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 hdu-ailab/EasyResearch --skill find-skillsgit clone --depth 1 https://github.com/hdu-ailab/EasyResearchWrote 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/hdu-ailab/easyresearch/find-skills)<a href="https://agentmods.dev/skills/hdu-ailab/easyresearch/find-skills"><img src="https://agentmods.dev/badge/skills/hdu-ailab/easyresearch/find-skills/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/hdu-ailab/easyresearch/find-skills"><img src="https://agentmods.dev/badge/skills/hdu-ailab/easyresearch/find-skills.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 | $0.00067 | $0.01303 |
| Opus 5 | $0.00034 | $0.00651 |
| Sonnet 5 | $0.00013 | $0.00261 |
| Haiku 4.5 | $0.00007 | $0.00130 |
Grade A, and why
find-skills 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 12d 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.
This is a copy
83% identical to find-skills — 57 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find Skills
This skill helps you discover and install skills from the open agent skills ecosystem.
When to Use This Skill
Use this skill when the user:
- Asks "how do I do X" where X might be a common task with an existing skill
- Says "find a skill for X" or "is there a skill for X"
- Asks "can you do X" where X is a specialized capability
- Expresses interest in extending agent capabilities
- Wants to search for tools, templates, or workflows
- Mentions they wish they had help with a specific domain (design, testing, deployment, etc.)
What is the Skills CLI?
The Skills CLI (npx skills) is the package manager for the open agent skills ecosystem. Skills are modular packages that extend agent capabilities with specialized knowledge, workflows, and tools.
Key commands:
npx skills find [query] [--owner <owner>]- Search for skills interactively or by keyword, optionally scoped to a GitHub ownernpx skills add <package>- Install a skill from GitHub or other sourcesnpx skills update- Update all installed skills
Browse skills at: https://skills.sh/
How to Help Users Find Skills
Step 1: Understand What They Need
When a user asks for help with something, identify:
- The domain (e.g., React, testing, design, deployment)
- The specific task (e.g., writing tests, creating animations, reviewing PRs)
- Whether this is a common enough task that a skill likely exists
Step 2: Check the Leaderboard First
Before running a CLI search, check the skills.sh leaderboard to see if a well-known skill already exists for the domain. The leaderboard ranks skills by total installs, surfacing the most popular and battle-tested options.
For example, top skills for web development include:
vercel-labs/agent-skills— React, Next.js, web design (100K+ installs each)anthropics/skills— Frontend design, document processing (100K+ installs)
Step 3: Search for Skills
If the leaderboard doesn't cover the user's need, run the find command:
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.
- 12d ago First seen · 142 lines · 67 tokens per session scan A c00eeea0e13e
find-skills is a skill published in the GitHub repository hdu-ailab/EasyResearch (13 stars, last pushed 2d ago), licensed MIT. It adds 67 tokens to every session and 1,303 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to find-skills, differing in 57 lines, and is treated as a copy.
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Sync and manage Overleaf LaTeX projects from the command line. Pull projects locally, push changes back, compile PDFs, and download compile outputs like .bbl files for arXiv submissions. Use when working with LaTeX, Overleaf, academic papers, or arXiv.
ai-research-explore
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explore-run
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with…
explore-code
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together…
run-train
Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized…