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Web Research to Docs

by r28ai
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Python
Remote

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    TDQS

    B3.2/5.0

    Scored across 21 tools

    Disambiguation4/5

    Most tools target clearly distinct resources (web search, crawl, scrape, Notion pages, Slack messages, Linear issues, GitHub repos), and descriptions provide usage guidance. However, the web research cluster (tavily_search, firecrawl_scrape, firecrawl_extract, tavily_research_create) has overlapping purposes that an agent could confuse without careful reading.

    Naming Consistency3/5

    All names use snake_case with app prefixes, but the ordering is mixed: some are verb_noun (github_search_repositories, linear_search_issues) while others are noun_verb (notion_pages_create, gdocs_documents_create, linear_issue_create). The server-level tools 'connect' and 'connection_status' also lack the app-prefix pattern, making the set readable but not fully predictable.

    Tool Count3/5

    21 tools is on the heavy side for a server named 'Web Research to Docs', and the surface sprawls across web search, document creation, spreadsheets, Slack, Linear, GitHub, and connection management. While each tool could earn its place in a broad integration hub, the count feels over-scoped for the stated workflow.

    Completeness2/5

    Several tools reference operations that are not exposed: gdocs_documents_create points to documents_batch_update for adding content, firecrawl_extract points to extract_status for polling, and linear_issue_create requires teams_list/users_list/workflow_states_list that are absent. Create-only surfaces for Notion, Google Docs, and Sheets lack read/update/delete counterparts, leaving agents with dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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