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 jubscodes/get-shit-pretty --skill gsp-brand-researchgit clone --depth 1 https://github.com/jubscodes/get-shit-prettyWrote 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/jubscodes/get-shit-pretty/gsp-brand-research)<a href="https://agentmods.dev/skills/jubscodes/get-shit-pretty/gsp-brand-research"><img src="https://agentmods.dev/badge/skills/jubscodes/get-shit-pretty/gsp-brand-research/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/jubscodes/get-shit-pretty/gsp-brand-research"><img src="https://agentmods.dev/badge/skills/jubscodes/get-shit-pretty/gsp-brand-research.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 | $0.00000 | $0.00926 |
| Opus 5 | $0.00000 | $0.00463 |
| Sonnet 5 | $0.00000 | $0.00185 |
| Haiku 4.5 | $0.00000 | $0.00093 |
Grade A, and why
gsp-brand-research 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 11d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prerequisites: /gsp-start must have run first to scaffold .design/branding/{brand}/BRIEF.md and config.json. Invoking this skill cold (no brand directory) exits with a one-line "run /gsp-start first" prompt — it does not bootstrap.
Input: .design/branding/{brand}/BRIEF.md
Output: .design/branding/{brand}/discover/ (4 chunks + INDEX.md)
Agent: gsp-brand-researcher
Resolve brand from .design/branding/ (one → use it, multiple → ask). Set BRAND_PATH.
Read {BRAND_PATH}/BRIEF.md. If missing, tell user to run /gsp-start first.
Read {BRAND_PATH}/config.json for brand_mode.
Step 2: Confirm research scope
Load BRIEF.md personas and competitive landscape. If {BRAND_PATH}/audit/ exists, also load audit/evolution-map.md and audit/market-fit.md.
Present a compact research plan, then use AskUserQuestion:
- Looks good — "Start research with this scope"
- Adjust — "I want to add competitors or shift emphasis"
Step 2.5: Pre-fetch competitor sites (background)
While preparing the agent context, use WebFetch with run_in_background: true for each competitor URL or website found in BRIEF.md's competitive landscape. This warms the cache so the researcher agent has content ready instead of fetching sequentially during research.
What ships with it
2 files 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.
- 11d ago First seen · 92 lines · 0 tokens per session scan A 638a22eb694e
gsp-brand-research is a skill published in the GitHub repository jubscodes/get-shit-pretty (54 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 926 tokens. 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
opencli-usage
Use at the start of any OpenCLI session — this is the top-level map of what opencli can do, how to discover adapters, what flags and output formats are universal, and which specialized skill to load next. Point here when an agent asks "what can opencli do?" or "how do I find the right command?".
opencli-sitemap-author
Use when creating or maintaining OpenCLI site sitemaps: agent-facing navigation, page-state, action, workflow, API-reference, pitfall, and fallback knowledge for a website. Use after browser exploration discovers durable site context, when a sitemap is stale, or when promoting local site knowledge into the repo.
opencli-browser-sitemap
Use when driving a website with opencli browser and sitemap context is available, requested, or needed to avoid blind navigation. Guides agents to consume site sitemap files lazily, choose adapter/browser fallback paths, resume from state signatures, and mark stale sitemap entries without trusting them over live…
antv-x6-editor
A skill for creating and troubleshooting interactive diagrams with AntV X6, a JavaScript engine for editors made of connected nodes and lines. It supports diagram types such as flowcharts, dependency graphs, entity-relationship diagrams, and organization charts.
gpt-vis
A chart-generation tool that recommends visual formats for data and produces either chart settings or runnable code. It uses GPT-Vis, a library for rendering data visualisations.
infographic-creator
Create beautiful infographics based on given text content. Use when users request to create infographics.