market-research
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- AlicenseNot gradedqualityBmaintenanceMakes AI research agents accountable by giving every conclusion a traceable argument graph. Provides a persistent argument graph where claims require grounds and warrants for auditable, verifiable reasoning.3MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to reverse-engineer how an organization actually operates by ingesting documents, spreadsheets, chat exports, invoices and audio, then tracing every claim back to graded evidence. It supports process mining, stated-vs-enacted comparison, coverage and obligation tracking, and bilingual report generation while keeping unproven areas explicitly flagged as unknown.MIT
- AlicenseAqualityBmaintenanceEnables local AI models to structure and reason through debates using argument maps, with claims and supporting/attacking arguments automatically validated and organized.81AGPL 3.0
- AlicenseNot gradedqualityAmaintenanceEnables users to conduct inspectable research with native Codex or Claude providers, producing locally saved dossiers with source-linked findings, evidence levels, falsifiers, limitations, and recorded retrieval events.7 npm2MIT
- AlicenseCqualityBmaintenanceGives any MCP client 27 tools for turning scattered feeds, forums, and media into a persistent, searchable evidence corpus, so an agent can search and import evidence, verify claims with independent-source counting and citation checks, and run multi-round research that produces cited, revisable reports. It also supports adaptive retrieval widening, tiered evidence where only author-written sections count as sources, and honest degradation when no LLM key is available.27MIT
- AlicenseNot gradedqualityCmaintenanceEnables agents to search the web, communities, databases, and archives, read original sources, and gather verifiable evidence with URLs, versions, timestamps, and saved evidence IDs.1MIT
TDQS
Scored across 47 tools
Most tools target distinct stages of the research pipeline, and descriptions clarify boundaries (e.g., lexical vs. semantic search, single vs. batch operations). However, the presence of legacy and batch variants (e.g., verify_claims vs. resolve_claims_batch) and multiple extraction submission paths introduces some ambiguity that an agent could misselect.
All tool names use snake_case with a clear verb_noun pattern (e.g., create_research, get_research_state, submit_extracted_signals). Batch variants consistently add a _batch suffix, and no camelCase or mixed conventions appear.
47 tools is far beyond the typical 3-15 range and exceeds the 25+ threshold for 'too many'. While the domain is complex, the sheer number increases cognitive load and risks tool selection errors.
The surface covers the full research lifecycle: creation, state management, stepping, extraction, verification, counterevidence, clustering, query lattice, source operations, search, comparison, analysis, and export. No obvious gaps in core workflows are apparent.