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dsa-coach-mcp

by aaryagodbole
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Python
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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

    B3.4/5.0

    Scored across 8 tools

    Disambiguation4/5

    Each tool maps to a distinct action: platform metadata, profile lookup, problem search, review logging, due revisions, mistake labels, mistake journaling, and mistake analytics. The closest overlap is between mistake_kinds (label vocabulary) and mistake_patterns (aggregated counts), but the descriptions make the boundary clear enough.

    Naming Consistency3/5

    The tools are all snake_case and readable, but they mix verb-first names (list_platforms, get_profile, search_problems, log_review) with noun-phrase names (revisions_due, mistake_kinds, mistake_patterns). The inconsistency is noticeable but not chaotic.

    Tool Count5/5

    Eight tools is a well-scoped set for a DSA coaching workflow, covering discovery, review scheduling, and mistake tracking without obvious filler. Each tool appears to earn its place.

    Completeness4/5

    The surface covers the main coaching loop: inspect platforms and profiles, find problems, log reviews, see due revisions, and analyze mistakes. Minor gaps exist around explicitly updating solved status or managing platform connections, but core workflows are supported.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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