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 skills add lofcz/LLMTornado --skill research-synthesis-workflowgit clone --depth 1 https://github.com/lofcz/LLMTornadoWrote 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/skills/lofcz/llmtornado/research-synthesis-workflow)<a href="https://agentmods.dev/skills/lofcz/llmtornado/research-synthesis-workflow"><img src="https://agentmods.dev/badge/skills/lofcz/llmtornado/research-synthesis-workflow/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/skills/lofcz/llmtornado/research-synthesis-workflow"><img src="https://agentmods.dev/badge/skills/lofcz/llmtornado/research-synthesis-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.00252 |
| Opus 5 | $0.00011 | $0.00126 |
| Sonnet 5 | $0.00004 | $0.00050 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
Research Synthesis Workflow 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 13d 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.
What it actually says
Research synthesis workflow
Copy this checklist and track your progress:
Research Progress:
- [ ] Step 1: Read all source documents
- [ ] Step 2: Identify key themes
- [ ] Step 3: Cross-reference claims
- [ ] Step 4: Create structured summary
- [ ] Step 5: Verify citations
Step 1: Read all source documents
Review each document in the sources/ directory. Note the main arguments and supporting evidence.
Step 2: Identify key themes
Look for patterns across sources. What themes appear repeatedly? Where do sources agree or disagree?
Step 3: Cross-reference claims
For each major claim, verify it appears in the source material. Note which source supports each point.
Step 4: Create structured summary
Organize findings by theme. Include:
- Main claim
- Supporting evidence from sources
- Conflicting viewpoints (if any)
Step 5: Verify citations
Check that every claim references the correct source document. If citations are incomplete, return to Step 3.
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.
- 13d ago First seen · 39 lines · 22 tokens per session scan A 28fad8af9b72
Research Synthesis Workflow is a skill published in the GitHub repository lofcz/LLMTornado (639 stars, last pushed 25d ago), licensed MIT. It adds 22 tokens to every session and 252 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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