7966560fb5
Adds a public reload path for the in-process skill caches so newly installed (or removed) skills become visible mid-session without a gateway restart. Mirrors the shape of /reload-mcp. Three surfaces: * /reload-skills slash command — CLI (cli.py) and gateway (gateway/run.py), with /reload_skills alias for Telegram autocomplete and an explicit Discord registration. * skills_reload agent tool (tools/skills_tool.py) — lets agents/subagents pick up freshly-installed skills via tool call. * agent.skill_commands.reload_skills() — shared helper that clears _skill_commands, _SKILLS_PROMPT_CACHE (in-process LRU), and the on-disk .skills_prompt_snapshot.json, then returns an added/removed diff plus the new total count. Tested: * tests/agent/test_skill_commands_reload.py (9 cases) * tests/cli/test_cli_reload_skills.py (3 cases) * tests/gateway/test_reload_skills_command.py (4 cases) Use case: NemoClaw / OpenShell-style sandboxed orchestrators that drop skills into ~/.hermes/skills mid-session, plus agentic flows where the agent itself installs a skill via the shell tool and needs it bound without a gateway restart. The Python helper clear_skills_system_prompt_cache(clear_snapshot=True) already exists internally — this PR just exposes it via slash command and tool.
450 lines
17 KiB
Python
450 lines
17 KiB
Python
"""Shared slash command helpers for skills.
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Shared between CLI (cli.py) and gateway (gateway/run.py) so both surfaces
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can invoke skills via /skill-name commands.
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"""
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import json
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import logging
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import re
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from pathlib import Path
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from typing import Any, Dict, Optional
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from hermes_constants import display_hermes_home
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from agent.skill_preprocessing import (
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expand_inline_shell as _expand_inline_shell,
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load_skills_config as _load_skills_config,
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substitute_template_vars as _substitute_template_vars,
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)
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logger = logging.getLogger(__name__)
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_skill_commands: Dict[str, Dict[str, Any]] = {}
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# Patterns for sanitizing skill names into clean hyphen-separated slugs.
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_SKILL_INVALID_CHARS = re.compile(r"[^a-z0-9-]")
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_SKILL_MULTI_HYPHEN = re.compile(r"-{2,}")
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def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tuple[dict[str, Any], Path | None, str] | None:
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"""Load a skill by name/path and return (loaded_payload, skill_dir, display_name)."""
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raw_identifier = (skill_identifier or "").strip()
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if not raw_identifier:
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return None
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try:
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from tools.skills_tool import SKILLS_DIR, skill_view
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identifier_path = Path(raw_identifier).expanduser()
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if identifier_path.is_absolute():
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try:
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normalized = str(identifier_path.resolve().relative_to(SKILLS_DIR.resolve()))
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except Exception:
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normalized = raw_identifier
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else:
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normalized = raw_identifier.lstrip("/")
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loaded_skill = json.loads(
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skill_view(normalized, task_id=task_id, preprocess=False)
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)
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except Exception:
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return None
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if not loaded_skill.get("success"):
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return None
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skill_name = str(loaded_skill.get("name") or normalized)
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skill_path = str(loaded_skill.get("path") or "")
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skill_dir = None
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# Prefer the absolute skill_dir returned by skill_view() — this is
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# correct for both local and external skills. Fall back to the old
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# SKILLS_DIR-relative reconstruction only when skill_dir is absent
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# (e.g. legacy skill_view responses).
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abs_skill_dir = loaded_skill.get("skill_dir")
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if abs_skill_dir:
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skill_dir = Path(abs_skill_dir)
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elif skill_path:
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try:
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skill_dir = SKILLS_DIR / Path(skill_path).parent
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except Exception:
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skill_dir = None
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return loaded_skill, skill_dir, skill_name
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def _inject_skill_config(loaded_skill: dict[str, Any], parts: list[str]) -> None:
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"""Resolve and inject skill-declared config values into the message parts.
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If the loaded skill's frontmatter declares ``metadata.hermes.config``
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entries, their current values (from config.yaml or defaults) are appended
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as a ``[Skill config: ...]`` block so the agent knows the configured values
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without needing to read config.yaml itself.
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"""
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try:
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from agent.skill_utils import (
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extract_skill_config_vars,
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parse_frontmatter,
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resolve_skill_config_values,
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)
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# The loaded_skill dict contains the raw content which includes frontmatter
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raw_content = str(loaded_skill.get("raw_content") or loaded_skill.get("content") or "")
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if not raw_content:
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return
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frontmatter, _ = parse_frontmatter(raw_content)
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config_vars = extract_skill_config_vars(frontmatter)
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if not config_vars:
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return
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resolved = resolve_skill_config_values(config_vars)
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if not resolved:
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return
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lines = ["", f"[Skill config (from {display_hermes_home()}/config.yaml):"]
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for key, value in resolved.items():
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display_val = str(value) if value else "(not set)"
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lines.append(f" {key} = {display_val}")
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lines.append("]")
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parts.extend(lines)
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except Exception:
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pass # Non-critical — skill still loads without config injection
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def _build_skill_message(
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loaded_skill: dict[str, Any],
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skill_dir: Path | None,
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activation_note: str,
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user_instruction: str = "",
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runtime_note: str = "",
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session_id: str | None = None,
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) -> str:
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"""Format a loaded skill into a user/system message payload."""
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from tools.skills_tool import SKILLS_DIR
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content = str(loaded_skill.get("content") or "")
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# ── Template substitution and inline-shell expansion ──
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# Done before anything else so downstream blocks (setup notes,
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# supporting-file hints) see the expanded content.
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skills_cfg = _load_skills_config()
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if skills_cfg.get("template_vars", True):
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content = _substitute_template_vars(content, skill_dir, session_id)
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if skills_cfg.get("inline_shell", False):
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timeout = int(skills_cfg.get("inline_shell_timeout", 10) or 10)
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content = _expand_inline_shell(content, skill_dir, timeout)
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parts = [activation_note, "", content.strip()]
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# ── Inject the absolute skill directory so the agent can reference
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# bundled scripts without an extra skill_view() round-trip. ──
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if skill_dir:
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parts.append("")
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parts.append(f"[Skill directory: {skill_dir}]")
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parts.append(
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"Resolve any relative paths in this skill (e.g. `scripts/foo.js`, "
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"`templates/config.yaml`) against that directory, then run them "
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"with the terminal tool using the absolute path."
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)
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# ── Inject resolved skill config values ──
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_inject_skill_config(loaded_skill, parts)
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if loaded_skill.get("setup_skipped"):
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parts.extend(
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[
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"",
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"[Skill setup note: Required environment setup was skipped. Continue loading the skill and explain any reduced functionality if it matters.]",
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]
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)
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elif loaded_skill.get("gateway_setup_hint"):
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parts.extend(
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[
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"",
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f"[Skill setup note: {loaded_skill['gateway_setup_hint']}]",
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]
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)
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elif loaded_skill.get("setup_needed") and loaded_skill.get("setup_note"):
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parts.extend(
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[
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"",
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f"[Skill setup note: {loaded_skill['setup_note']}]",
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]
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)
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supporting = []
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linked_files = loaded_skill.get("linked_files") or {}
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for entries in linked_files.values():
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if isinstance(entries, list):
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supporting.extend(entries)
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if not supporting and skill_dir:
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for subdir in ("references", "templates", "scripts", "assets"):
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subdir_path = skill_dir / subdir
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if subdir_path.exists():
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for f in sorted(subdir_path.rglob("*")):
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if f.is_file() and not f.is_symlink():
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rel = str(f.relative_to(skill_dir))
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supporting.append(rel)
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if supporting and skill_dir:
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try:
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skill_view_target = str(skill_dir.relative_to(SKILLS_DIR))
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except ValueError:
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# Skill is from an external dir — use the skill name instead
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skill_view_target = skill_dir.name
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parts.append("")
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parts.append("[This skill has supporting files:]")
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for sf in supporting:
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parts.append(f"- {sf} -> {skill_dir / sf}")
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parts.append(
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f'\nLoad any of these with skill_view(name="{skill_view_target}", '
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f'file_path="<path>"), or run scripts directly by absolute path '
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f"(e.g. `node {skill_dir}/scripts/foo.js`)."
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)
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if user_instruction:
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parts.append("")
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parts.append(f"The user has provided the following instruction alongside the skill invocation: {user_instruction}")
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if runtime_note:
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parts.append("")
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parts.append(f"[Runtime note: {runtime_note}]")
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return "\n".join(parts)
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def scan_skill_commands() -> Dict[str, Dict[str, Any]]:
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"""Scan ~/.hermes/skills/ and return a mapping of /command -> skill info.
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Returns:
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Dict mapping "/skill-name" to {name, description, skill_md_path, skill_dir}.
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"""
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global _skill_commands
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_skill_commands = {}
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try:
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from tools.skills_tool import SKILLS_DIR, _parse_frontmatter, skill_matches_platform, _get_disabled_skill_names
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from agent.skill_utils import get_external_skills_dirs, iter_skill_index_files
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disabled = _get_disabled_skill_names()
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seen_names: set = set()
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# Scan local dir first, then external dirs
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dirs_to_scan = []
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if SKILLS_DIR.exists():
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dirs_to_scan.append(SKILLS_DIR)
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dirs_to_scan.extend(get_external_skills_dirs())
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for scan_dir in dirs_to_scan:
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for skill_md in iter_skill_index_files(scan_dir, "SKILL.md"):
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if any(part in ('.git', '.github', '.hub') for part in skill_md.parts):
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continue
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try:
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content = skill_md.read_text(encoding='utf-8')
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frontmatter, body = _parse_frontmatter(content)
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# Skip skills incompatible with the current OS platform
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if not skill_matches_platform(frontmatter):
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continue
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name = frontmatter.get('name', skill_md.parent.name)
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if name in seen_names:
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continue
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# Respect user's disabled skills config
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if name in disabled:
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continue
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description = frontmatter.get('description', '')
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if not description:
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for line in body.strip().split('\n'):
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line = line.strip()
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if line and not line.startswith('#'):
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description = line[:80]
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break
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seen_names.add(name)
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# Normalize to hyphen-separated slug, stripping
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# non-alnum chars (e.g. +, /) to avoid invalid
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# Telegram command names downstream.
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cmd_name = name.lower().replace(' ', '-').replace('_', '-')
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cmd_name = _SKILL_INVALID_CHARS.sub('', cmd_name)
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cmd_name = _SKILL_MULTI_HYPHEN.sub('-', cmd_name).strip('-')
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if not cmd_name:
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continue
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_skill_commands[f"/{cmd_name}"] = {
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"name": name,
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"description": description or f"Invoke the {name} skill",
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"skill_md_path": str(skill_md),
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"skill_dir": str(skill_md.parent),
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}
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except Exception:
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continue
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except Exception:
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pass
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return _skill_commands
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def get_skill_commands() -> Dict[str, Dict[str, Any]]:
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"""Return the current skill commands mapping (scan first if empty)."""
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if not _skill_commands:
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scan_skill_commands()
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return _skill_commands
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def reload_skills() -> Dict[str, Any]:
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"""Re-scan the skills directory and invalidate every in-process skill cache.
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Mirrors the ``/reload-mcp`` shape: clears state, rebuilds it, returns a
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diff summary that the caller (CLI, gateway, or agent tool) can render
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for the user / model.
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What this clears:
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* ``agent.skill_commands._skill_commands`` (slash-command map)
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* ``agent.prompt_builder._SKILLS_PROMPT_CACHE`` (in-process LRU)
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* ``.skills_prompt_snapshot.json`` on disk (cross-process snapshot)
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What gets re-read on the next prompt build:
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* ``~/.hermes/skills/`` and any ``skills.external_dirs``
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* Plugin-provided skills
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* ``skills.disabled`` / ``skills.platform_disabled`` from config.yaml
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Returns:
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Dict with keys::
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{
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"added": [skill names newly visible],
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"removed": [skill names no longer visible],
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"unchanged": [skill names present before and after],
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"total": total skill count after rescan,
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"commands": total /slash-skill count after rescan,
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}
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"""
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# Snapshot pre-reload state from the cache (what the agent had been
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# advertising). Comparing this to the post-rescan disk state shows
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# the user/agent which skills actually appeared / disappeared.
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before = set(_skill_commands.keys()) # /slash-form keys, e.g. "/demo"
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# Clear the slash-command cache. ``scan_skill_commands`` already
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# resets ``_skill_commands = {}`` internally, but we call the public
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# rescan path so the result is observable to ``get_skill_commands``.
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new_commands = scan_skill_commands()
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# Clear the system-prompt cache (in-process LRU + on-disk snapshot)
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# so the next prompt build re-walks the skills dir.
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try:
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from agent.prompt_builder import clear_skills_system_prompt_cache
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clear_skills_system_prompt_cache(clear_snapshot=True)
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except Exception as e: # pragma: no cover — best-effort
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logger.debug("Could not clear skills prompt cache: %s", e)
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after = set(new_commands.keys())
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# Strip leading slash for display: callers compare bare skill names.
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def _strip(s: set) -> set:
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return {k.lstrip("/") for k in s}
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added = sorted(_strip(after - before))
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removed = sorted(_strip(before - after))
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unchanged = sorted(_strip(after & before))
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return {
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"added": added,
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"removed": removed,
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"unchanged": unchanged,
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"total": len(after),
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"commands": len(new_commands),
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}
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def resolve_skill_command_key(command: str) -> Optional[str]:
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"""Resolve a user-typed /command to its canonical skill_cmds key.
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Skills are always stored with hyphens — ``scan_skill_commands`` normalizes
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spaces and underscores to hyphens when building the key. Hyphens and
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underscores are treated interchangeably in user input: this matches
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``_check_unavailable_skill`` and accommodates Telegram bot-command names
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(which disallow hyphens, so ``/claude-code`` is registered as
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``/claude_code`` and comes back in the underscored form).
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Returns the matching ``/slug`` key from ``get_skill_commands()`` or
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``None`` if no match.
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"""
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if not command:
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return None
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cmd_key = f"/{command.replace('_', '-')}"
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return cmd_key if cmd_key in get_skill_commands() else None
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def build_skill_invocation_message(
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cmd_key: str,
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user_instruction: str = "",
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task_id: str | None = None,
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runtime_note: str = "",
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) -> Optional[str]:
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"""Build the user message content for a skill slash command invocation.
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Args:
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cmd_key: The command key including leading slash (e.g., "/gif-search").
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user_instruction: Optional text the user typed after the command.
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Returns:
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The formatted message string, or None if the skill wasn't found.
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"""
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commands = get_skill_commands()
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skill_info = commands.get(cmd_key)
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if not skill_info:
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return None
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loaded = _load_skill_payload(skill_info["skill_dir"], task_id=task_id)
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if not loaded:
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return f"[Failed to load skill: {skill_info['name']}]"
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loaded_skill, skill_dir, skill_name = loaded
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activation_note = (
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f'[IMPORTANT: The user has invoked the "{skill_name}" skill, indicating they want '
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"you to follow its instructions. The full skill content is loaded below.]"
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)
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return _build_skill_message(
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loaded_skill,
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skill_dir,
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activation_note,
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user_instruction=user_instruction,
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runtime_note=runtime_note,
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session_id=task_id,
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)
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def build_preloaded_skills_prompt(
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skill_identifiers: list[str],
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task_id: str | None = None,
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) -> tuple[str, list[str], list[str]]:
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"""Load one or more skills for session-wide CLI preloading.
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Returns (prompt_text, loaded_skill_names, missing_identifiers).
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"""
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prompt_parts: list[str] = []
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loaded_names: list[str] = []
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missing: list[str] = []
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seen: set[str] = set()
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for raw_identifier in skill_identifiers:
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identifier = (raw_identifier or "").strip()
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if not identifier or identifier in seen:
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continue
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seen.add(identifier)
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loaded = _load_skill_payload(identifier, task_id=task_id)
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if not loaded:
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missing.append(identifier)
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continue
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loaded_skill, skill_dir, skill_name = loaded
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activation_note = (
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f'[IMPORTANT: The user launched this CLI session with the "{skill_name}" skill '
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"preloaded. Treat its instructions as active guidance for the duration of this "
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"session unless the user overrides them.]"
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)
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prompt_parts.append(
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_build_skill_message(
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loaded_skill,
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skill_dir,
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activation_note,
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session_id=task_id,
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)
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)
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loaded_names.append(skill_name)
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return "\n\n".join(prompt_parts), loaded_names, missing
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