Borrowing it
Nothing to install: this file belongs to huangzhonglv/hep-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/huangzhonglv/hep-workflow/main/.agents/skills/hep-idea/SKILL.mdgit clone --depth 1 https://github.com/huangzhonglv/hep-workflowWrote 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/huangzhonglv/hep-workflow/hep-idea)<a href="https://agentmods.dev/skills/huangzhonglv/hep-workflow/hep-idea"><img src="https://agentmods.dev/badge/skills/huangzhonglv/hep-workflow/hep-idea/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/huangzhonglv/hep-workflow/hep-idea"><img src="https://agentmods.dev/badge/skills/huangzhonglv/hep-workflow/hep-idea.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 | $0.00128 | $0.06512 |
| Opus 5.5 | $0.00051 | $0.02605 |
| Sonnet 5.5 | $0.00026 | $0.01302 |
| Haiku 4.5 | $0.00013 | $0.00651 |
Grade C, and why
hep-idea scanned grade C 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 2mo 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
- **User gives a very vague direction** (e.g., "I want to do BSM"): Don't refuse. Consult `references/research-directions.md`, pick 3 diverse sub-topics, and present them as the candidate ideas. How it starts
The opening of the file, as written. The whole thing — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HEP Idea Generator
Generate concrete, publishable research proposals for particle physics phenomenology. The goal is not to produce vague directions, but specific, well-scoped problems that can realistically lead to a paper.
Step 1: Determine the idea source strategy
Before generating ideas, ask the user which approach they want for this session. Present these three strategies and let them pick:
Strategy A - Experiment-driven: Start from a recent experimental anomaly or new data release (e.g., a tension in B-meson measurements, a new LHC search limit, updated neutrino oscillation data). The idea addresses the anomaly with a concrete model or reinterprets new bounds in an existing framework.
Strategy B - Theory-driven: Start from a theoretical model or mechanism and explore its phenomenological consequences in a region that hasn't been fully studied (e.g., extending a known Z' model to the lepton sector, combining a seesaw mechanism with a particular dark matter candidate).
Strategy C - Gap-driven: Start from an open question or gap identified in existing literature (e.g., "nobody has computed the one-loop correction to this process", "the interplay between constraints X and Y in this model class hasn't been mapped out").
If the user has already indicated a preference in their message (e.g., "there's a new anomaly in muon g-2, let's build a model for it"), skip the strategy question and proceed directly.
Step 2: Gather context
Based on the chosen strategy, collect the necessary inputs:
-
Strategy A: Ask what anomaly or dataset. If the user doesn't have one in mind, consult
references/research-directions.mdfor current hot topics and suggest 2-5 recent experimental results worth investigating. -
Strategy B: Ask what model or mechanism to start from. If vague, consult
references/research-directions.mdand suggest 2-5 model frameworks with unexplored phenomenological territory. -
Strategy C: Ask what area to look for gaps. If the user has a previous project (check
workspace/projects/for completed projects), offer to read its conclusions and derive follow-up questions from there.
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .DS_Store 8.0 KB
- references/benchmarks-json-contract.md 2.5 KB
- references/calc-tasks-json-contract.md 2.6 KB
- references/constraints-data-json-contract.md 4.5 KB
- references/manifest-json-contract.md 4.7 KB
- references/model-spec-json-contract.md 2.7 KB
- references/research-directions.md 10 KB
- scripts/init_project_skeleton.py 3.4 KB runs code
- templates/benchmarks.example.json 1.4 KB
- templates/calc-tasks.example.json 2.0 KB
- templates/constraints-data.example.json 2.8 KB
- templates/manifest.example.json 1.9 KB
- templates/model-spec.example.json 2.4 KB
- templates/proposal.md.tmpl 5.4 KB
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.
- 2mo ago First seen · 495 lines · 128 tokens per session scan C d687125eb188
hep-idea is a skill published in the GitHub repository huangzhonglv/hep-workflow (9 stars, last pushed 3mo ago), licensed MIT. It adds 128 tokens to every session and 6,512 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
hep-idea compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| hep-ideahuangzhonglv/hep-workflow | Skill | 9 | 3mo ago | MIT | C | 128 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |