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cleveragents-core/docs/reference/skill_registry.md
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2026-02-25 10:03:21 +00:00

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Skill Registry

The Skill Registry provides persistent storage for skill definitions in CleverAgents. Skills are namespaced, reusable collections of tools registered via YAML config and persisted to the skills and skill_items database tables.

Registration Behavior

Skills are registered with a namespaced name (namespace/short_name) as the unique identifier. The registry enforces:

  • Name uniqueness: Duplicate names are rejected with DuplicateSkillError.
  • Name validation: Names must match ^[a-zA-Z0-9_-]+/[a-zA-Z0-9_-]+$.
  • Cascading deletes: Removing a skill cascades to all child skill_items rows.

Skill Items

Each skill stores its components as ordered items in the skill_items table. The item_type discriminator distinguishes:

item_type Description
tool_ref Reference to a named tool in the registry
include Recursive inclusion of another skill
inline_tool Anonymous tool defined inline
mcp_source MCP server tool source
agent_source Agent Skills Standard folder source

Items are stored with a stable item_order to preserve definition ordering across round-trips.

Filters

The SkillRegistryService.list_skills() method supports:

  • Namespace filter: Pass namespace="local" to list only skills in the local namespace.

Service API

from cleveragents.application.services import SkillRegistryService
from cleveragents.infrastructure.database.repositories import SkillRepository

svc = SkillRegistryService(skill_repo=SkillRepository(session_factory))

# Register
svc.add_skill(skill)

# Retrieve
skill = svc.get_skill("local/code-tools")

# List with filter
skills = svc.list_skills(namespace="local")

# Update
svc.update_skill(updated_skill)

# Remove
svc.remove_skill("local/code-tools")

Agent Skills Discovery

The Skill Registry integrates with the Agent Skills Standard — filesystem-based tool bundles identified by a SKILL.md file with YAML front-matter.

Configuration

The skills.agent_skills_paths config key controls which directories are scanned. Multiple paths are separated by commas:

# ~/.cleveragents/config.toml
[skills]
agent_skills_paths = "/home/user/.cleveragents/agent_skills,/opt/skills"

The default path is ~/.cleveragents/agent_skills.

Environment variable override: CLEVERAGENTS_SKILLS_AGENT_SKILLS_PATHS.

Discovery Algorithm

  1. Parse the comma-separated skills.agent_skills_paths value.
  2. For each directory, find immediate subdirectories containing a SKILL.md file.
  3. Parse the YAML front-matter (between --- fences) to extract the tool name, description, and optional input_schema / output_schema.
  4. Construct ToolSpec instances with source="agent_skills" and source_metadata containing the filesystem path.
  5. Register each tool in the ToolRegistry under the agent_skills/<name> namespace.

SKILL.md Format

---
name: my-tool
description: A custom agent skill
input_schema:
  type: object
  properties:
    query:
      type: string
---

# My Tool

Additional documentation here.

Conflict Handling

When an Agent Skill name collides with an existing tool in the ToolRegistry, the discovery process records a DiscoveryConflict. The caller decides the strategy:

Strategy Behavior
skip Keep existing tool, log warning (default)
error Raise ValueError with collision details
replace Remove existing tool and register the new one

Refresh Hook

The SkillRegistryService.refresh_agent_skills() method re-scans all configured paths. It first removes previously registered agent skill tools, then re-discovers and re-registers. The CLI agents skill tools command accepts a --refresh flag to trigger this.

CLI Output

The agents skill tools command includes source metadata when tools originate from Agent Skills:

agents skill tools local/devops-toolkit --format json

Each entry in the output includes a "source" field indicating the tool's origin (builtin, agent_skills, mcp, or custom).

Service API (Discovery)

from cleveragents.application.services import SkillRegistryService
from cleveragents.infrastructure.database.repositories import SkillRepository
from cleveragents.tool.registry import ToolRegistry

tool_registry = ToolRegistry()
svc = SkillRegistryService(
    skill_repo=SkillRepository(session_factory),
    tool_registry=tool_registry,
)

# Initial discovery
result = svc.discover_and_register(
    "~/.cleveragents/agent_skills,/opt/skills"
)
print(f"Discovered: {len(result.discovered)} skills")
print(f"Conflicts: {len(result.conflicts)}")

# Refresh (re-scan)
result = svc.refresh_agent_skills(
    "~/.cleveragents/agent_skills,/opt/skills"
)

Database Schema

skills

Column Type Description
name String(255) PK, namespaced name
namespace String(100) Extracted namespace
short_name String(150) Extracted short name
description Text Skill description
version String(50) Optional version string
metadata_json Text JSON metadata (overrides, etc.)
created_at String(30) ISO-8601 creation timestamp
updated_at String(30) ISO-8601 update timestamp

skill_items

Column Type Description
id Integer Auto-increment PK
skill_name String(255) FK to skills.name (CASCADE)
item_type String(30) Discriminator (tool_ref, etc.)
item_name String(500) Item identifier or name
item_config Text Optional JSON configuration
item_order Integer Stable ordering index
created_at String(30) ISO-8601 creation timestamp

Flattening Rules

The SkillResolver flattens a skill's tool set using the following deterministic algorithm:

Include Order

Tools are collected via depth-first traversal of includes:

  1. For each include (left-to-right), recurse into the included skill first, processing its includes before its own tool_refs.
  2. After all includes are resolved, add the current skill's tool_refs in definition order.
  3. Add inline tools as {skill_name}/_anon_{index}.
  4. Add MCP tools as mcp:{server}/{tool_name}.
  5. Add agent skills as agent_skill:{path}.

De-Duplication

When the same tool name appears multiple times (from overlapping includes), the first occurrence determines the position in the output list, but the last occurrence's entry metadata wins (last-wins semantics).

Override Merging

Overrides are applied at two levels:

  1. Skill-level overrides (skill.overrides dict): Applied to matching tool_refs during resolution.
  2. Per-include overrides (SkillInclude.overrides): Applied to all tool entries contributed by the included skill. Uses shallow merge -- include overrides are merged on top of any existing entry overrides.

Non-Overridable Fields

The following ResolvedToolEntry fields cannot be overridden:

  • name
  • source_skill
  • is_inline

Attempting to override these raises ValueError with the skill name and include path for traceability.

Capability Summary

The SkillCapabilitySummary aggregates capability metadata across all resolved tools:

Field Description
total_tools Total number of resolved tool entries
read_only_tools Count of inline tools with read_only=True
write_tools Count of inline tools with writes=True
checkpointable_tools Count of inline tools with checkpointable=True
has_side_effects True if any inline tool has side effects
mcp_sources Number of MCP server sources on the root skill
agent_skill_sources Number of agent skill sources on the root skill

validate_plan() Usage

The SkillRegistry.validate_plan() method checks that a plan's skill references are satisfiable:

from cleveragents.skills.registry import SkillRegistry

registry = SkillRegistry()
# ... register skills ...

errors = registry.validate_plan({"skills": ["local/code-tools", "local/deploy"]})
if errors:
    for err in errors:
        print(f"Plan validation error: {err}")

Checks Performed

  1. All referenced skills exist in the registry.
  2. All includes are resolvable (no missing skills in include chains).
  3. No cycles in include chains.
  4. Tool refs are valid (if a tool registry is configured).

Error Messages

Condition Error message pattern
Missing skill Skill '{name}' referenced in plan is not registered
Missing include Skill '{name}': Included skill '{inc}' not found ...
Cycle detected Skill '{name}': Cycle detected in skill includes: A -> B
Non-overridable field Non-overridable field(s) ... in overrides from skill ...

tools() Method

The SkillRegistry.tools() method combines resolve_tools() and compute_capability_summary() into a single call:

entries, summary = registry.tools("local/code-tools")
print(f"Total tools: {summary.total_tools}")
print(f"Has writes: {summary.write_tools > 0}")

Returns a 2-tuple of (list[ResolvedToolEntry], SkillCapabilitySummary).

Testing

Behave BDD Tests

The Behave feature file features/skill_registry.feature contains 23 scenarios covering the full SkillRegistryService and SkillRepository persistence layer:

Area Scenarios Description
Registration 6 Each skill item type (tool_ref, include, inline_tool, mcp_source, agent_source) plus basic round-trip
Duplicate rejection 1 DuplicateSkillError on name collision
Retrieval 2 Get by name, non-existent returns None
Listing 2 List all, list with namespace filter
Update 2 Description change, non-existent raises SkillNotFoundError
Deletion 2 Remove existing (cascades items), remove non-existent returns False
Overrides 1 Override metadata survives persistence round-trip
Item ordering 1 Mixed item types maintain stable order across round-trip
Name validation 3 Empty name, no-slash name, special characters rejected at persistence layer
Large payload 1 50 tool refs persist correctly
Domain objects 1 Listed skills are Skill domain instances

Step definitions: features/steps/skill_registry_steps.py

Session management note: Each scenario creates a fresh in-memory SQLite database with a single shared Session that is reused across all repository calls within the scenario. This mirrors the production UnitOfWork pattern (ADR-019) and avoids transaction-scoping issues inherent to multiple ephemeral sessions on a single StaticPool connection.

Run the Behave suite via:

nox -s unit_tests -- features/skill_registry.feature

Robot Smoke Tests

A Robot Framework smoke suite validates core registry operations:

robot/skill_registry.robot
robot/helper_skill_registry.py
Test Case What it validates
Register And Retrieve A Skill Round-trip: register then get by name
List Skills With Namespace Filter Register multiple skills, filter by namespace
Update A Skill Change description after registration
Reject Duplicate Skill Name Duplicate name produces error
Remove A Skill Remove and verify absence
nox -s integration_tests -- robot/skill_registry.robot

ASV Benchmarks

Performance benchmarks live in benchmarks/skill_registry_bench.py:

  • SkillModelConstruction -- time_from_domain (domain-to-ORM mapping)
  • SkillModelReconstruction -- time_to_domain (ORM-to-domain mapping)
  • SkillRepositoryCRUD -- time_create_skill, time_get_skill, time_list_all, time_list_namespace
  • SkillRegistryListPerformance -- time_list_100_skills, time_list_100_skills_filtered
nox -s benchmark