Analyze SAPUI5 project configuration from ui5.yaml, manifest.json, and package.json.

Generate a SAPUI5 controller skeleton with lifecycle hooks and JSDoc.

Generate an XML SAPUI5 fragment skeleton with proper namespaces.

Generate a formatter module that follows SAPUI5 module structure.

Generate UI5 view-controller event logic methods for XML views.

Generate an end-to-end UI5 feature scaffold (view/controller/fragment/routing/i18n) with dry-run support.

Extract UI literals, detect missing/unused i18n keys, and optionally apply fixes with safe preview/apply patch flow.

Analyze UI5 XML/JS files with performance-focused rules and actionable recommendations.

Read a workspace file safely with project-root sandboxing.

Search workspace files by text query with optional extension filtering.

Analyze the current file for imports, class structure, and controller methods.

Synchronize manifest.json models, routes, and targets with idempotent updates and optional dry-run.

Preview a safe workspace file write with hashes, line summary, and textual diff preview.

Apply one or more safe workspace file changes and create rollback metadata for later restore.

Rollback a previously applied patch using stored backup metadata.

Run consolidated quality gate for UI5 projects (version compatibility, security, performance, OData usage, and context docs freshness).

Return MCP server/runtime health diagnostics (tool exposure, docs alignment, contract snapshot, and managed artifact status).

Search official SAPUI5 SDK metadata and return API/topic summaries with examples.

Search MDN documentation for JavaScript and web platform references.

Generate an ES2022 JavaScript or TypeScript function with JSDoc for browser or Node runtime.

Refactor JavaScript code using modern syntax while preserving readability.

Run ESLint-style static checks and return warnings plus suggested fixes.

Detect risky JavaScript patterns including eval, command injection, and prototype pollution.

Validate SAPUI5 code for sap.ui.define usage, dependency order, naming, and MVC separation.

Validate UI5 control/module compatibility against project version and recommend better-fit components (e.g. dedicated date controls).

Scan UI5 XML/JS sources for security risks (XSS, unsafe HTML injection, dynamic code execution, insecure redirects).

Analyze OData V2/V4 metadata from XML, file, URL, or service root and return entities, properties, navigation, and operations.

Validate UI5 OData usage across manifest, XML/JS bindings, model APIs, and optional metadata cross-checks.

Generate a base UI5 OData feature scaffold (view/controller/manifest/i18n) from service metadata with dry-run safety.

Scaffold reusable project agent artifacts (blueprint, guide, bootstrap prompt, optional MCP config) with dry-run and patch safety.

Validate generated agent blueprint and guardrail artifacts for consistency, tool coverage, and MCP integration readiness.

Analyze project signals and recommend agent definitions with materialization-ready arguments.

Materialize recommended agents into project artifacts by generating blueprint/guide/prompt and optional MCP config.

Save generated agent artifacts into a reusable pack catalog with strict validation and fingerprinting.

List saved reusable agent packs from catalog.

Apply a saved agent pack to the current project with fingerprint verification and scaffolded materialization.

Refresh docs/mcp context files incrementally using workspace snapshot diff with deterministic output.

Record agent execution feedback in local JSONL log and update aggregate pack metrics for future ranking and promotion.

Rank saved agent packs using execution feedback metrics to prioritize recommendations for the current context.

Promote/degrade pack lifecycle status (experimental/candidate/recommended/deprecated) using automatic rules over feedback metrics or manual override.

Audit MCP project artifacts/layout version and produce a migration plan to the current managed structure.

Upgrade MCP-managed project artifacts to the latest layout version with dry-run, preview, and rollback-safe patching.

Automatically audit and upgrade MCP project artifacts to the current managed layout when needed.

Collect and persist legacy-project contextual intake to improve AI guidance quality while minimizing repeated prompts/tokens.

Build a technical baseline for legacy projects to guide high-quality AI integration with minimal context waste.

Build a token-efficient, quality-aware context index for legacy projects to minimize redundant prompts.

Prepare a legacy/existing project for high-quality AI delivery by orchestrating ensure, intake, baseline, and context index steps.

Scaffold and manage project skills catalog with official references, safe preview/apply flow, and growth-ready feedback artifacts.

Validate project skill catalog integrity, official references, and file layout consistency.

Record structured execution feedback for project skills and update aggregate metrics for future ranking.

Rank project skills using local feedback metrics to prioritize reliable skills in future recommendations.