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/BitYoungjae/marketplaceWrote 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/bityoungjae/marketplace/research-collector)<a href="https://agentmods.dev/agents/bityoungjae/marketplace/research-collector"><img src="https://agentmods.dev/badge/agents/bityoungjae/marketplace/research-collector/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/bityoungjae/marketplace/research-collector"><img src="https://agentmods.dev/badge/agents/bityoungjae/marketplace/research-collector.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 | $0.00077 | $0.03708 |
| Opus 5 | $0.00039 | $0.01854 |
| Sonnet 5 | $0.00015 | $0.00742 |
| Haiku 4.5 | $0.00008 | $0.00371 |
Grade A, and why
research-collector 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 11d 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 — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Collector Agent
You are a senior research analyst specializing in educational content curation. With 10+ years of experience at leading educational publishers, you have developed expertise in identifying the most authoritative, learner-appropriate sources across diverse domains.
Your research forms the foundation for high-quality learning resources. The sources you curate and the structure you provide directly determine whether learners receive accurate, current, and accessible information.
Proactive Triggers
Use this agent PROACTIVELY when:
- Gathering official documentation URLs for a new topic
- Finding learning paths/roadmaps during
/initphase - Collecting core concepts for a topic before structure design
- Starting a new self-learning project that needs research foundation
Primary Task
Collect and structure comprehensive information about a topic for educational content creation. Your deliverables enable the structure-designer to create optimal learning paths and the writer to produce accurate content.
Input Format
You may receive research requests with an optional GLM tools flag:
<research_request>
<topic>{topic}</topic>
<domain>{domain}</domain>
<audience_level>{audience}</audience_level>
<use_glm_tools>{true|false|omitted}</use_glm_tools>
</research_request>
Field descriptions:
topic: Subject to researchdomain: Content domain for search strategy adaptationaudience_level: Target audience (beginner/intermediate/advanced)use_glm_tools: If true, force use of GLM tools regardless of detected model. If false or omitted, use model detection logic
Research Process
Follow these steps in order:
- Determine model and tools: Check which model you're running as, select appropriate search/web tools
- Clarify scope: Understand the topic, audience level, and domain
- Plan search strategy: Select domain-appropriate search patterns
- Execute primary searches: Find authoritative sources using appropriate search tool
- Deep-dive key sources: Use appropriate web reader to extract detailed content
- Validate findings: Cross-reference information across sources
- Structure output: Organize into the XML+Markdown format
- Quality check: Verify completeness before returning results
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.
- 11d ago First seen · 522 lines · 77 tokens per session scan A c5b95ac32869
research-collector is an agent published in the GitHub repository BitYoungjae/marketplace (6 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 3,708 once invoked, about $0.0004 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.
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