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/llv22/autoresearchwitheyes/idea-creatornpx skills add llv22/AutoResearchWithEyes --skill idea-creatorgit clone --depth 1 https://github.com/llv22/AutoResearchWithEyesWrote 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/llv22/autoresearchwitheyes/idea-creator)<a href="https://agentmods.dev/skills/llv22/autoresearchwitheyes/idea-creator"><img src="https://agentmods.dev/badge/skills/llv22/autoresearchwitheyes/idea-creator.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 | $0.00051 | $0.02544 |
| Opus 5 | $0.00026 | $0.01272 |
| Sonnet 5 | $0.00010 | $0.00509 |
| Haiku 4.5 | $0.00005 | $0.00254 |
Grade A, and why
idea-creator 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 5d 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Idea Creator
Generate publishable research ideas for: $ARGUMENTS
Overview
Given a broad research direction from the user, systematically generate, validate, and rank concrete research ideas. This skill composes with /research-lit, /novelty-check, and /research-review to form a complete idea discovery pipeline.
Constants
All constants (PILOT_MAX_HOURS, PILOT_TIMEOUT_HOURS, MAX_PILOT_IDEAS, MAX_TOTAL_GPU_HOURS, REVIEWER_MODEL) are defined in the project's CLAUDE.md. Read them from there before proceeding.
💡 Override via argument, e.g.,
/idea-creator "topic" — pilot budget: 4h per idea, 20h total.
Workflow
Phase 1: Landscape Survey (5-10 min)
Map the research area to understand what exists and where the gaps are.
-
Scan local paper library first: Check
papers/andliterature/in the project directory for existing PDFs. Read first 3 pages of relevant papers to build a baseline understanding before searching online. This avoids re-discovering what the user already knows. -
Search recent literature using WebSearch:
- Top venues in the last 2 years (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.)
- Recent arXiv preprints (last 6 months)
- Use 5+ different query formulations
- Read abstracts and introductions of the top 10-15 papers
-
Build a landscape map:
- Group papers by sub-direction / approach
- Identify what has been tried and what hasn't
- Note recurring limitations mentioned in "Future Work" sections
- Flag any open problems explicitly stated by multiple papers
-
Identify structural gaps:
- Methods that work in domain A but haven't been tried in domain B
- Contradictory findings between papers (opportunity for resolution)
- Assumptions that everyone makes but nobody has tested
- Scaling regimes that haven't been explored
- Diagnostic questions that nobody has asked
Phase 2: Idea Generation (brainstorm with external LLM)
Use the external LLM via Codex MCP for divergent thinking. Enable web search
(tools.web_search) so brainstorming is grounded in current literature — this is light
search-augmented reasoning, not a dedicated deep-research pass (that is gpt-pro's job).
Web search is set on this initial call, so the thread inherits it for the later
codex-reply critical-review step.
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.
- 5d ago First seen · 234 lines · 51 tokens per session scan A 8a334979f802
idea-creator is a skill published in the GitHub repository llv22/AutoResearchWithEyes (5 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 2,544 once invoked, about $0.0003 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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