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 skills/billbuchanan-code/claude-code-power-setup/researchnpx skills add billbuchanan-code/claude-code-power-setup --skill researchgit clone --depth 1 https://github.com/billbuchanan-code/claude-code-power-setupWhat 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 | $0.00016 | $0.00343 |
| Opus 5 | $0.00008 | $0.00171 |
| Sonnet 5 | $0.00003 | $0.00069 |
| Haiku 4.5 | $0.00002 | $0.00034 |
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 yesterday.
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.
What it actually says
Deep Research Skill
Perform deep research on a given topic by combining web search, codebase exploration, and synthesis into a comprehensive report.
Process
- Parse the research question from $ARGUMENTS
- Search the web for current information using WebSearch. Run multiple queries with different phrasings to get broad coverage. Use WebFetch to read the most relevant results in detail.
- Explore the local codebase for relevant context using Grep, Glob, and Read. Look for related code, configuration, documentation, and dependencies.
- Synthesize findings into a structured research report that connects web findings with codebase context.
- Include sources, confidence levels, and actionable recommendations for each finding.
Output Format
Structure the output as a Research Report with the following sections:
Executive Summary
A 2-3 sentence overview of the key findings.
Web Findings
Bullet points of what was discovered from web searches, with source URLs.
Codebase Findings
Relevant code, configuration, or documentation found in the local project, with file paths.
Synthesis
How the web findings and codebase findings connect. Identify gaps, risks, or opportunities.
Sources
A numbered list of all sources consulted (URLs, file paths).
Recommended Next Steps
Actionable items ranked by priority, with confidence level (High / Medium / Low) for each recommendation.
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.
- yesterday First seen · 47 lines · 16 tokens per session scan A 765e8b8fc7cb
research is a skill published in the GitHub repository billbuchanan-code/claude-code-power-setup (2 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 343 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 2026-08-31.
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