Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mehrad-dm/mastermindnpx agentmods add skills/mehrad-dm/mastermind/lintWrote 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/mehrad-dm/mastermind/lint)<a href="https://agentmods.dev/skills/mehrad-dm/mastermind/lint"><img src="https://agentmods.dev/badge/skills/mehrad-dm/mastermind/lint/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/mehrad-dm/mastermind/lint"><img src="https://agentmods.dev/badge/skills/mehrad-dm/mastermind/lint.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 | $0.00090 | $0.01556 |
| Opus 5.5 | $0.00036 | $0.00622 |
| Sonnet 5.5 | $0.00018 | $0.00311 |
| Haiku 4.5 | $0.00009 | $0.00156 |
Grade A, and why
lint 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 15d 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MasterMind: Lint
Instruction text rots in a specific way: rules accumulate, the same principle gets restated in three layers, and prohibitions pile up long after the model outgrew needing them. Anthropic removed ~80% of Claude Code's system prompt with no measured loss, and named the mechanism of harm: accumulated guardrails produce conflicting instructions, so the model spends its reasoning reconciling them before it can act. This skill finds that drift in MasterMind itself.
It reports. It never edits. Every finding comes back as a proposal you approve or reject, see the guard at the bottom for why that constraint is not negotiable.
Pass A: deterministic, near-free
Run the script; don't do this by hand:
node scripts/lint-brain.mjs # add --strict to exit non-zero on high findings
Run it from the MasterMind clone. An installed brain ships only build-router.mjs and
check-integrity.mjs, not this one: if that's where you are, say so and run Pass B alone rather
than hand-counting.
Counting is not judgment, so it shouldn't depend on a model remembering to do it: and a hand-count drifts between runs, which makes two reports incomparable. The script reports every item below, sorted by severity, with the always-loaded vs on-demand token budget at the top:
- Negative-framing density:
never,don't,do not,avoid,must notper file. Flag files well above the corpus median. (A negative measurably loads the concept it forbids, so each one should be paying for itself.) - Cross-layer repetition: the same normalized sentence in kernel ↔ core ↔ skill ↔ agent. Two layers is a smell, three is where contradictions come from.
- Near-duplicates within a file: the same rule said twice in different words.
- Size and budget: lines and characters per file, split by always-loaded vs on-demand, with a token estimate. The always-loaded number is the one that matters.
- Stale references:
~/.mastermind/…paths, and skill/agent names, that no longer exist on disk.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 15d ago Changed · +90 tokens per session 8eaf3e85845d
- 1mo ago First seen · 114 lines · 0 tokens per session scan A c4c1e712a7ef
lint is a skill published in the GitHub repository mehrad-dm/mastermind (23 stars, last pushed 6d ago), licensed MIT. It adds 90 tokens to every session and 1,556 once invoked, about $0.0004 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.
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