# ─── Add these sections to your OpenClaw AGENTS.md ───
#
# Paste them at the end of ~/.openclaw/workspace/AGENTS.md (or wherever
# your AGENTS.md lives). The agent reads AGENTS.md at session start and
# will follow these instructions automatically.
#
# REQUIREMENTS:
#   - Build the ACE-extended Docker image (see Dockerfile.ace)
#   - Pass your LLM API key through docker-compose environment:
#
#       environment:
#         ACE_MODEL: "bedrock/us.anthropic.claude-sonnet-4-20250514-v1:0"
#         # Pick ONE of these depending on your provider:
#         AWS_BEARER_TOKEN_BEDROCK: ${AWS_BEARER_TOKEN_BEDROCK}
#         ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY}
#         OPENROUTER_API_KEY: ${OPENROUTER_API_KEY}
#         LITELLM_API_KEY: ${LITELLM_API_KEY}

## Auto-Learning

At the start of each session, before responding to the user's first message,
run:

    ace-learn

After it completes, report the results to the user. Include:
- How many new sessions were processed
- How many new strategies were added (and their IDs)
- Total strategy count in the skillbook

Example:

> **ACE Learning Report**
> Processed 2 new sessions (6 total, 4 previously processed).
> Added 3 new strategies: `error_handling-00005`, `code_style-00008`,
> `debugging-00003`. Skillbook now contains 14 strategies.

If there were no new sessions, report that briefly:

> **ACE:** No new sessions to learn from. Skillbook has 14 strategies loaded.

If the command fails, tell the user that auto-learning failed and suggest they
check their API key configuration, then continue normally.
If `ace-learn` is not found, tell the user ACE is not installed and continue.

### On-demand learning

If the user asks to "learn from this session" (or similar), process only the
current session's transcript:

    ace-learn <path-to-current-session.jsonl>

Find the current session file in `~/.openclaw/agents/main/sessions/` (it will
be the most recently modified `.jsonl` file). Report what was learned using the
same format as above.

Do **not** reprocess all sessions — only the current one.

## Learned Strategies

After running `ace-learn`, read the file `skills/kayba-ace/ace_skillbook.md`
into your context. This file contains strategies learned from past sessions.

**Important:** You must explicitly read the file — markdown links are not
auto-inlined. Use your file-reading tools to load the full content.

When a strategy is relevant to the current task:

1. Apply it.
2. Cite the strategy ID (e.g. `conversation_style-00003`) so the user can
   trace which learned behaviour influenced the response.