Borrowing it
Nothing to install: this file belongs to Avarok-Cybersecurity/atlas. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Avarok-Cybersecurity/atlas/main/.claude/skills/measurement-discipline/SKILL.mdgit clone --depth 1 https://github.com/Avarok-Cybersecurity/atlasWrote 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/avarok-cybersecurity/atlas/measurement-discipline)<a href="https://agentmods.dev/skills/avarok-cybersecurity/atlas/measurement-discipline"><img src="https://agentmods.dev/badge/skills/avarok-cybersecurity/atlas/measurement-discipline/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/avarok-cybersecurity/atlas/measurement-discipline"><img src="https://agentmods.dev/badge/skills/avarok-cybersecurity/atlas/measurement-discipline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 24 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00128 | $0.02015 |
| Opus 5.5 | $0.00051 | $0.00806 |
| Sonnet 5.5 | $0.00026 | $0.00403 |
| Haiku 4.5 | $0.00013 | $0.00201 |
Grade A, and why
measurement-discipline scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
timing via curl, nsys cadence, server-attested usage). Discredit fields, not The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 Changed · +9 lines b7a647d55361
- 1mo ago Changed 26338e785c33
- 2mo ago First seen · 115 lines · 128 tokens per session scan A 8770e3bab42d
measurement-discipline is a skill published in the GitHub repository Avarok-Cybersecurity/atlas (712 stars, last pushed 3d ago), licensed AGPL-3.0. It adds 128 tokens to every session and 2,015 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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Prepare a Linux server with NVIDIA or Intel Arc GPUs for neural-network and LLM workloads, or diagnose one that misbehaves. Use when the user asks to set up or prepare a GPU server, install NVIDIA drivers or CUDA on Debian/Ubuntu, bring up Intel Arc (A770, A750, B580, Arc Pro B60/B70) with the i915/xe driver and…
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Review invoices and contracts against accounts-payable policy before human approval.