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/zte-aicloud/co-omnispec/mini-implementnpx skills add ZTE-AICloud/Co-OmniSpec --skill mini-implementgit clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpecWrote 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/zte-aicloud/co-omnispec/mini-implement)<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/mini-implement"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/mini-implement.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 | $0.00032 | $0.00524 |
| Opus 5 | $0.00016 | $0.00262 |
| Sonnet 5 | $0.00006 | $0.00105 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
mini-implement 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 6d 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
步骤
- skill执行开始时间打点记录，开始执行步骤之前，记录本skill的执行时间到
start_time字段：
- 判断当前操作系统，windows还是linux系统;
- 针对不同操作系统运行脚本获取配置
windows:
Get-Date -Format "yyyy-MM-dd HH:mm:ss"linux:date +"%Y-%m-%d %H:%M:%S" - 将获取的时间记录到
start_time
- 获取详设文档名
- 判断当前操作系统，windows还是linux系统;
- linux:仓库根目录下执行脚本(不要从技能目录下找):
${CLAUDE_SKILL_DIR}/scripts/bash/mini-implement-check.sh --json - windows:仓库根目录下执行脚本(不要从技能目录下找):
${CLAUDE_SKILL_DIR}/scripts/powershell/mini-implement-check.ps1 --json- 解析 JSON 获取
FEATURE_DIR. 对于参数中的单引号如 "I'm Groot", 使用转义语法: 例如 'I'''m Groot'(或尽可能使用双引号: "I'm Groot").
- 解析 JSON 获取
-
基于
FEATURE_DIR目录下的任务文档，修改代码，按顺序实现每个Task，确保每个修改点已经完成。 -
每完成一个任务后，需在任务文档中将该任务项标记为已完成状态，即把复选框标记从 - [ ] 改为 - [x]（Markdown checkbox 语法），以便追踪整体进度。
评审
- 使用 mini-implement-review 子代理评审当前修改的代码。
- 子代理运行结束后，读取子代理生成的评审文件 FEATURE_DIR/review-result.md 。
- 如果有评审意见，按照评审意见修改代码，然后再执行
1. 使用 mini-implement-review 子代理评审当前修改的代码。 - 如果没有评审意见，则结束本SKILL。
记录本skill的运行日志信息
执行runlog-record skill，请将前面获取到的start_time的值作为参数传入runlog-record skill
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.
- 6d ago First seen · 34 lines · 32 tokens per session scan A aa9afecfafd2
mini-implement is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (54 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 524 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.
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