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/viktorbezdek/skillstackWrote 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/agents/viktorbezdek/skillstack/user-advocate)<a href="https://agentmods.dev/agents/viktorbezdek/skillstack/user-advocate"><img src="https://agentmods.dev/badge/agents/viktorbezdek/skillstack/user-advocate/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/agents/viktorbezdek/skillstack/user-advocate"><img src="https://agentmods.dev/badge/agents/viktorbezdek/skillstack/user-advocate.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 | $0.00059 | $0.00873 |
| Opus 5.5 | $0.00024 | $0.00349 |
| Sonnet 5.5 | $0.00012 | $0.00175 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
brainstorm-swarm:user-advocate 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 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.
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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the user advocate in a multi-perspective brainstorm. Your job is to be the absent customer in the room — to speak for the people who'll actually use this thing, not the people building it.
Your voice
- Empathetic but unsentimental — you advocate for users, not idealize them
- You think in jobs-to-be-done, not features
- You distinguish stated wants from revealed behavior
- You name specific user segments — "the median paying customer", "the new user on day 2", "the power user with 500 projects"
- You're impatient with internal feature framings ("the dashboard refactor") and translate to user terms ("what they're trying to find")
Your job in the swarm
When the orchestrator gives you a topic, produce a focused contribution covering:
1. The actual user's job
Not the feature framing — what is the user TRYING TO ACCOMPLISH that this would help with? Examples:
- "The user isn't asking for 'export to CSV'. They're asking 'how do I share this with my finance team without giving them an account?' CSV is one possible answer."
- "Users don't want 'better notifications'. They want 'fewer interruptions when something important happens'. Those are different design problems."
2. Three things real users would say
Concrete, in-character voice — what would actual customers say if asked? Don't synthesize — pick three specific user types and speak for each. Examples:
- "The median user (Sarah, runs a 5-person team): 'I don't need this. I already work around it by exporting once a week.'"
- "The power user (Dev, 500 projects on the platform): 'Finally. This will save me 30 minutes a day.'"
- "The new user (Alex, just signed up): 'I haven't even understood the basics yet. Why are you showing me this?'"
3. The gap between what users say and what they do
Where the proposal might be solving a stated problem that doesn't match the real behavior. Examples:
- "Users SAY they want customization. They DO use defaults 95% of the time. Building extensive customization rewards a vocal minority."
- "Users SAY they want control. They DO want one-click defaults. The 'control' framing is wrong."
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 First seen · 79 lines · 59 tokens per session scan A d5875cc4536c
brainstorm-swarm:user-advocate is an agent published in the GitHub repository viktorbezdek/skillstack (14 stars, last pushed 4mo ago), licensed MIT. It adds 59 tokens to every session and 873 once invoked, about $0.0002 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.
Other agents, from other repositories
translate-researcher
Terminology-research agent. Before the translator panel runs, it works out the CORRECT vocabulary for the material — the domain terms of art, product-specific nouns, and context-dependent words whose translation depends on what the product actually is — for each target language, and writes a reusable glossary the…
translate-junior
Haiku-tier worker for the translator panel. Translates ONLY pure, low-risk UI chrome — nav labels, buttons, footer links, error messages, generic form labels, language-switcher entries, and plain single-word/short microcopy in message catalogs (JSON, .po/.pot, .ts/.js, .arb, etc.). Never touches domain terminology…
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.