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/yrris/pro-agent/github-deep-researchnpx skills add yrris/pro-agent --skill github-deep-researchgit clone --depth 1 https://github.com/yrris/pro-agentWhat 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 | $0.00045 | $0.00594 |
| Opus 5 | $0.00023 | $0.00297 |
| Sonnet 5 | $0.00009 | $0.00119 |
| Haiku 4.5 | $0.00005 | $0.00059 |
Grade A, and why
github-deep-research 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 2d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
1 file 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.
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.
- 2d ago First seen · 36 lines · 45 tokens per session scan A 754a5c502c9c
github-deep-research is a skill published in the GitHub repository yrris/pro-agent (23 stars, last pushed 1mo ago), with no licence file. It adds 45 tokens to every session and 594 once invoked, about $0.0002 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.
Other skills, from other repositories
readme-generate
從原始碼分析自動生成雙語 README。當使用者請求為專案建立 README、需要從程式碼庫生成 README.md（英文）和 README.zh.md（中文）、或希望為其函式庫/套件建立一致的多語言文件時使用。.
extension-upload
Package a script tool under /.config/agenvoy/tools/script/ into a tar.gz and publish to pkg.agenvoy.com registry. Keyword picker, dep/key detection, config-stored email (ask + lowercase + persist), ask version, email verification gate, multipart upload with downgrade/unique guards.
scheduler-skill-creator
建立並排程定時觸發的 skill。所有新增定時／週期任務、提醒、排程通知的請求必須走此 skill，禁止直接呼叫 schedules(mode=write)（那是 skill 已存在時的時間綁定工具，不該作為新建排程的入口）。 必定觸發的訊息特徵（任一即活化）： 相對延遲：「X 分鐘後」「X 小時後」「稍後」「待會」「等一下」 明確時間：「X 點」「下午 X 點」「明天 X 點」「後天」「YYYY-MM-DD HH:MM」 週期性：「每 X 分鐘」「每小時」「每天」「每週」「每月」「定時」「固定」 提醒 / 通知意圖：「提醒我」「通知我」「告訴我」+ 時間描述 範例觸發訊息：「5 分鐘後提醒我喝水」「每天早上 9 點抓 HN…
skill-creator
Create, edit, improve, or audit AgentSkills. Use when creating a new skill from scratch or when asked to improve, review, audit, tidy up, or clean up an existing skill or SKILL.md file. Also use when editing or restructuring a skill directory.
search-suitable-public-api
Search the curated Agenvoy public API list for an API that fits the current user need or skill context, then chain into the api-tool-add skill to register it under /.config/agenvoy/tools/api/. Triggers when the agent lacks a tool for a data lookup (weather, currency, geocoding, dictionary, etc.), when the user says…
code-reviewer
Analyze project source code and generate optimization suggestions. Use when user wants code review, performance optimization advice, security hardening recommendations, or architecture improvement suggestions.