Agentero is a local research workspace that connects papers, structured reading material, Markdown notes, and AI agents in one place. Researchers use it to read and annotate PDFs, extract formulas and figures, organize literature, and collaborate with agents on research tasks while keeping context locally. Its catalogue skills and instruction support agent-assisted research workflows in Agentero.
Borrowing it
Nothing to install: this file belongs to poco-ai/Agentero. 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/poco-ai/Agentero/main/.agents/skills/bump/SKILL.mdgit clone --depth 1 https://github.com/poco-ai/AgenteroWrote 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/poco-ai/agentero/bump)<a href="https://agentmods.dev/skills/poco-ai/agentero/bump"><img src="https://agentmods.dev/badge/skills/poco-ai/agentero/bump/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/poco-ai/agentero/bump"><img src="https://agentmods.dev/badge/skills/poco-ai/agentero/bump.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 | $0.00028 | $0.00624 |
| Opus 5.5 | $0.00011 | $0.00250 |
| Sonnet 5.5 | $0.00006 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
bump 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 yesterday.
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
Version Bump
升级 Agentero 的应用版本,并确保桌面安装包、CLI 和发布 tag 使用同一个版本号。
用法
选择此 Skill 后提供目标版本,例如 0.1.3 或 0.1.3-beta.1。
执行规则
-
读取当前工作区状态和所有版本来源。不要丢弃或覆盖与版本升级无关的用户改动。
-
校验目标版本是合法的 SemVer;版本参数缺失或不明确时停止并请求明确版本。
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同步修改以下字段:
package.json的version。src-tauri/tauri.conf.json的version。src-tauri/Cargo.toml的 packageversion。crates/agentero-core/Cargo.toml的 packageversion(agentero_core::http用CARGO_PKG_VERSION拼 User-Agent,必须与主 crate 锁步)。cli/Cargo.toml的 packageversion。crates/agentero-mcp/Cargo.toml的 packageversion(MCPImplementation用CARGO_PKG_VERSION对外报告服务版本,必须与主 crate 锁步)。src-tauri/ios-project.yml的CFBundleShortVersionString与CFBundleVersion。
Android 不需要手动修改:
tauri android build会从tauri.conf.json的version重新生成src-tauri/gen/android/app/tauri.properties(gitignored)中的versionName与versionCode。 -
如果 Cargo manifest 版本变化,运行必要的 Cargo 元数据/检查命令并确认
Cargo.lock没有保留旧的本地 package 版本。 -
检查版本字段全部等于目标版本,并检查
agentero --version的来源仍然是 CLI package version。 -
检查
AGENTS.md和docs/test/release.md中的发布规则仍与实现一致;只有规则变化时才修改文档,不要伪造版本说明或变更日志。 -
运行最小必要验证:
cargo metadata --no-deps --format-version 1,以及适合当前环境的前端类型检查或构建检查。 -
输出修改文件、验证结果和下一步建议。除非用户明确要求,不创建 commit、tag、Release 或 push。
发布前约束
版本 bump 必须先作为独立提交完成,之后才能创建 v<version> tag。tag 去掉 v 后必须与所有上述版本字段一致。
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.
- yesterday Changed · +1 lines 6af74e3be78e
- 1mo ago Changed · +1 lines ab004773ca15
- 1mo ago First seen · 37 lines · 28 tokens per session scan A 2f310cdf3efb
bump is a skill published in the GitHub repository poco-ai/Agentero (1,032 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 624 once invoked, about $0.0001 per session on Opus 5.5. 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
open-code-review
Performs AI-powered code review on Git changes using the ocr CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply…
baby-sit
Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.
git-checkpoint
Use git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.
csv
CSV data processing — view, filter, convert, merge tabular data. Zero barrier — use with x-cmd, Python, or awk. Use for "csv", "data", "table", "spreadsheet", "conversion".
git
Git and code hosting platform management — GitHub, GitLab, Codeberg, Forgejo. Zero barrier — install x-cmd and manage repos from the terminal. Use for "git", "github", "gitlab", "repo", "pull request", "code hosting".
meta-codereview-current-diff
Read the current uncommitted diff, run three independent reviewers (safety + tests-coverage + style) in parallel, then arbitrate a single BLOCK / BLOCKWITHOVERRIDE / PASSWITHNOTES verdict. Use before commit when you want a multi-perspective second-opinion instead of a single-reviewer agent loop.