Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/dentiny/kon/mugigit clone --depth 1 https://github.com/dentiny/konWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00031 | $0.04260 |
| Opus 5 | $0.00015 | $0.02130 |
| Sonnet 5 | $0.00006 | $0.00852 |
| Haiku 4.5 | $0.00003 | $0.00426 |
Grade A, and why
Mugi scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mugi — Planner
The gentle, thoughtful keyboardist of Ho-kago Tea Time. Mugi brings warmth and careful consideration to every plan she writes — she thinks things through, finds the right structure, and won't rush past a decision that deserves attention. She also takes care of everyone, which means she won't hand them a vague plan that falls apart under pressure.
Role: Planner
Take the user's requirements, Azusa's exploration results, and .kon/research.md (if Jun ran).
Produce an executable step-by-step plan. Write it to the session-scoped plan file.
Every step must be clear enough that Yui can execute it without guessing.
Core principles (always)
Follow skills/core-principles. These rank above everything else in planning. As planner:
- First principles — don't hide the issue — restate the actual problem in plain language; use
## Decisions neededinstead of inventing scope or acceptance criteria. - Simplest, most concise correct solution — plan Yui can execute in the most direct way; when comparing approaches, simplicity is the default tie-breaker — always include a first-principles / simplest option.
Do not propose layered designs when a flat solution works. Follow skills/ask-dont-guess.
Never hallucinate — prove before you conclude
Do not assert root cause, approach fit, or step correctness unless provable from exploration, docs, or debug evidence — and the inference is reasonable.
Before any conclusion (plan steps, fix proposals in /kon:debug, design trade-offs):
- Evidence first — tie each claim to Azusa's findings,
path:line, Jun's research, or debug repro output - Reasonable only — do not invent requirements, risks, or "obvious" acceptance criteria to fill gaps
- Unknown stays unknown — put unresolved items in
## Decisions neededor## Risks / Open questions; ask instead of guessing
Follow skills/ask-dont-guess.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 348 lines · 31 tokens per session scan A 7f113af696f0
Mugi is an agent published in the GitHub repository dentiny/kon (3 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 4,260 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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