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Ikalus1988

MisakaNet

by Ikalus1988
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Python

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TDQS

A4.4/5.0

Scored across 11 tools

Disambiguation3/5

Three tools (misakanet_search, misakanet_memory_context, misakanet_preflight) all match a text query against the same lesson corpus, and choosing between them depends on subtle timing cues ('before a task' vs 'after an error appears' vs 'before a risky operation') rather than distinct resources. The verbose descriptions do explicitly steer usage, which rescues the set from worse confusion, but an agent can plausibly pick memory_context where preflight was intended. The remaining tools (write/submit/register/quota/inbox/evidence) are cleanly separable.

Naming Consistency3/5

There is a consistent misakanet_ prefix and snake_case throughout, but the second segment mixes conventions: verb_noun (search, get_lesson, submit_intake, write_lesson, submit_usage), bare noun phrases (preflight, usage_status, memory_context), and an odd 'me_' family (me_events, me_inbox). The description itself admits me_events is a backward-compatibility alias for a semantic get_my_events, confirming the inconsistency. Still readable and greppable, but not a predictable pattern.

Tool Count5/5

Eleven tools sit squarely in the well-scoped range and each covers a distinct lifecycle stage: discovery, retrieval, proactive warning, write/intake, feedback, evidence, quota, registration, and inbox polling. No tool looks like dead weight or a duplicate of another.

Completeness4/5

The lifecycle is broadly covered — read, active-memory injection, preflight risk, contribution (intake and full lesson), feedback, evidence, identity/quota, and inbox polling — with no obvious dead ends for the primary search-and-contribute workflow. Minor gaps remain: there is no polling path for a submitted lesson_id (me_inbox only accepts intake_id or dedup_key), and no update/retract operation for an existing lesson.

Maintenance

ActivityActive
ResponsivenessResponsive

Resources