1d4ffa964d
- README.MD: add original-source-code and nano-claude-code sections, update overview table (4 subprojects), add v3.0 news entry, expand comparison table with memory/multi-agent/skills dimensions - nano-claude-code v3.0: multi-agent package (multi_agent/), memory package (memory/), skill package (skill/) with built-in /commit and /review skills, context compression (compaction.py), tool registry plugin system, diff view, 17 slash commands, 18 built-in tools, 101 tests (~5000 lines total) - original-source-code/src: add raw TypeScript source tree (1884 files) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
"""Skill execution: inline (current conversation) or forked (sub-agent)."""
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from __future__ import annotations
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from typing import Generator
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from .loader import SkillDef, substitute_arguments
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def execute_skill(
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skill: SkillDef,
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args: str,
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state,
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config: dict,
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system_prompt: str,
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) -> Generator:
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"""Execute a skill.
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If skill.context == "fork", runs as an isolated sub-agent and yields its events.
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Otherwise (inline), injects the rendered prompt into the current agent loop.
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Args:
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skill: SkillDef to execute
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args: raw argument string from user (after the trigger word)
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state: AgentState
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config: config dict (may contain _depth, model, etc.)
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system_prompt: current system prompt string
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Yields:
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agent events (TextChunk, ToolStart, ToolEnd, TurnDone, …)
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"""
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rendered = substitute_arguments(skill.prompt, args, skill.arguments)
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message = f"[Skill: {skill.name}]\n\n{rendered}"
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if skill.context == "fork":
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yield from _execute_forked(skill, message, config, system_prompt)
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else:
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yield from _execute_inline(message, state, config, system_prompt)
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def _execute_inline(message: str, state, config: dict, system_prompt: str) -> Generator:
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"""Run skill prompt inline in the current conversation."""
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import agent as _agent
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yield from _agent.run(message, state, config, system_prompt)
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def _execute_forked(
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skill: SkillDef,
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message: str,
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config: dict,
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system_prompt: str,
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) -> Generator:
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"""Run skill as an isolated sub-agent (separate conversation context)."""
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import agent as _agent
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# Build a sub-agent config with depth tracking
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depth = config.get("_depth", 0) + 1
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sub_config = {**config, "_depth": depth, "_system_prompt": system_prompt}
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if skill.model:
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sub_config["model"] = skill.model
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# Restrict tools if skill specifies allowed-tools
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if skill.tools:
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sub_config["_allowed_tools"] = skill.tools
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# Run in fresh state (no shared history)
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sub_state = _agent.AgentState()
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yield from _agent.run(message, sub_state, sub_config, system_prompt)
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