Skip to main content
Glama
Ikalus1988

MisakaNet

by Ikalus1988
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

Related Servers

Alternatives to MisakaNet

  • Kira

    benyalgx
    A
    license
    A
    quality
    A
    maintenance
    Automatically provides AI agents with proven instructions and past failure warnings for common tasks like deployment, auth, and payments, enabling flawless execution without manual configuration.
    10
    53 npm
    3
    MIT

Related Servers

  • fixmemory

    xixi-box
    A
    license
    Not graded
    quality
    B
    maintenance
    Enables coding agents to maintain a shared, verified memory of debugging failures and fixes, with candidate verification, project-scoped search, and cross-project promotion.
    10 npm
    MIT
  • FailEcho by FailEcho

    FailEchoofficial

    FailEcho
    A
    license
    A
    quality
    A
    maintenance
    Enables AI agents to query live, cross-agent tool failure fingerprints and recovery outcomes before retrying, so they can act on collective evidence and avoid repeating proven-ineffective retries.
    4
    2
    MIT

  • FailTrace

    LBarimi
    A
    license
    Not graded
    quality
    A
    maintenance
    Enables coding agents to capture and replay intermittent software failures, minimize reproductions, compare trials, search regressions, verify proposed fixes against a saved failing baseline, and retrieve investigation evidence without rerunning commands.
    86 npm
    MIT

  • diffhound

    reacherwu
    A
    license
    Not graded
    quality
    A
    maintenance
    Zero-noise anti-regression guard & causal memory engine for Cursor, Claude Code, and CI/CD. Retrospectively pairs failure symptoms with fixes in < 100 μs, exempting historical root causes from decay.
    3
    AGPL 3.0
Deploy Server
Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

TDQS

A4.5/5.0

Scored across 10 tools

Disambiguation3/5

Several tools overlap in retrieval and contribution roles: misakanet_search, misakanet_get_lesson, and misakanet_memory_context all return lessons, while misakanet_submit_intake and misakanet_write_lesson both submit contributions. Descriptions do differentiate them (discovery vs. ID fetch vs. proactive injection; lightweight intake vs. full registered lesson), but an agent could reasonably misselect between search and memory_context or between the two submission tools.

Naming Consistency4/5

Almost all tools share the misakanet_ prefix and snake_case, with many following a verb_noun shape (search, submit_intake, write_lesson, get_lesson, submit_usage, register). A few deviate into noun phrases (me_events, preflight, usage_status, memory_context), which is a minor inconsistency but still readable and grouped coherently.

Tool Count5/5

Ten tools is well-scoped for a failure-lesson knowledge service, covering discovery, retrieval, contribution, risk checks, evidence, and auth/quota. Each tool maps to a distinct capability rather than padding the surface.

Completeness4/5

The surface covers the main lifecycle: search/discovery, fetch, proactive context, preflight risk check, two contribution paths, usage recording, evidence lookup, and registration/quota. There is no edit/update or delete for lessons, nor a way to list one's own submissions beyond events, but these are minor gaps an agent can work around.

Maintenance

ActivityNo data
ResponsivenessResponsive

Resources