feat(skill): add agent skills loader

Implemented AgentSkillSpec loader that parses SKILL.md frontmatter and
progressive disclosure sections (discover/activate/deactivate) into
structured SkillStep objects with stable 1-based ordering.

Mapped Agent Skills to AgentSkillToolDescriptor with namespaced naming
(namespace/short_name), source="agent_skill", read-only defaults, and
AgentSkillResourceSlot bindings for scripts/, references/, and assets/
directories. All resource slots are unconditionally read_only.

Added explicit validation for missing frontmatter fields (name,
description) and invalid namespace format with actionable error messages.

Added docs/reference/agent_skills.md covering folder layout, SKILL.md
parsing rules, progressive disclosure model, and tool mapping.

Added Behave scenarios covering valid/invalid SKILL.md parsing,
namespaced naming, step ordering, missing frontmatter errors, progressive
disclosure lifecycle, tool mapping, and resource binding slots.

Added Robot Framework integration tests using the deploy-to-staging
example skill folder (robot/agent_skills_loader.robot).

Added ASV benchmarks for parsing throughput, folder load, progressive
disclosure lifecycle, and resource listing
(benchmarks/agent_skills_loader_bench.py).

ISSUES CLOSED: #160

examples/agent-skills/deploy-to-staging/SKILL.md

@@ -0,0 +1,40 @@
+---
+name: local/deploy-to-staging
+description: Deploy the current branch to the staging environment.
+version: 1.0.0
+steps:
+  - Verify all tests pass locally
+  - Confirm the branch is up to date with the remote
+  - Push the branch to the remote repository
+  - Trigger the CI pipeline and wait for it to pass
+  - Run the deployment script from scripts/deploy.py
+  - Verify the deployment using the health check in references/runbook.md
+  - Notify the team via the configured notification channel
+  - Monitor logs for the first 5 minutes after deployment
+metadata:
+  author: example
+  environment: staging
+allowed-tools:
+  - builtin/shell
+  - builtin/git-status
+---
+# Deploy to Staging
+
+Follow these steps to deploy the current branch to staging.
+
+## Pre-flight Checks
+
+1. Verify all tests pass locally using `builtin/shell`.
+2. Confirm the branch is up to date with `builtin/git-status`.
+
+## Deployment Steps
+
+3. Push the branch to the remote repository.
+4. Trigger the CI pipeline and wait for it to pass.
+5. Run the deployment script from `scripts/deploy.py`.
+6. Verify the deployment using the health check reference in `references/runbook.md`.
+
+## Post-deployment
+
+7. Notify the team via the configured notification channel.
+8. Monitor logs for the first 5 minutes after deployment.

examples/agent-skills/deploy-to-staging/references/runbook.md

@@ -0,0 +1,14 @@
+# Deployment Runbook
+
+## Health Check Endpoints
+
+- `/health` — Returns 200 OK if the service is healthy.
+- `/ready` — Returns 200 OK if the service is ready to accept traffic.
+
+## Rollback Procedure
+
+If deployment fails, run the rollback script from the scripts/ directory.
+
+## Contact
+
+Alert the on-call engineer if health checks fail after 3 retries.

examples/agent-skills/deploy-to-staging/scripts/deploy.py

@@ -0,0 +1,20 @@
+"""Deployment helper script for the deploy-to-staging Agent Skill.
+
+This script is invoked by the LLM agent following the SKILL.md instructions.
+It runs the deployment pipeline and returns a structured result.
+"""
+
+from __future__ import annotations
+
+import sys
+
+
+def main() -> int:
+    """Execute the deployment pipeline."""
+    print("deploy-to-staging: starting deployment")
+    print("deploy-to-staging: deployment complete")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())