Munder Difflin is a local multi-agent harness that turns terminal coding CLIs into a coordinated team of agents running on a user's machine. It is for people who want several supported coding agents to communicate, delegate work, retain memory, and operate through a shared office-style interface. The catalogue skills provide workflows for using and coordinating those agents.
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 skills add chaitanyagiri/munder-difflin --skill md-auditgit clone --depth 1 https://github.com/chaitanyagiri/munder-difflinWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chaitanyagiri/munder-difflin/md-audit)<a href="https://agentmods.dev/skills/chaitanyagiri/munder-difflin/md-audit"><img src="https://agentmods.dev/badge/skills/chaitanyagiri/munder-difflin/md-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chaitanyagiri/munder-difflin/md-audit"><img src="https://agentmods.dev/badge/skills/chaitanyagiri/munder-difflin/md-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00085 | $0.00368 |
| Opus 5.5 | $0.00034 | $0.00147 |
| Sonnet 5.5 | $0.00017 | $0.00074 |
| Haiku 4.5 | $0.00009 | $0.00037 |
Grade A, and why
md-audit 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 1mo ago.
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.
What it actually says
Code Audit (read-only)
Perform a read-only code quality scan and return a findings report. Do NOT edit any files.
Steps:
- Scope — identify the primary language and entry points (
package.json,Cargo.toml,go.mod,pyproject.toml, or similar). - Scan — use
GrepandReadto look for:- Unhandled promise rejections / ignored errors
- Hard-coded secrets or credentials (keys, tokens, passwords)
TODO/FIXME/HACKcomments that signal known debt- Dead exports (exported symbols with no in-repo import)
- Obvious type-safety gaps (unchecked
any, missing null guards)
- Report — output a findings list sorted by severity (Critical → High → Medium → Low):
## Audit Report — <project name> ### Critical - [file:line] <description> ### High - ... ### Summary <total count> findings across <file count> files scanned. - Stop after reporting. Do not apply any fixes.
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.
- 1mo ago First seen · 42 lines · 85 tokens per session scan A 64e5ec65d30e
md-audit is a skill published in the GitHub repository chaitanyagiri/munder-difflin (8,862 stars, last pushed 4d ago), licensed MIT. It adds 85 tokens to every session and 368 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
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Dispatch a parallel adversarial verifier wave after any high-stakes sub-agent investigation (code reviews, audits, findings reports, large refactors, gap analyses) — or whenever a sub-agent asserts a claim with high-confidence language, since confidence is a trigger, not a verdict. Use when sub-agent output will drive…
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potpie-debug-memory
Use while debugging or troubleshooting failures, flaky tests, incidents, production alerts, CI failures, local dev setup issues, repeated bugs, prior fixes, failed attempts, and verification history.
oracle
Oracle second-model review: bundle prompts/files, debug, refactor, design.
resolve-review-pr
Review an existing fix PR using the audited repro and full diff, preserving branch and approval rules.
mindos
MindOS: local knowledge assistant & shared KB. Keeps decisions, notes, SOPs, debugging lessons, research findings, preferences across sessions/agents. Core: save notes, search KB, organize files, run workflows, review, append CSV, hand off context, distill lessons. NOT for app source or paths outside KB. Triggers…