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/wxhcore/bumblehive/project-summarynpx skills add wxhcore/bumblehive --skill project-summarygit clone --depth 1 https://github.com/wxhcore/bumblehiveWrote 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/wxhcore/bumblehive/project-summary)<a href="https://agentmods.dev/skills/wxhcore/bumblehive/project-summary"><img src="https://agentmods.dev/badge/skills/wxhcore/bumblehive/project-summary.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 | $0.00013 | $0.00071 |
| Opus 5 | $0.00006 | $0.00036 |
| Sonnet 5 | $0.00003 | $0.00014 |
| Haiku 4.5 | $0.00001 | $0.00007 |
Grade A, and why
project-summary 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 4d 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.
What it actually says
Project summary
- Read
references/format.mdfor the required structure. - Run
scripts/count_python_files.pywhen a Python file count is useful. - Fill in
assets/summary-template.mdwith the project findings.
What ships with it
3 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.
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.
- 4d ago First seen · 11 lines · 13 tokens per session scan A 692b133eb4b3
project-summary is a skill published in the GitHub repository wxhcore/bumblehive (9 stars, last pushed 8d ago), licensed Apache-2.0. It adds 13 tokens to every session and 71 once invoked, about $0.0001 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.
Other skills, from other repositories
with-frontmatter
Help an agent inspect a failed trace run, identify likely failure layers, and produce a short audit note.
x-scraper
X (Twitter) 抓取 skill - 通过 agent-browser (CDP) 抓取指定用户推文或首页推荐流,支持关键词过滤、Tab 切换、多格式输出。使用场景:按用户/关键词抓取时间线、查看首页推荐流、生成 RSS/JSON/Markdown。.
html-to-image
HTML 转图片 skill - 将 HTML 文件或内容通过 agent-browser 渲染并截图为图片。适用于生成信息图、社交媒体配图、数据可视化截图等场景。.
skill-creator
Generates Anthropic Skills with complete workflow including GitHub PR creation and local download verification.
beevibe-team-mesh-negotiation
Multi-round negotiation protocol — covers both initiator and peer roles. Use when about to call negotiate(), when receiving a intent block as a peer, or when receiving an 'escalated' sentinel from a blocked respondnegotiate. Covers proposal crafting, counter-strategy, deadlock detection, when to accept early…
dashclaw-governance
Governance behavior for AI agents governed by DashClaw. Teaches the governance protocol: when to call guard (risk thresholds), how to interpret decisions (allow/warn/block/requireapproval), when to record actions, how to wait for approvals, and session lifecycle management. Loads org-specific policies and capabilities…