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 chentao326/vibe-code --skill vibe-score-blindgit clone --depth 1 https://github.com/chentao326/vibe-codeWrote 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/chentao326/vibe-code/vibe-score-blind)<a href="https://agentmods.dev/skills/chentao326/vibe-code/vibe-score-blind"><img src="https://agentmods.dev/badge/skills/chentao326/vibe-code/vibe-score-blind.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 5.1 | $0.00077 | $0.00628 |
| Opus 5 | $0.00039 | $0.00314 |
| Sonnet 5 | $0.00015 | $0.00126 |
| Haiku 4.5 | $0.00008 | $0.00063 |
Grade A, and why
vibe-score-blind 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 7d 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
vibe-score-blind — Channel B (blind scorer sub-agent)
⚠️ 子 agent,非用户 skill。只能由 vibe-assess / vibe-bump 通过 Task tool spawn。
Why this exists
主 AI 看过 git log、执行结果、历史复盘。inline 打分 = 被污染。Channel B 用全新 context——只看 task + rubric.md。
Inputs(白名单)
| 必填 | 说明 |
|---|---|
<task-path> |
tasks/.md 全文 |
<rubric-path> |
rubric.md 当前公式 |
仅此两个文件可读。
禁读(hard list)
| 路径 | refusal_code |
|---|---|
.vibe-state.json |
blocked_contaminated_input |
predictions/*.md |
blocked_contaminated_input |
retros/*/ |
blocked_contaminated_input |
codebase-profile.md |
blocked_profile |
| 含"实际/耗时/完成/diff/lint/bug"的文件 | blocked_contaminated_input |
Output(严格 JSON)
{
"dimensions": {
"CS": {"score":4,"confidence":"high","reason":"文件路径和期望行为都写了"},
"CX": {"score":2,"confidence":"high","reason":"仅涉及auth模块"},
"AM": {"score":1,"confidence":"high","reason":"信息完整"},
"TE": {"score":4,"confidence":"medium","reason":"有测试但验收标准偏主观"},
"AQ": {"score":5,"confidence":"high","reason":"代码修复AI强项"}
},
"composite": 6.4,
"input_status": {"rubric_read":true,"task_read":true,"any_other_file_read":false},
"self_check": {"saw_execution_data":false,"any_contamination_signal":false},
"refusal": null
}
主 AI 调用契约
Task prompt 仅含:
Spawn blind assessor sub-agent.
Input: task_path=<path>, rubric_path=rubric.md
Task: 按 rubric.md 打分。返回严格 JSON。不要读 state/predictions/retros。不要询问用户。
调用前自检:grep -Ei '实际|耗时|完成|diff|lint|bug|过去|上次'
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.
- 7d ago First seen · 63 lines · 0 tokens per session scan A 7e1e68d859a0
vibe-score-blind is a skill published in the GitHub repository chentao326/vibe-code (2 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 628 once invoked, about $0.0004 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…