improve-agent

Improve an Agent

Read first, change second. Diagnose from real data, propose the smallest fix, and never write without explicit approval.

Before you start

• Call list_scenarios to resolve the Agent. Config tools require EDITOR-or-above on that Agent; if the user lacks it, say so and stop.
• Ask whether to PROPOSE changes only (default) or also APPLY approved ones.

Diagnose

1. get_assistant_settings — persona, profession, creativity, greeting, language, reply length, KB descriptions.
2. list_knowledge_base_articles — what the Agent already knows.
3. get_insights plus a list_conversations sample read with get_conversation_detail to find where it struggled. Classify with references/failure-taxonomy.md.

Propose

For each recurring problem, propose the SMALLEST change that fixes it:

• Missing knowledge -> a new KB article (draft the exact text).
• Wrong tone/persona -> a specific personality (an enum id, not a scale) or an ai_commands guideline.
• Too long / short / robotic -> reply_length or creativity_level. Present proposals as a before -> after diff, then STOP for approval.

Apply (only after approval)

• update_assistant_settings — pass ONLY the fields that change; effective immediately, no retrain.
• add_knowledge_base_article — content required; embedded automatically in the background, no retrain.
• After each write, re-read with get_assistant_settings / list_knowledge_base_articles and confirm the change landed.

Guardrails

• Never call a write tool before the user approves that specific change.
• personality and similar fields are enum ids — use the ids from the tool schema, not free text.
• Some fields (e.g. ai_commands) need a plan feature; if a write is rejected for that reason, report it plainly instead of retrying.

Output

A short report: top issues (ranked, one example each), the proposed changes as a diff, and — if you applied any — a confirmation of what changed.