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/jansenanalytics/claudex/deep-researchnpx skills add JansenAnalytics/claudex --skill deep-researchgit clone --depth 1 https://github.com/JansenAnalytics/claudexWhat 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 | $0.00030 | $0.00333 |
| Opus 5 | $0.00015 | $0.00167 |
| Sonnet 5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
deep-research scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. **Search multiple sources** for each sub-question using Bash + curl What it actually says
Deep Research Skill
When given a research task:
- Decompose the question into 3-5 sub-questions
- Search multiple sources for each sub-question using Bash + curl
- Cross-reference findings across sources
- Synthesize into a structured report with:
- Executive summary (3-5 sentences)
- Key findings (bullet points)
- Detailed analysis (organized by sub-topic)
- Sources cited
- Confidence level and caveats
Search Methods
# DuckDuckGo (no API key needed)
curl -s "https://html.duckduckgo.com/html/?q=QUERY" | grep -oP '(?<=<a rel="nofollow" class="result__a" href=").*?(?=")'
# Fetch readable content from URL
curl -sL URL | sed 's/<[^>]*>//g' | head -200
# Wikipedia API
curl -s "https://en.wikipedia.org/api/rest_v1/page/summary/TOPIC"
Quality Standards
- Never present a single source as definitive
- Flag conflicting information explicitly
- Distinguish facts from opinions
- Include dates/recency of information
- Rate overall confidence: HIGH / MEDIUM / LOW
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.
- 3d ago First seen · 41 lines · 30 tokens per session scan A 44ad217ca8f9
deep-research is a skill published in the GitHub repository JansenAnalytics/claudex (5 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 333 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
Core Refinery
Find the core that runs through everything — the ideas that survive across all your sources.
Principle Synthesizer
Synthesize invariant principles from 3+ sources — find the core that survives across all expressions.
synthesis
Multi-source research synthesis — aggregate and compare 3+ sources or any source >5KB using sub-agent dispatch and SharedState.
Web Research Report
Synthesize fetched web sources into a structured research report on a topic: key findings, themes, tradeoffs, and a recommendation, with citations. Use for web research, literature review, and report writing.
gsd-research-synthesizer
Synthesizes research outputs from parallel researcher agents into SUMMARY.md. Spawned by /gsd:new-project after 4 researcher agents complete.
tavily-research
Deep multi-source research using Tavily Research API.