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.
git clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/commands/perniemann/pncore/pn-colorize)<a href="https://agentmods.dev/commands/perniemann/pncore/pn-colorize"><img src="https://agentmods.dev/badge/commands/perniemann/pncore/pn-colorize/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/commands/perniemann/pncore/pn-colorize"><img src="https://agentmods.dev/badge/commands/perniemann/pncore/pn-colorize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00033 | $0.00606 |
| Opus 5 | $0.00016 | $0.00303 |
| Sonnet 5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
pn-colorize 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.
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pn-colorize
Start every response with: [pn-command] 🔺
Advanced (palette-hidden). Not in the
/slash palette. Invoked by/pn-design(Color substep),/pn-visual-tweak, or/pn-polish, or directly viaget_command("pn-colorize").
Focused color pass: establish or improve the color system, fix contrast issues, introduce strategic color, or implement dark mode. No layout or font changes — color only.
Flow
1. Context
Check .pncore-design.md for brand personality, visual ambition, and any existing brand colors. If not found, ask: "What's the brand hue or personality? Any existing brand colors to work with?"
2. Mode
Ask (if not clear from context):
- Establish — build a new color system from scratch
- Improve — audit and fix an existing palette (contrast, generic choices, token gaps)
- Dark mode — add dark mode to an existing light system
- Specific fix — address a particular issue (e.g., "fix contrast on the blue button")
3. Audit / Plan
Load get_skill("pn-color-system") and consult [reference/color-and-contrast.md](../skills/frontend/reference/color-and-contrast.md).
For Improve mode, audit:
- Is the color system using OKLCH? If not, flag.
- Are neutrals tinted with brand hue, or pure gray?
- Does the system use primitive + semantic token layers?
- Named anti-patterns present? (AI color palette, pure black/white, gray on color)
- WCAG contrast: body text 4.5:1, UI components 3:1, placeholder text 4.5:1?
- Does the accent color have appropriate rarity (≤10% of visual weight)?
- Is there a defined palette structure (primary, neutral, semantic, surface)?
Output issues with severity. Gate on confirmation before fixing.
4. Implement
Apply changes using OKLCH. Typical outputs:
- CSS custom properties with primitive + semantic layers
- Tinted neutral scale (brand hue applied at chroma 0.005–0.01)
- Dark mode semantic override block
- Fix WCAG violations with specific new values
5. Summary
Colors changed, contrast ratios verified, dark mode coverage if applicable.
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.
- 8d ago First seen · 62 lines · 33 tokens per session scan A 4015a1042ad8
pn-colorize is a command published in the GitHub repository perniemann/pnCore (0 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 606 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.
Other commands, from other repositories
t800-start
A single command for creating or updating development helpers such as rules, skills, commands, subagents, and hooks. It can target a plugin, the current project, or shared settings.
t800-fix
A command for making a narrow, predefined fix to existing agents, skills, commands, rules, or hooks. A fix-pack is a file listing the exact changes to make.
t800-loop
A semi-manual workflow for reviewing the results of a previous development run and preparing a queue of fixes. HITL means a human reviews or approves the queued work before fixes are applied in batches.
t800-audit
A command for auditing a Cursor setup, including its rules, skills, commands, agents, and plugins. It identifies which parts are useful and which consume unnecessary context, meaning the instructions an AI reads before working.
t800-onboard
A command for newcomers that explains what is installed in Cursor globally and in the current project, plus what the T-800 team can do.
t800-cloud-hub
A command for setting up a Cloud Hub and its client automation package, including instructions, a data format, and a test report.