Single tool 'execute_skill_action' has a vague, marketing-focused name that does not follow verb_noun convention. Description is generic marketing copy (97 chars) lacking specifics on what the tool actually does, when to use it, or what it returns. Input schema is minimal: single string parameter 'query_payload' with no format constraints, validation rules, or examples. No output schema documented. The tool appears to be a pass-through echo service with no real functionality, it returns the input query verbatim in a JSON wrapper. No error handling guidance, no parameter validation, no security considerations. The implementation in mcp_server.py shows the tool simply echoes back the query_payload without any actual DOM pruning, accessibility tree processing, or semantic analysis despite the server name claiming to do so.

• Rename tool to 'prune_dom_tree' or 'analyze_accessibility_tree' to clearly convey the action and match the server's stated purpose.
• Rewrite description to 50-150 characters explaining: 'Prunes non-semantic DOM elements (scripts, styles, SVGs) and returns an accessibility tree with interactive element IDs and bounding boxes.' Include when to use it: 'Call this after fetching raw DOM to extract actionable interactive targets.'
• Add parameter constraints: 'query_payload' should accept a JSON string with a defined schema (e.g. array of DOM elements with tag, role, text, bbox fields). Document expected format and provide an example.
• Document output schema explicitly in the tool definition: return object with fields 'accessibility_tree' (array of pruned elements), 'interactive_lookup' (map of element IDs to metadata), 'compression_ratio' (percentage), 'interactive_targets_count' (integer).
• Implement actual DOM pruning logic in the MCP server. Currently the tool is a pass-through echo. Integrate the DOMSemanticAccessibilityTreePruner class from client.py into the tools/call handler so the tool performs its stated function.