feat(cli): skill factory — openkb skill new + /skill new + auto marketplace.json

[KylinMountain]

Summary

• New openkb skill new <name> "<prompt>" compiles the wiki into an
  Anthropic-Skills directory at <kb>/output/skills/<name>/.
• New /skill new slash command inside openkb chat — same primitive,
  conversational front end, lets users iterate via natural-language
  follow-ups (chat agent now has Write access to <kb>/output/** +
  <kb>/wiki/explorations/**).
• Auto-regenerated <kb>/.claude-plugin/marketplace.json lists all
  compiled skills; pushing the KB to GitHub makes npx skills@latest add <owner>/<repo> work end-to-end.
• Generator primitive (openkb/generator.py) is architected so future
  ppt / podcast / report targets slot in without restructuring.
• Community contribution path documented (CONTRIBUTING.md +
  skill_submission PR template) — no new CLI surface needed for
  submission.

Architecture

Reuses the existing openai-agents SDK + LiteLLM stack from openkb.agent.query.
The skill-compile agent is constructed via build_skill_compile_agent with
a system prompt from openkb/prompts/skill_compile.md interpolated with
the user's intent + skill name + wiki schema. Tools are scoped: read wiki,
query wiki, write only within <kb>/output/skills/<name>/. Marketplace.json
regenerates synchronously after the agent finishes (no LLM call).

Test plan

• uv run pytest — full suite green (430+ tests)
• CLI command name validation, KB detection, wiki-content gate,
  overwrite logic, marketplace.json regen all covered by unit tests
• Chat /skill new covered by 3 dedicated tests + write_kb_file
  allow-list covered by 9 dedicated tests
• Manual acceptance: run openkb skill new <name> "<intent>" -y
  against a real KB with compiled wiki content, verify the resulting
  output/skills/<name>/SKILL.md activates appropriately in Claude
  Code after cp -r output/skills/<name> ~/.claude/skills/. Spec
  criteria from docs/superpowers/specs/2026-05-18-skill-factory-design.md
  §11 success criteria.
• Iteration: in openkb chat, run /skill new, then ask the
  agent to tweak the description or a references/ file; verify the
  file actually changes on disk.

Spec: docs/superpowers/specs/2026-05-18-skill-factory-design.md (gitignored locally; design notes in PR review)

[KylinMountain]

Code review

Found 1 issue:

1. MaxTurnsExceeded is not caught — agent hitting MAX_TURNS = 80 produces an unhandled traceback instead of a friendly error. MaxTurnsExceeded inherits from AgentsException, not RuntimeError, but both call sites (CLI and chat) only catch RuntimeError. Either widen the catch to Exception (or AgentsException + RuntimeError), or have run_skill_compile translate the SDK exception into a RuntimeError with a clear message.

OpenKB/openkb/agent/skill_compiler.py

Lines 124 to 131 in 7467200

	# Single user message kicks off the compile. The system prompt already
	# contains the intent — this just nudges the agent to start.
	seed = (
	f"Compile the skill '{skill_name}'. Follow the system prompt's "
	f"working method. Read the wiki, then write the skill files."
	)
	await Runner.run(agent, seed, max_turns=MAX_TURNS)

Call sites that catch only RuntimeError:

OpenKB/openkb/cli.py

Lines 1490 to 1495 in 7467200

	kb_dir=kb_dir,
	model=model,
	)
	asyncio.run(gen.run())
	except RuntimeError as exc:
	click.echo(f"[ERROR] {exc}", err=True)

OpenKB/openkb/agent/chat.py

Lines 540 to 546 in 7467200

	# Load model from KB config
	from openkb.config import load_config, DEFAULT_CONFIG
	config = load_config(kb_dir / ".openkb" / "config.yaml")
	model = config.get("model", DEFAULT_CONFIG["model"])
	from openkb.generator import Generator
	_fmt(style, ("class:slash.help", f"Compiling skill '{name}'...\n"))

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[quanqigu]

Code review (round 2, on commits 7467200..a5fe567)

Found 1 issue:

1. skill eval re-introduces the MaxTurnsExceeded/JSONDecodeError traceback leak that round 1 caught for skill new — openkb/cli.py:skill_eval only catches RuntimeError, but run_eval calls Runner.run (raises MaxTurnsExceeded, an AgentsException, not RuntimeError) and json.loads on LLM output (raises JSONDecodeError, a ValueError, not RuntimeError). Same bug class fixed in skill_creator.run_skill_create by translating SDK exceptions to RuntimeError; skill_evaluator needs the same shim, or the CLI catch must widen to Exception.

https://github.com/VectifyAI/OpenKB/blob/a5fe567c34a4ed5e1c0c842a6ed35a5d8d6cb01f/openkb/cli.py#L1771-L1781

https://github.com/VectifyAI/OpenKB/blob/a5fe567c34a4ed5e1c0c842a6ed35a5d8d6cb01f/openkb/skill_evaluator.py#L120-L135

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