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 commands/arielshad/balagan-agent/researchgit clone --depth 1 https://github.com/arielshad/balagan-agentWrote 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/arielshad/balagan-agent/research)<a href="https://agentmods.dev/commands/arielshad/balagan-agent/research"><img src="https://agentmods.dev/badge/commands/arielshad/balagan-agent/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 | $0.00008 | $0.00247 |
| Opus 5 | $0.00004 | $0.00123 |
| Sonnet 5 | $0.00002 | $0.00049 |
| Haiku 4.5 | $0.00001 | $0.00025 |
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 4d 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.
This is a copy
100% identical to research — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Research the following topic thoroughly: $ARGUMENTS
Research Strategy
-
Break Down the Topic
- Identify 2-4 key subtopics or angles to investigate
- Ensure comprehensive coverage without redundancy
-
Parallel Research
- Spawn researcher subagents for each subtopic
- Each researcher should conduct 3-7 web searches
- Focus on authoritative, recent sources (2024-2025)
-
Source Quality
- Prioritize: academic papers, official docs, reputable news
- Cross-reference claims from multiple sources
- Note any conflicting information
-
Output Requirements
- Save findings to files/research_notes/
- Use clear, descriptive filenames
- Include source URLs for citations
-
Synthesis
- After all research is complete, automatically spawn report-writer
- Create a comprehensive synthesis in files/reports/
Quality Standards
- Minimum 3 sources per subtopic
- Include diverse perspectives
- Flag areas where information is uncertain or conflicting
- Note knowledge gaps for potential follow-up
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.
- 4d ago First seen · 38 lines · 8 tokens per session scan A 2e56ec992b6a
research is a command published in the GitHub repository arielshad/balagan-agent (11 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 247 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
init
Scaffold a new MindBase project (v2 layout). Usage: /mb:init [template] [-- mission ...].
commit
智能生成 Git 提交信息并提交.
pr
Handle the full workflow from current branch state to an open, CI-monitored pull request.
doctor.es
Diagnostica problemas de inferencia LLM en Mac: asiai doctor verifica el estado de los motores, conflictos de puertos, carga de modelos y estado de la GPU.
requirement-review
需求文档多角色评审（requirement-review）：需求文档 → 7-Agent 并行评审 → 重构高质量需求文档（Runtime 受控流程，0-7 阶段状态机）.