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/vinnie357/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/commands/vinnie357/claude-skills/research)<a href="https://agentmods.dev/commands/vinnie357/claude-skills/research"><img src="https://agentmods.dev/badge/commands/vinnie357/claude-skills/research/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/commands/vinnie357/claude-skills/research"><img src="https://agentmods.dev/badge/commands/vinnie357/claude-skills/research.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 | $0.00008 | $0.00879 |
| Opus 5 | $0.00004 | $0.00439 |
| Sonnet 5 | $0.00002 | $0.00176 |
| Haiku 4.5 | $0.00001 | $0.00088 |
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 9d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research a topic and create multi-file documentation for planning, understanding, and working with the subject.
Document Creation:
- Directory Structure: Creates
research/<category>/<topic>/ - File Generation: Produces
overview.md,troubleshooting.md, and optional guides - Planning Focus: Helps understand topics before implementation
- Reference Material: Creates searchable knowledge base
Features:
- Automatic Complexity Assessment: Evaluates topic complexity (1-10 scale)
- Thinking Mode Selection: Standard/Extended/Deep based on complexity
- Manual Override: Use
--complexity=<level>to force thinking depth - Structured Content: Consistent templates for reliability
- Authoritative Sources: Links to official docs and best practices
- Practical Examples: Real-world usage patterns and code samples
Examples:
/research development docker-compose
# Creates: research/development/docker-compose/
# - overview.md
# - troubleshooting.md
/research infrastructure kubernetes-networking --complexity=high
# Creates: research/infrastructure/kubernetes-networking/
# - overview.md (with deep analysis)
# - troubleshooting.md
# - best-practices.md
/research frontend react-state-management --complexity=medium
# Creates: research/frontend/react-state-management/
# - overview.md
# - troubleshooting.md
# - comparison.md (Redux vs Context vs Zustand)
Document Structure:
overview.md
- Purpose & Use Cases: When and why to use this technology
- Core Concepts: Fundamental principles and architecture
- Implementation Patterns: Common approaches and best practices
- Code Examples: Practical, runnable examples
- Integration Guidelines: How it fits into larger systems
- Performance Considerations: Optimization and scaling
- Security: Common vulnerabilities and protections
- Resources: Official docs, tutorials, community resources
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.
- 9d ago First seen · 111 lines · 8 tokens per session scan A a75282bae389
research is a command published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 879 once invoked, about $0.0000 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.