This is a specialized encoding/decoding library, not a traditional MCP server. Tools lack proper descriptions (most are 20-80 chars, below the 50-200 char baseline for LLM optimization). Input schemas are present but minimal, parameters lack type constraints, enums, ranges, or validation guidance. No error handling documentation. Tools are narrowly focused on GCF format manipulation rather than user-facing operations. The 'encode' tool accepts a complex nested object (symbols, edges) with no guidance on structure or constraints. Generic tools like 'encode-generic' and 'decode-generic' accept 'any' type with no validation hints. No output schemas documented. This reads as a low-level codec library exposed as tools, not a production-grade agent toolkit.

• Expand all descriptions to 50-200 characters. Include WHAT the tool does, WHEN to use it (e.g., 'Use encode for graph payloads with symbols and edges; use encode-generic for arbitrary JSON'), and WHAT it returns. Example: 'Encode a graph payload (symbols + edges) into GCF wire format for token-efficient transmission. Returns a compact string representation. Use this when you have structured graph data; use encode-generic for arbitrary JSON.'
• Add explicit schemas for nested objects. For 'symbols' array, document: [{qualifiedName: string, kind: enum(class|function|variable|...), score: number 0-1, provenance: string, distance: integer >= 0}]. For 'edges', document: [{source: string, target: string, edgeType: enum(depends_on|calls|...), status?: string}].
• Document output schemas for all tools. Example for 'encode': returns a string in GCF wire format (lines of key=value pairs). For 'stats': returns an object {jsonTokens: integer, gcfTokens: integer, savings: number 0-100}.
• Add error handling guidance. Example for 'decode': 'Returns error if input is not valid GCF format. Check that the input starts with a valid GCF header (e.g., "GCF profile=graph"). If parsing fails, try decode-generic or validate the input with a GCF validator tool.'
• Consolidate duplicate tools. Choose one naming convention (lowercase with hyphens: encode, decode, encode-generic, decode-generic) and remove the PascalCase variants (Encode, Decode, EncodeGeneric, etc.). This reduces cognitive load for LLMs and clarifies the canonical API.