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Diogenes Context Compression, Code Patching & Deterministic Solver MCP

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Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

A4.5/5.0

Scored across 15 tools

Disambiguation5/5

Each tool targets a clearly distinct operation (compression, token budgeting, reranking, patching, AST analysis, dependency cycles, stacktrace triage, type generation, math, scheduling, A/B stats, schema diffing, test vectors, Monte Carlo, state diffing). Descriptions explicitly cross-reference the nearest neighbor ('for X, use Y instead'), resolving the only potential overlaps like prune_context_skeleton vs rerank_hybrid_rag_chunks or analyze_ast_symbol_graph vs audit_module_dependency_cycles.

Naming Consistency5/5

All 15 tools follow a consistent snake_case verb_noun (or verb_qualifier_noun) pattern: prune_context_skeleton, compile_polyglot_type_schemas, simulate_monte_carlo_risk, diff_agent_memory_checkpoint. No camelCase mixing or vague single-word verbs; names fully describe the action and target.

Tool Count5/5

15 tools sits at the upper end of the well-scoped 3-15 range, and each tool maps to a genuinely distinct, non-redundant capability. No filler tools or near-duplicates inflate the surface.

Completeness4/5

The 'context engineering / code analysis' domain is well covered across compression, budgeting, patching, static analysis, stats, and scheduling with no obvious dead ends. Minor gaps exist (e.g. no embedding/search or sandboxed execution step), but core workflows are workable end-to-end.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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