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Hedgehog

by jpalmerr
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Python
Local

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    TDQS

    A3.7/5.0

    Scored across 16 tools

    Disambiguation5/5

    Every tool has a clearly distinct purpose within the spike investigation lifecycle. The tools cover different phases (planning, exploration, synthesis, completion) and specific actions (create, add branch, challenge, checkpoint, rollback, etc.) with no overlap or ambiguity. An agent can easily distinguish between tools like spike_add_branch, spike_complete_branch, and spike_mark_dead_end based on their distinct roles.

    Naming Consistency5/5

    All tools follow a perfect 'spike_verb_noun' naming pattern throughout. The verb-noun structure is consistent (e.g., spike_create, spike_add_branch, spike_generate_adr), using snake_case uniformly. This predictable naming makes it easy for agents to understand and navigate the toolset.

    Tool Count4/5

    With 16 tools, the count is slightly high but reasonable for the comprehensive spike investigation domain. It covers the full lifecycle from creation to archival, including branching, challenges, checkpoints, and synthesis. While it might feel heavy, each tool appears to earn its place for a specific workflow step.

    Completeness5/5

    The toolset provides complete coverage of the spike investigation domain, supporting all phases from planning (create, approve meta) through exploration (add branch, complete branch, mark dead end) to synthesis (generate adr, synthesize) and completion (approve adr, archive). There are no obvious gaps; agents can manage the entire lifecycle without dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources