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    • A
      license
      A
      quality
      B
      maintenance
      Enables frontier coding agents to delegate routine probabilistic judgments to TypeSafe Jev, providing calibrated triage signals for failures, attempts, completion, context ranking, findings, risk, and generic evidence-grounded questions.
      7
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI coding agents to offload yes/no, multiple-choice, and scoring questions to TypeSafe's Jev, returning compact confidence-scored answers to save tokens and improve speed.
      1
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables coding or reasoning agents to request structured judgments from TypeSafe's Jev model at decision points, including choices, scores, claim verification, and code reviews, with probabilities and confidence returned as data.
      5
      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Enables AI agents to obtain typed judgments from TypeSafe's Jev System One models, including yes/no probabilities, multiple-choice selections with distributions, and rubric-based scores, directly usable in code.
      5
      1
      AGPL 3.0
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables Claude Code agents to perform structured decision-making through TypeSafe Jev, supporting yes/no checks, route selection, scoring, and batched multi-question judgments with confidence values.
      1
      -
    • A
      license
      A
      quality
      A
      maintenance
      Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.
      1
      208 npm
      2
      MIT

    TDQS

    A4.4/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool has a clearly identified job: classification, scoring, yes/no checks, batched questions, batched files, directory line search, single-file line search, short-value extraction, injection screening, web ranking, and model listing. Even the similar pair jev_search and jev_locate are explicitly split by directory versus single-file use, so an agent should not misselect.

    Naming Consistency4/5

    All tools share the jev_ prefix and nearly all use a simple verb form, creating a predictable pattern. The only minor deviation is jev_models, which is a noun rather than a verb like list_models, but it is still recognizable and does not break the overall convention.

    Tool Count5/5

    Eleven tools is within the ideal range and each tool addresses a distinct need in the Jev workflow, from asking questions of files to ranking web pages to screening for prompt injection. The count feels deliberate rather than padded.

    Completeness5/5

    The surface covers the full read-and-analyze lifecycle: single questions, batched questions, many-file triage, directory search, large-file location, short extraction, classification, scoring, web ranking, and security screening. No obvious dead ends or missing operations stand out for the stated domain.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues