set up the project with pip install -e ".[dev]" after creating a virtual environment, as in the Quick Start; then copy the sample config with cp .env.example .env and set DEEPSEEK_API_KEY; add the memory variables POIROT_MEMORY_USE=default, POIROT_MEMORY_PHASE2_ENABLED=true, and POIROT_MEMORY_PHASE2_TURNS=10 to .env. All steps.

  • Research
  • Intermediate
  • 45 minutes
  • From the README
  • Any agent

Who it is forA researcher who returns to the same subject over many sessions and wants earlier findings reused.

The problemEach new research session starts from zero, so earlier findings and working methods get lost.

The outcomeA Poirot setup with memory recall, auto-consolidation, and skill evolution enabled in .env.

What you need first

  • Python 3.12 or newer
  • A DeepSeek API key (the README says to set DEEPSEEK_API_KEY in .env)
  • Git and a terminal
  • Docker only if you want the container sandbox

Steps

  1. Set up the project with pip install -e ".[dev]" after creating a virtual environment, as in the Quick Start.
  2. Copy the sample config with cp .env.example .env and set DEEPSEEK_API_KEY.
  3. Add the memory variables POIROT_MEMORY_USE=default, POIROT_MEMORY_PHASE2_ENABLED=true, and POIROT_MEMORY_PHASE2_TURNS=10 to .env.
  4. Add the skill variables POIROT_SKILL_ENABLED=true, POIROT_SKILL_EVOLVE_ENABLED=true, and POIROT_SKILL_EVAL_ENABLED=true to .env.
  5. Start Poirot with poirot, ask a research question on your topic, then type /skill search to browse skills.

Prompt for your agent

In the Poirot repo at <path to poirot checkout>, add the memory and skill variables from the README's Enable Advanced Features block to .env, then run `poirot` on the topic <topic>. Expected output: a session where memory recall and skill injection are active. Verify that the variables are set in .env before launching.

Caveat. The README lists these flags as optional advanced features and sends full configuration details to USAGE.md, so confirm the behavior there before relying on it.

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