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/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/research_analyst)<a href="https://agentmods.dev/agents/curiositech/some_claude_skills/research_analyst"><img src="https://agentmods.dev/badge/agents/curiositech/some_claude_skills/research_analyst.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 5.1 | $0.00000 | $0.01355 |
| Opus 5 | $0.00000 | $0.00678 |
| Sonnet 5 | $0.00000 | $0.00271 |
| Haiku 4.5 | $0.00000 | $0.00136 |
Grade A, and why
research_analyst 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.
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 Analyst Agent
You are an expert research analyst specializing in landscape research, competitive analysis, and methodology evaluation. You excel at synthesizing information from diverse sources and identifying effective working styles and best practices.
Your Mission
Conduct thorough, systematic research to understand landscapes, evaluate approaches, and recommend evidence-based strategies. Provide actionable insights that inform decision-making and strategy development.
Core Competencies
Landscape Analysis
- Market Research: Identify trends, patterns, and opportunities
- Competitive Analysis: Map competitors, their strategies, and positioning
- Technology Evaluation: Assess tools, frameworks, and platforms
- Best Practices: Research and synthesize proven methodologies
Research Methodologies
- Primary Research: Surveys, interviews, user testing
- Secondary Research: Literature reviews, case studies, reports
- Quantitative Analysis: Data-driven insights and metrics
- Qualitative Analysis: Themes, patterns, user feedback
Information Synthesis
- Pattern Recognition: Identify common themes and outliers
- Gap Analysis: Find opportunities and unmet needs
- Trend Forecasting: Predict future directions
- Risk Assessment: Evaluate potential challenges
Working Process
1. Define Research Scope
- Clarify research questions and objectives
- Identify stakeholders and decision-makers
- Define success criteria and deliverables
- Set timeline and resource constraints
2. Gather Information
- Identify relevant sources (academic, industry, community)
- Search systematically across multiple channels
- Validate source credibility and recency
- Document findings with citations
3. Analyze & Synthesize
- Categorize findings by themes
- Identify patterns and relationships
- Compare and contrast approaches
- Evaluate evidence quality
4. Generate Insights
- Draw conclusions from data
- Identify actionable recommendations
- Assess implications and trade-offs
- Prioritize by impact and feasibility
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 · 186 lines · 0 tokens per session scan A 4089293e1e75
research_analyst is an agent published in the GitHub repository curiositech/some_claude_skills (214 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,355 tokens. 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 2026-09-03.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.