feat(skills): add skill config interface + llm-wiki skill (#5635)
Skills can now declare config.yaml settings via metadata.hermes.config in their SKILL.md frontmatter. Values are stored under skills.config.* namespace, prompted during hermes config migrate, shown in hermes config show, and injected into the skill context at load time. Also adds the llm-wiki skill (Karpathy's LLM Wiki pattern) as the first skill to use the new config interface, declaring wiki.path. Skill config interface (new): - agent/skill_utils.py: extract_skill_config_vars(), discover_all_skill_config_vars(), resolve_skill_config_values(), SKILL_CONFIG_PREFIX - agent/skill_commands.py: _inject_skill_config() injects resolved values into skill messages as [Skill config: ...] block - hermes_cli/config.py: get_missing_skill_config_vars(), skill config prompting in migrate_config(), Skill Settings in show_config() LLM Wiki skill (skills/research/llm-wiki/SKILL.md): - Three-layer architecture (raw sources, wiki pages, schema) - Three operations (ingest, query, lint) - Session orientation, page thresholds, tag taxonomy, update policy, scaling guidance, log rotation, archiving workflow Docs: creating-skills.md, configuration.md, skills.md, skills-catalog.md Closes #5100
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Teknium
@@ -79,6 +79,45 @@ def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tu
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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 = ["", "[Skill config (from ~/.hermes/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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@@ -93,6 +132,9 @@ def _build_skill_message(
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parts = [activation_note, "", content.strip()]
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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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@@ -254,6 +254,163 @@ def extract_skill_conditions(frontmatter: Dict[str, Any]) -> Dict[str, List]:
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}
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# ── Skill config extraction ───────────────────────────────────────────────
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def extract_skill_config_vars(frontmatter: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""Extract config variable declarations from parsed frontmatter.
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Skills declare config.yaml settings they need via::
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metadata:
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hermes:
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config:
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- key: wiki.path
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description: Path to the LLM Wiki knowledge base directory
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default: "~/wiki"
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prompt: Wiki directory path
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Returns a list of dicts with keys: ``key``, ``description``, ``default``,
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``prompt``. Invalid or incomplete entries are silently skipped.
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"""
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metadata = frontmatter.get("metadata")
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if not isinstance(metadata, dict):
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return []
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hermes = metadata.get("hermes")
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if not isinstance(hermes, dict):
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return []
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raw = hermes.get("config")
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if not raw:
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return []
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if isinstance(raw, dict):
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raw = [raw]
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if not isinstance(raw, list):
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return []
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result: List[Dict[str, Any]] = []
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seen: set = set()
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for item in raw:
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if not isinstance(item, dict):
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continue
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key = str(item.get("key", "")).strip()
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if not key or key in seen:
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continue
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# Must have at least key and description
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desc = str(item.get("description", "")).strip()
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if not desc:
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continue
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entry: Dict[str, Any] = {
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"key": key,
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"description": desc,
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}
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default = item.get("default")
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if default is not None:
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entry["default"] = default
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prompt_text = item.get("prompt")
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if isinstance(prompt_text, str) and prompt_text.strip():
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entry["prompt"] = prompt_text.strip()
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else:
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entry["prompt"] = desc
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seen.add(key)
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result.append(entry)
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return result
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def discover_all_skill_config_vars() -> List[Dict[str, Any]]:
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"""Scan all enabled skills and collect their config variable declarations.
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Walks every skills directory, parses each SKILL.md frontmatter, and returns
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a deduplicated list of config var dicts. Each dict also includes a
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``skill`` key with the skill name for attribution.
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Disabled and platform-incompatible skills are excluded.
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"""
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all_vars: List[Dict[str, Any]] = []
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seen_keys: set = set()
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disabled = get_disabled_skill_names()
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for skills_dir in get_all_skills_dirs():
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if not skills_dir.is_dir():
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continue
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for skill_file in iter_skill_index_files(skills_dir, "SKILL.md"):
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try:
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raw = skill_file.read_text(encoding="utf-8")
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frontmatter, _ = parse_frontmatter(raw)
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except Exception:
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continue
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skill_name = frontmatter.get("name") or skill_file.parent.name
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if str(skill_name) in disabled:
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continue
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if not skill_matches_platform(frontmatter):
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continue
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config_vars = extract_skill_config_vars(frontmatter)
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for var in config_vars:
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if var["key"] not in seen_keys:
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var["skill"] = str(skill_name)
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all_vars.append(var)
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seen_keys.add(var["key"])
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return all_vars
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# Storage prefix: all skill config vars are stored under skills.config.*
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# in config.yaml. Skill authors declare logical keys (e.g. "wiki.path");
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# the system adds this prefix for storage and strips it for display.
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SKILL_CONFIG_PREFIX = "skills.config"
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def _resolve_dotpath(config: Dict[str, Any], dotted_key: str):
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"""Walk a nested dict following a dotted key. Returns None if any part is missing."""
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parts = dotted_key.split(".")
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current = config
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for part in parts:
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if isinstance(current, dict) and part in current:
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current = current[part]
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else:
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return None
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return current
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def resolve_skill_config_values(
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config_vars: List[Dict[str, Any]],
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) -> Dict[str, Any]:
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"""Resolve current values for skill config vars from config.yaml.
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Skill config is stored under ``skills.config.<key>`` in config.yaml.
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Returns a dict mapping **logical** keys (as declared by skills) to their
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current values (or the declared default if the key isn't set).
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Path values are expanded via ``os.path.expanduser``.
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"""
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config_path = get_hermes_home() / "config.yaml"
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config: Dict[str, Any] = {}
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if config_path.exists():
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try:
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parsed = yaml_load(config_path.read_text(encoding="utf-8"))
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if isinstance(parsed, dict):
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config = parsed
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except Exception:
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pass
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resolved: Dict[str, Any] = {}
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for var in config_vars:
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logical_key = var["key"]
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storage_key = f"{SKILL_CONFIG_PREFIX}.{logical_key}"
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value = _resolve_dotpath(config, storage_key)
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if value is None or (isinstance(value, str) and not value.strip()):
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value = var.get("default", "")
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# Expand ~ in path-like values
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if isinstance(value, str) and ("~" in value or "${" in value):
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value = os.path.expanduser(os.path.expandvars(value))
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resolved[logical_key] = value
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return resolved
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# ── Description extraction ────────────────────────────────────────────────
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