Edit the lead agent's system prompt with discipline. Use when the user says "the agent is being too X", "tell the agent to Y", "the prompt needs a rule about Z", or before adding any new rule to the system prompt. The system prompt is at `backend/packages/harness/deerflow/agents/lead_agent/prompt.py` (a single function that returns a `ChatPromptTemplate`). Use this skill BEFORE making the change; the skill walks through the change-and-validate cycle. Triggers on phrases like "edit the agent prompt", "add a rule to the lead agent", "system prompt", "AGENT_MANIFEST", or before merging any change touching `agents/lead_agent/prompt.py`.
Installation
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Edit the lead agent's system prompt with discipline. Use when the user says "the agent is being too X", "tell the agent to Y", "the prompt needs a rule about Z", or before adding any new rule to the system prompt. The system prompt is at `backend/packages/harness/deerflow/agents/lead_agent/prompt.py` (a single function that returns a `ChatPromptTemplate`). Use this skill BEFORE making the change; the skill walks through the change-and-validate cycle. Triggers on phrases like "edit the agent prompt", "add a rule to the lead agent", "system prompt", "AGENT_MANIFEST", or before merging any change touching `agents/lead_agent/prompt.py`.
nova-prompt-author
The change-and-validate cycle
Read the current prompt:wc -l backend/packages/harness/deerflow/agents/lead_agent/prompt.py (should be 500+ lines). Identify the section you're changing (e.g., <skill_persistence>, <command_arsenal>, <self_verify>, etc.).
Find or create the test:backend/tests/test_lead_agent_prompt.py (exists per the audit's test inventory). Add a regression assertion: e.g., "the prompt contains <rule>no ENOENT hunts</rule>" so the rule is enforced by the test, not just the prompt.
Update the prompt. Constraints (per FORK_V5.md hard rules):
Use literal paths (no {...} braces) — braces break .format() (the prompt is .format()-templated).
Keep <system-reminder> blocks separate from the static prompt — they're injected at runtime, not at template time.
Don't reference deprecated/removed tools (e.g., cowork, the v6 namespace).
Don't duplicate the <agent_manifest> content — the manifest is injected separately.
Re-run replay E2E:cd backend && PYTHONPATH=. uv run pytest tests/test_replay_golden.py -v. The fixture should still match — if it doesn't, your prompt change drifted the agent graph semantics.
Update the test for the new rule so it actually exercises it (not just asserts the rule exists).
Anti-patterns
❌ Don't add import statements to the prompt file — it's a function returning a ChatPromptTemplate, not a module.
❌ Don't add a rule without a corresponding test. The rule lives in the prompt; the test lives in the code. Both must move together.
❌ Don't make the prompt > 2000 lines. Larger prompts slow the agent and dilute the most important rules.
❌ Don't reference tool names that are loaded via assemble_deferred_tools — those are HIDDEN from the model until promoted. If you mention tool_search in the prompt, the agent won't find the tool by its deferred name; it finds it via the <available-deferred-tools> block.
❌ Don't reword rules without re-running the replay E2E. The fixture is the contract.
