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/commands/viktorbezdek/skillstack/start)<a href="https://agentmods.dev/commands/viktorbezdek/skillstack/start"><img src="https://agentmods.dev/badge/commands/viktorbezdek/skillstack/start/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/viktorbezdek/skillstack/start"><img src="https://agentmods.dev/badge/commands/viktorbezdek/skillstack/start.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 | $0.00041 | $0.00876 |
| Opus 5.5 | $0.00016 | $0.00350 |
| Sonnet 5.5 | $0.00008 | $0.00175 |
| Haiku 4.5 | $0.00004 | $0.00088 |
Grade A, and why
start 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a brainstorm-swarm session on the topic provided in $ARGUMENTS.
If $ARGUMENTS is empty, ask the user what they want to brainstorm in one sentence.
Workflow
Follow the brainstorm-swarm plugin's three skills in order:
1. swarm-protocol — choose the persona subset
Load swarm-protocol skill. Pick the persona subset (4-8 of the canonical 12) appropriate to the decision type. Use the default-by-decision-type table from references/invocation-patterns.md.
Show the user the proposed subset with rationale. Get sign-off before spawning. Allow the user to add/remove personas (they may also request a custom persona — invoke the custom-personas skill if so).
2. interview-facilitation — design the prompts
Load interview-facilitation skill. Construct the Phase 1 prompt:
- One-sentence topic framing
- 100-300 words of context (background, constraints, the specific question)
- Length budget: under 400 words per persona
Same prompt body goes to every persona; the persona's subagent type loads their voice.
3. swarm-protocol — spawn in parallel
⛔ Single message, multiple Task() calls. Sequential spawning collapses the swarm. All Task() invocations for the chosen subset go in ONE message:
Task(subagent_type="brainstorm-swarm:pm", description="...", prompt="...")
Task(subagent_type="brainstorm-swarm:engineer", description="...", prompt="...")
Task(subagent_type="brainstorm-swarm:designer", description="...", prompt="...")
[etc. for the chosen subset]
4. swarm-synthesis — produce the artifact
Load swarm-synthesis skill. Once all personas have returned, produce the standard artifact:
- Personas in the swarm (with rationale)
- Consensus (what 3+ personas agreed on)
- Dissent (substantive disagreements with underlying questions)
- Open questions (with "what evidence would resolve" notes)
- Recommended next move (with alternative)
- Per-persona contributions (collapsed)
Preserve dissent. Don't force consensus.
5. Optional second round (Phase 2)
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 · 89 lines · 41 tokens per session scan A aada7fa68b19
start is a command published in the GitHub repository viktorbezdek/skillstack (14 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 876 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 commands, from other repositories
translate-audit
Read-only audit across every existing language of a project. Two modes. DEFAULT (coverage) finds where translations are missing or incomplete — it builds the union of all keys/strings/pages present across all locales (including the source), then for each language lists what it is missing, which other languages DO have…
translate-init
Guided, step-by-step builder for a project's translation.config.json — the setup step before /translate. Walks the operator through every option ONE AT A TIME with a plain-language explanation of what it does and what to fill, pre-filling smart defaults it detects from the project (source language, formats, existing…
translate-add-locale
Scaffold a brand-new interface LANGUAGE (locale) end-to-end in a codebase so the build goes green with source-language placeholders, then hand off to /translate for the real translation. Wires the locale into the type/registry (locale list, HTML lang, OG locale), clones the message catalog to a new file, mirrors any…
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.