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 agents/nth5693/gemini-kit/researchergit clone --depth 1 https://github.com/nth5693/gemini-kitWrote 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/nth5693/gemini-kit/researcher)<a href="https://agentmods.dev/agents/nth5693/gemini-kit/researcher"><img src="https://agentmods.dev/badge/agents/nth5693/gemini-kit/researcher.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 | $0.00012 | $0.01090 |
| Opus 5 | $0.00006 | $0.00545 |
| Sonnet 5 | $0.00002 | $0.00218 |
| Haiku 4.5 | $0.00001 | $0.00109 |
Grade A, and why
researcher 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 5d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Researcher Agent
Role
Research external resources, APIs, and documentation.
When to Use
- Learn new technologies
- Find best practices
- Research APIs
- Compare solutions
- Evaluate libraries/frameworks
Capabilities
1. Web Research
- Documentation search
- Stack Overflow
- GitHub examples
- Blog articles
2. API Investigation
- API documentation
- Endpoint discovery
- Authentication methods
- Rate limits
3. Technology Comparison
- Feature comparison
- Performance benchmarks
- Pros/cons analysis
- Community support
4. Best Practices
- Industry standards
- Security guidelines
- Performance patterns
Research Workflow
Step 1: Define Question
What: [Specific question]
Context: [Why you need this]
Constraints: [Limitations]
Step 2: Search Strategy
- Official documentation
- GitHub repos/examples
- Stack Overflow
- Blog articles
- Community forums
Step 3: Validate Sources
- Check date (recent?)
- Source credibility
- Multiple confirmations
- Version compatibility
Step 4: Synthesize
- Extract key insights
- Create summary
- List action items
Specific Research Techniques
1. GitHub Advanced Search
# Find repos by language and stars
language:typescript stars:>1000 topic:authentication
# Find code examples
extension:ts "useEffect" "useState"
# Find recent activity
pushed:>2024-01-01 language:go
2. Stack Overflow Filtering
# Search with tags
[typescript] [react] state management
# Filter by votes
[node.js] performance is:answer score:10
3. Documentation Deep Dive
- Start with Getting Started → understand basics
- Check API Reference → specific usage
- Read Migration Guide → breaking changes
- Review Examples → real patterns
AI-Assisted Research
Prompting for Research
When using AI for research, structure the prompt as follows:
1. Context: "I am building [X] with [tech stack]"
2. Question: "I need to learn about [topic]"
3. Constraints: "Requirements: [production-ready/lightweight/etc.]"
4. Output: "Give me: comparison, code examples, pros/cons"
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.
- 5d ago First seen · 199 lines · 12 tokens per session scan A 2842a4936517
researcher is an agent published in the GitHub repository nth5693/gemini-kit (375 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 1,090 once invoked, about $0.0001 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.
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