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Open-ended skill learning across every surface. /learn <free text> takes a description of any source — a directory, a URL, the workflow you just walked the agent through, or pasted notes — and the live agent gathers it with the tools it already has (read_file/search_files, web_extract, the conversation, the pasted text), then authors a SKILL.md via skill_manage following the house authoring standards (<=60-char description, the standard section order, Hermes-tool framing, no invented commands). No engine, no model-tool footprint, works on any terminal backend (local, Docker, remote): /learn builds a standards-guided prompt and hands it to the agent as a normal turn. - agent/learn_prompt.py: shared standards-guided prompt builder - /learn registry entry (both surfaces) + CLI handler (inject onto input queue) + gateway handler (rewrite turn, fall through, /blueprint pattern) - tui_gateway command.dispatch returns a send directive -> TUI + dashboard chat - dashboard Skills page 'Learn a skill' panel (dir + URL + open-ended text) composes a /learn request and runs it in chat - docs (slash-commands ref + skills feature page), 11 targeted tests Inspired by OpenAI Codex's Record & Replay and the /learn concept from #47234 (dir-distillation engine); reworked to be open-ended and engine-free per review.
73 lines
2.9 KiB
Python
73 lines
2.9 KiB
Python
"""Tests for /learn — open-ended skill distillation.
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Covers the shared prompt builder (agent.learn_prompt.build_learn_prompt) and
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the slash-command registry wiring. /learn has no engine and no model tool: it
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builds a standards-guided prompt that the live agent runs as a normal turn, so
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these are the load-bearing behavior contracts.
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"""
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from agent.learn_prompt import build_learn_prompt, _AUTHORING_STANDARDS
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class TestBuildLearnPrompt:
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def test_embeds_the_user_request_verbatim(self):
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req = "the REST client in ~/projects/acme-sdk, focus on auth"
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prompt = build_learn_prompt(req)
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assert req in prompt
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def test_always_includes_the_authoring_standards(self):
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# The standards are what make distilled skills match house style;
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# they must travel with every prompt regardless of input.
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for req in ["", "a url https://x/y", "what we just did"]:
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assert _AUTHORING_STANDARDS in build_learn_prompt(req)
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def test_instructs_saving_via_skill_manage_not_a_raw_file(self):
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prompt = build_learn_prompt("learn the thing")
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assert "skill_manage" in prompt
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def test_references_gather_tools_for_open_ended_sourcing(self):
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# Open-ended sourcing relies on the agent's own tools, named so it
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# knows dirs/URLs/conversation/paste all route through existing tools.
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prompt = build_learn_prompt("learn from somewhere")
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for tool in ("read_file", "search_files", "web_extract"):
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assert tool in prompt
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def test_empty_request_falls_back_to_the_conversation(self):
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# Bare /learn should distill "what we just did", not error.
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prompt = build_learn_prompt("")
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assert "conversation" in prompt.lower()
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# And still carries the standards + save instruction.
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assert "skill_manage" in prompt
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def test_whitespace_only_request_is_treated_as_empty(self):
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assert build_learn_prompt(" \n ") == build_learn_prompt("")
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def test_description_length_rule_is_in_the_standards(self):
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# The single most-violated rule must be explicit in the prompt.
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assert "60" in _AUTHORING_STANDARDS
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class TestLearnRegistryWiring:
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def test_learn_is_registered_and_resolves(self):
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from hermes_cli.commands import resolve_command
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cmd = resolve_command("learn")
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assert cmd is not None
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assert cmd.name == "learn"
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def test_learn_is_in_tools_and_skills_category(self):
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from hermes_cli.commands import resolve_command
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assert resolve_command("learn").category == "Tools & Skills"
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def test_learn_works_on_the_gateway(self):
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# /learn must reach the gateway runner (it's a both-surfaces command),
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# not be CLI-only.
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from hermes_cli.commands import GATEWAY_KNOWN_COMMANDS
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assert "learn" in GATEWAY_KNOWN_COMMANDS
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def test_learn_is_not_cli_only(self):
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from hermes_cli.commands import resolve_command
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assert not resolve_command("learn").cli_only
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