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 agentmods add skills/haoruilee/oh-my-mcode/researchnpx skills add haoruilee/oh-my-mcode --skill researchgit clone --depth 1 https://github.com/haoruilee/oh-my-mcodeWrote 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/haoruilee/oh-my-mcode/research)<a href="https://agentmods.dev/skills/haoruilee/oh-my-mcode/research"><img src="https://agentmods.dev/badge/skills/haoruilee/oh-my-mcode/research.svg" alt="Measured on agentmods" 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 | $0.00107 | $0.00438 |
| Opus 5 | $0.00053 | $0.00219 |
| Sonnet 5 | $0.00021 | $0.00088 |
| Haiku 4.5 | $0.00011 | $0.00044 |
Grade A, and why
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 3d 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.
What it actually says
Research
Explorer only. Load agents/explorer.md. Stop after DISCOVER. No builder. No EXECUTE.
中文名：仅调研。
Inputs
- Topic / question.
- Workspace root.
- Prefer
oh-my-mcode research "<topic>"so the note lands in.minimax/runs/<id>/research.md.
Procedure
- Create a run for the topic (or load the named run).
set-phase --phase DISCOVER. Search read-only. Diagnostic commands only.- Write
research.mdvia the CLI orwrite-planis the wrong file — use the research artifact. Appendresearch_completed. - Do not start PLAN/EXECUTE. Do not edit product files.
Output contract
- A research note on disk. Paths, commands, risks.
- Phase remains DISCOVER.
Failure handling
- Missing tests: record that as a risk. Do not invent coverage.
- User says "just implement it": hand off to
max.
Examples
User: research how auth tokens are rotated
Discover, write a note, stop.
User: max mode: rotate tokens and prove tests pass
Wrong skill. That is the full loop.
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.
- 3d ago First seen · 52 lines · 107 tokens per session scan A cd018c8283d7
research is a skill published in the GitHub repository haoruilee/oh-my-mcode (51 stars, last pushed 5d ago), licensed MIT. It adds 107 tokens to every session and 438 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…