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 michaeljauk/brain-starter --skill research-spikegit clone --depth 1 https://github.com/michaeljauk/brain-starterWrote 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/michaeljauk/brain-starter/research-spike)<a href="https://agentmods.dev/skills/michaeljauk/brain-starter/research-spike"><img src="https://agentmods.dev/badge/skills/michaeljauk/brain-starter/research-spike/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/michaeljauk/brain-starter/research-spike"><img src="https://agentmods.dev/badge/skills/michaeljauk/brain-starter/research-spike.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 | $0.00063 | $0.01706 |
| Opus 5 | $0.00032 | $0.00853 |
| Sonnet 5 | $0.00013 | $0.00341 |
| Haiku 4.5 | $0.00006 | $0.00171 |
Grade A, and why
research-spike 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 9d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Spike
Runs a structured research spike: gathers real-time community signals via /last30days, synthesizes findings into a comparison matrix, and saves a recommendation note to the brain vault.
Trigger phrases
/research-spike [topic]- "spike on [topic]"
- "research [topic]"
- "evaluate [X] vs [Y]"
- "compare options for [topic]"
- "what should we use for [topic]?"
Input
The user provides:
- Topic (required) — what to research (e.g., "auth providers for Next.js", "Playwright vs Cypress", "vector databases")
- Context (optional) — project constraints, must-haves, dealbreakers
- Candidates (optional) — specific options to compare. If not provided, the skill discovers them during research.
Step-by-step workflow
1. Clarify scope
Before researching, confirm:
- What decision does this inform? (library choice, vendor selection, architecture approach, etc.)
- What project is this for? (check
projects/for active projects — constraints differ per project) - Any known candidates? If the user already has 2-3 options in mind, start there. If not, discovery is part of the research.
- Dealbreakers? (e.g., "must be open source", "needs EU hosting", "no vendor lock-in")
If the user's input already covers these, skip asking and proceed.
2. Run /last30days research
Invoke the last30days skill for the topic. This searches Reddit, X, YouTube, HN, and other sources for community signals from the past 30 days.
/last30days [topic]
For comparison spikes (X vs Y), use the comparison mode:
/last30days [X] vs [Y]
If there are 3+ candidates, run /last30days for the overall topic first, then targeted searches for the top contenders if the initial results don't cover them well enough.
Important: /last30days takes 2-8 minutes. Let the user know it's running.
Raw research output is automatically saved to ~/brain/research/ via the LAST30DAYS_OUTPUT_DIR env var and --save-dir flag. This keeps all research artifacts inside the brain repo.
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.
- 9d ago First seen · 186 lines · 63 tokens per session scan A 6c3c6d66b123
research-spike is a skill published in the GitHub repository michaeljauk/brain-starter (5 stars, last pushed 12d ago), licensed MIT. It adds 63 tokens to every session and 1,706 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 2026-08-31.
Other skills, from other repositories
obsidian-md2wechat
Format the current Obsidian article with the existing md2wechat CLI and return its preview to the Obsidian publishing plugin. Use when the user asks to typeset an Obsidian note for WeChat.
pos-verify
Use this immediately after files are created, edited, moved, deleted, or materially rewritten inside PersonalOS. Verifies that new truth was routed to the correct owner, written in the correct file shape, and still follows POS conventions. Do NOT use for whole-vault deep audits; use system-health-check.
skillify
Use this when {{username}} asks to skillify a repeated workflow, determine whether it deserves a reusable PersonalOS skill, or harden an existing workflow into a tested resolver-reachable capability. Do NOT use for one-off notes, ordinary execution, or already-specified skill authoring; use write-skill.
write-skill
Use this when the user wants to create a new shared PersonalOS skill under skills/ or revise a specified PersonalOS skill and the scope is already clear. Do NOT use for raw workflow capture or deciding whether work should become a skill; use skillify first. Do NOT use for repo-local or agent-local skills unless…
priority-dashboard
Use this to rebuild, inspect, or temporarily steer {{username}}'s current PersonalOS priority dashboard from canonical Actions, Attention Triggers, and owner context. Do NOT use it to create, complete, or independently manage tasks; use task-manager for Action and Trigger lifecycle changes.
log
Use this when a PersonalOS work session, chat outcome, personal reflection, or provided source should be persisted into the modular Daily context and any already-owned canonical files. Do NOT use for single-call processing, single-source knowledge ingestion, Gmail/WhatsApp propagation, or Lexware booking.