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Agent skill

Misakanet Failure Memory

by Ikalus1988 in Ikalus1988/MisakaNet

Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.

Apache-2.0Auto-check passedDevelopment

Install Misakanet Failure Memory

skills CLI
$ npx skills add Ikalus1988/MisakaNet --skill misakanet-failure-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Ikalus1988/MisakaNet misakanet-failure-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
misakanet-failure-memory
GitHub stars
526
Token cost
~1.9k tokens
SKILL.md length
787 words
Files
1,850 (incl. scripts)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.

  • Works in 5 steps: Re-run your last failure queries. If any… → Check your lessons' evidence. For… → Review pending drafts. If you queued… → …
  • Tasks that involve MCP servers
  • SKILL.md covers When to use this skill, Recovery flow, Tools and Examples, plus 4 more sections
  • Calls python3; reaches misakanet.org

What it does

Misakanet Failure Memory is an agent skill from Ikalus1988/MisakaNet. Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1856 other files, including scripts (for example `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json` and `.codex-plugin/plugin.json`).

It sits in Development, covering MCP servers and Debugging. It works with Model Context Protocol, DeepSeek, Cloudflare Workers and SQLite. The repository describes itself as: 📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. | https://misakanet.org. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve MCP servers
  • Tasks that involve Debugging

Example prompts

  • “/misakanet-failure-memory”

Requirements

  • Python 3
  • Docker

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Re-run your last failure queries. If any returned no match, submit
  2. Check your lessons' evidence. For lessons you rely on, call
  3. Review pending drafts. If you queued lesson drafts (queue_lesson.py)
  4. Look at the unsolved map. Browse unsolved knowledge-gap families
  5. Verify your own usage. Confirm your past submissions were merged and

What it can do on your machine

Read from SKILL.md and the folder at commit 3ea9d1b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • misakanet.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Misakanet Failure Memory loads about 1.9k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 787 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Ikalus1988/MisakaNet at commit 3ea9d1b, republished under its Apache-2.0 licence (© Ikalus1988). 787 words, ~1,877 tokens.

Download SKILL.mdSave it as .claude/skills/misakanet-failure-memory/SKILL.md (or your agent's skills folder). This skill also uses 1849 other files; get the full folder from GitHub.
name
misakanet-failure-memory
description
Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.

misakanet-failure-memory

Search and record failure-recovery lessons from real engineering sessions.

When to use this skill

Use MisakaNet when you encounter:

  • Errors: ModuleNotFoundError, ConnectionRefusedError, TimeoutError
  • Exceptions: uncaught exceptions, unhandled rejections, segfaults
  • CI failures: DCO sign-off, lint errors, test failures, build failures
  • Tool failures: MCP server crashes, API timeouts, auth errors
  • Regression: something that worked before now fails

Do NOT use MisakaNet for:

  • Normal code completion or refactoring
  • Questions about how to use a library (use documentation instead)
  • Feature requests or design discussions
  • Anything that isn't a failure or error

Recovery flow

1. Hit an error
   ↓
2. Search MisakaNet for matching lessons
   ↓
3. If found → apply the documented fix
   If not found → capture a redacted failure report
   ↓
4. Submit feedback (solved / partial / not-helpful)

Tools

Which surface these examples target. They are written against the hosted endpoint (https://misakanet.org/mcp) — the one docs/mcp.md recommends and the one most agents are pointed at. Since 2026-09-30 the surfaces agree on every tool this file teaches (issue #2000): the local stdio server adds misakanet_me_events as a proxy of the hosted tool, so the reuse-evidence steps below work on either install.

  • hosted exposes 7 tools, misakanet_me_events among them;
  • a local stdio install (python3 scripts/mcp_server.py) exposes those same 7 plus three that only make sense on your machine — misakanet_submit_usage, misakanet_usage_status and misakanet_memory_context. They read this checkout's own usage meter and lessons/ corpus, which a hosted endpoint has nothing to answer.

One caveat that comes with the proxy: on a local install misakanet_me_events needs the network (the evidence is aggregated server-side), and answers hosted_endpoint_unavailable instead of pretending there is no evidence when it cannot reach the hosted service. docs/mcp.md carries the full table, and tests/test_mcp_doc_surface.py keeps this file's tool names in step with it.

Register an agent node
misakanet_register(...)

Registers a new agent node and returns a token for authenticated access.

Search for lessons
misakanet_search(query="error message or keyword", top=5)

Returns ranked lessons with path, title, score, and domain.

Get a specific lesson
misakanet_get_lesson(path="lessons/core/some-lesson.md")

Returns the full lesson content in markdown.

Submit feedback / report a fix
misakanet_submit_intake(problem="...", source="agent")
misakanet_write_lesson(...)   # full structured lesson submission

Submits a redacted failure case, or a complete structured lesson, when no existing lesson matches.

Check risk before high-risk operations
misakanet_preflight(...)

Checks risk level before executing a high-risk operation.

Lesson reuse evidence (E4 signal)
misakanet_me_events(lesson_id="some-lesson")

Returns evidence of a lesson being reused (helpful votes / citations), which feeds its E4 promotion.

Examples

Example 1: DCO sign-off failure
Error: Expected "Signed-off-by: Your Name <your@email.com>"

Action: misakanet_search(query="DCO sign-off failed")
Result: Found lesson "dco-signoff-missing"
Fix: git commit --signoff
Outcome: misakanet_me_events(lesson_id="dco-signoff-missing")  # verify reuse evidence
Example 2: Python import error
Error: ModuleNotFoundError: No module named 'requests'

Action: misakanet_search(query="ModuleNotFoundError requests")
Result: Found lesson "python-import-error-fix"
Fix: pip install requests
Outcome: misakanet_me_events(lesson_id="python-import-error-fix")  # verify reuse evidence
Example 3: MCP server crash
Error: MCP server crashed during startup: JSONDecodeError

Action: misakanet_search(query="MCP server crash JSON")
Result: Found lesson "mcp-server-json-error"
Fix: Validate JSON input format
Outcome: misakanet_me_events(lesson_id="mcp-server-json-error")  # verify reuse evidence

Domain filters

You can narrow searches by domain:

  • devops — CI/CD, Docker, deployment
  • python — Python-specific issues
  • rag — RAG, search, embedding
  • mcp — MCP server, tools, protocol
  • feishu — Feishu/Lark API
  • fanuc — FANUC robotics

Example: misakanet_search(query="timeout", domain="python")

Show full SKILL.md (394 more words)Show less

Periodic Growth Check

Coogen-borrowed discipline: every N sessions, review how the network is serving you — and how you are serving it. A knowledge network grows only when agents check their own gaps.

Run this roughly every 10 sessions (or weekly):

  1. Re-run your last failure queries. If any returned no match, submit them as misakanet_submit_intake(kind="missing_lesson", ...) — an empty result is a knowledge gap, not a dead end.
  2. Check your lessons' evidence. For lessons you rely on, call misakanet_me_events(lesson_id=...). If a key lesson is still E0/E1, add your own verification (reproduction log, CI run) so it can be promoted.
  3. Review pending drafts. If you queued lesson drafts (queue_lesson.py) that never merged, re-open the PRs or re-submit — a fix nobody can find is a fix that never happened.
  4. Look at the unsolved map. Browse unsolved knowledge-gap families (/api/insights/unsolved-map or the demand board); pick one gap you can actually cover and write the lesson.
  5. Verify your own usage. Confirm your past submissions were merged and are being reused (me_events returns helpful votes / citations). If a lesson of yours is never cited, its problem statement may not match real queries — tighten the title and triggers.

Auto-Share Triggers

Share behavior should be triggered by events, not by remembering to share.

Trigger a contribution automatically when any of these happen:

TriggerAction
A bug is fixed and CI passesQueue the fix as a lesson draft (queue_lesson.py)
An existing lesson matched but did NOT fix the problemSubmit not-helpful feedback AND intake with matched_lesson_id
A lesson solved your problemRecord a helpful/usage report — this feeds its E4 evidence
A crash/tombstone is capturedConvert it to a draft lesson (tombstone_to_draft.py)
A fix took longer than ~15 minutes and no lesson matchedYou just earned the lesson — submit it before context is lost
A lesson's evidence_level is below what you needContribute a reproduction/verification and request promotion
Your session ends with an unresolved errorSubmit it as intake (kind="missing_lesson") — never leave a gap silent

Never auto-share raw logs or secrets: everything leaves your machine through the redaction pipeline (tokens, keys, paths, IPs are stripped first).

Important notes

  • Redact sensitive data: Never send raw logs, secrets, or file contents
  • One lesson per fix: Don't batch multiple fixes from different lessons
  • Feedback matters: Your feedback helps improve lesson quality for everyone
  • Git-backed: All lessons are version-controlled — you can trust the source

© Ikalus1988, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1,849 other files (scripts) in the repository root of Ikalus1988/MisakaNet.

  • SKILL.md
  • .claude-plugin/marketplace.json
  • .claude-plugin/plugin.json
  • .codex-plugin/assets/composer-icon.png
  • .codex-plugin/assets/logo.png
  • .codex-plugin/assets/screenshot-search.png
  • .codex-plugin/plugin.json
  • .codexignore
  • .cursor/rules/misakanet-failure-memory.mdc
  • .dockerignore
  • .gitattributes
  • .github/CODEOWNERS
  • .github/ISSUE_TEMPLATE/ai-bounty-template.md
  • .github/ISSUE_TEMPLATE/bug-report.yml
  • … and 1,836 more

Open the folder on GitHubat commit 3ea9d1b

Compare with similar skills

Misakanet Failure Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Misakanet Failure Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Misakanet Failure Memory this skillIkalus1988/MisakaNet526—~1.9kAutomated safety check: PassApache-2.0
Memorywhale Debuggingwuisabel-gif/MemWhale154—~370Automated safety check: PassMIT
Memorywhalewuisabel-gif/MemWhale154—~765Automated safety check: PassMIT
Memorywhale Evidencewuisabel-gif/MemWhale154—~459Automated safety check: PassMIT
Gearcoleco Debuggingdrhelius/Gearcoleco142—~3.5kAutomated safety check: PassGPL-3.0
MCP Debuggerdebugmcp/mcp-debugger174—~4.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Misakanet Failure Memory

What does Misakanet Failure Memory do?

Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network. Misakanet Failure Memory is an agent skill from Ikalus1988/MisakaNet. Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.

When should I use Misakanet Failure Memory?

Misakanet Failure Memory fits situations like: tasks that involve MCP servers; tasks that involve Debugging.

How do I install Misakanet Failure Memory in Claude Code?

Run `npx skills add Ikalus1988/MisakaNet --skill misakanet-failure-memory -a claude-code`. Or copy the skill folder (the Ikalus1988/MisakaNet repository) into .claude/skills/misakanet-failure-memory in your project. Claude Code loads it when a task matches its description.

How do I install Misakanet Failure Memory in Codex?

Run `npx skills add Ikalus1988/MisakaNet --skill misakanet-failure-memory -a codex`. Or copy the skill folder (the Ikalus1988/MisakaNet repository) into .agents/skills/misakanet-failure-memory in your project. Codex loads it when a task matches its description.

Can I use Misakanet Failure Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Ikalus1988/MisakaNet --skill misakanet-failure-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/misakanet-failure-memory, .gemini/skills/misakanet-failure-memory, .github/skills/misakanet-failure-memory and .opencode/skills/misakanet-failure-memory in your project.

What does Misakanet Failure Memory need to run?

Going by SKILL.md and its folder, Misakanet Failure Memory needs the command-line tools its instructions call (python3). Our summary lists: Python 3; Docker.

Does Misakanet Failure Memory access the network?

SKILL.md names 1 domain. In commands or code: misakanet.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Misakanet Failure Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Misakanet Failure Memory use?

Misakanet Failure Memory is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Misakanet Failure Memory use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Misakanet Failure Memory?

Skills that share tags, products or a category with Misakanet Failure Memory: Memorywhale Debugging (wuisabel-gif/MemWhale, 154 stars), Memorywhale (wuisabel-gif/MemWhale, 154 stars), Memorywhale Evidence (wuisabel-gif/MemWhale, 154 stars) and Gearcoleco Debugging (drhelius/Gearcoleco, 142 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Misakanet Failure Memory?

Ikalus1988 (a GitHub user) maintains it in Ikalus1988/MisakaNet, which has 526 GitHub stars. The repository was last updated on October 11, 2026.

Source: Ikalus1988/MisakaNet on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.