sfdx-hardis: Skill for Claude Code

.claude/skills/uxlog-usage/SKILL.md

uxlog-usage is a skill for Claude Code from hardisgroupcom/sfdx-hardis. It costs 61 tokens per session (2,506 once invoked), scanned A, original, AGPL-3.0.

Guidance for choosing the right uxLog level and display settings when writing logs in an application. It also covers the matching terminal color, VS Code suppression, and table logging.

In plain words
What is it for?
Use it when adding or changing uxLog calls, selecting action, warning, error, success, or other levels, or displaying log tables.
Why use it?
It helps developers keep log messages consistent and choose whether sensitive or important messages should always be visible.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

This is hardisgroupcom/sfdx-hardis's own configuration. It tells Claude Code how to work on sfdx-hardis itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything sfdx-hardis configures →

Reuse

Borrowing it

Nothing to install: this file belongs to hardisgroupcom/sfdx-hardis. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/hardisgroupcom/sfdx-hardis/main/.claude/skills/uxlog-usage/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/hardisgroupcom/sfdx-hardis

Made for: Claude Code.

Wrote 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.

agentmods badge for uxlog-usage

README.md
[![agentmods](https://agentmods.dev/badge/skills/hardisgroupcom/sfdx-hardis/uxlog-usage.svg)](https://agentmods.dev/skills/hardisgroupcom/sfdx-hardis/uxlog-usage)
Your own site
<a href="https://agentmods.dev/skills/hardisgroupcom/sfdx-hardis/uxlog-usage"><img src="https://agentmods.dev/badge/skills/hardisgroupcom/sfdx-hardis/uxlog-usage.svg" alt="Measured on agentmods" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,506 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

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 →

  • high Privilege Escalation · line 82
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium Prompt Injection · line 29
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 33
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 34
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 37
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
How audits are shown
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.02506
Opus 5 $0.00030 $0.01253
Sonnet 5 $0.00012 $0.00501
Haiku 4.5 $0.00006 $0.00251

Measured 8d ago against content hash 54342bfb44ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

uxlog-usage 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 8d 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.

.claude/skills/uxlog-usage/SKILL.md · 184 lines

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.

Read it on GitHub

Changes

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.

  1. 8d ago First seen · 184 lines · 61 tokens per session scan A 54342bfb44ff

Subscribe to this mod's changes

uxlog-usage is a skill published in the GitHub repository hardisgroupcom/sfdx-hardis (384 stars, last pushed yesterday), licensed AGPL-3.0. It adds 61 tokens to every session and 2,506 once invoked, about $0.0003 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 2026-08-30.

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