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 echoVic/blade-code --skill skills-and-custom-commandsgit clone --depth 1 https://github.com/echoVic/blade-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/echovic/blade-code/skills-and-custom-commands)<a href="https://agentmods.dev/skills/echovic/blade-code/skills-and-custom-commands"><img src="https://agentmods.dev/badge/skills/echovic/blade-code/skills-and-custom-commands/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/echovic/blade-code/skills-and-custom-commands"><img src="https://agentmods.dev/badge/skills/echovic/blade-code/skills-and-custom-commands.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 | $0.00142 | $0.02811 |
| Opus 5.5 | $0.00057 | $0.01124 |
| Sonnet 5.5 | $0.00028 | $0.00562 |
| Haiku 4.5 | $0.00014 | $0.00281 |
Grade A, and why
knowledge-extension-ecosystem-skills-and-custom-commands scanned grade A with 1 finding 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 1mo 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- 自定义命令的 `!` Shell 嵌入由 `execSync` 在正文送给模型前直接执行，不经过 ToolExecutor 的常规工具权限、Hook 和调度；其安全前提是命令来源本身已受信(`packages/cli/src/slash-commands/custom/CustomCommandExecutor.ts`) How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Module Structure
Skills 与自定义命令共享“Markdown + frontmatter”的扩展形态，但加载与执行模型不同： Skills 启动时只暴露元数据并按需读取正文，命令发现时即读取正文并在调用时展开动态内容。
Directory Layout
packages/cli/src/skills/— Skill 解析、发现、安装、元数据注入与注册表packages/cli/src/slash-commands/custom/— 自定义命令发现、解析、执行与注册表packages/cli/src/tools/builtin/system/skill.ts— 模型调用 Skill 的工具适配packages/cli/src/tools/builtin/system/slashCommand.ts— 模型调用自定义命令的工具适配.blade/skills/— 当前仓库的项目级 Skills.blade/commands/— 当前仓库的项目级自定义命令
Key Entry Points
SkillRegistry.initialize()inpackages/cli/src/skills/SkillRegistry.ts— 按来源优先级发现 Skill 元数据SkillRegistry.loadContent()inpackages/cli/src/skills/SkillRegistry.ts— 调用时加载完整 Skill 正文CustomCommandRegistry.initialize()inpackages/cli/src/slash-commands/custom/CustomCommandRegistry.ts— 建立 Workspace 命令视图CustomCommandRegistry.executeCommand()inpackages/cli/src/slash-commands/custom/CustomCommandRegistry.ts— 展开命令正文snapshotWorkspaceAgentResources()inpackages/cli/src/agent/resources/WorkspaceAgentResources.ts— 将两类注册表冻结到 Session
API Surface
SkillRegistry
initialize()— 安装默认 Skill fallback、扫描来源并返回发现错误loadContent(name)— 对文件系统 Skill 延迟重读SKILL.md，内置 Skill 走内存内容getModelInvocableSkills()— 排除disable-model-invocationgetUserInvocableSkills()— 仅返回user-invocable: truegenerateAvailableSkillsList()— 生成稳定排序、描述有界的 Prompt 元数据snapshot()— 深拷贝元数据和插件 Skill，形成 Session 私有视图
CustomCommandRegistry
initialize(workspaceRoot)— 发现命令并按 Workspace Trust 过滤项目来源executeCommand(name, context)— 执行参数、Shell 和文件引用展开executePluginCommand(name, context)— 将 namespaced plugin command 适配为普通命令执行generateCommandListDescription(charBudget)— 为SlashCommand工具生成有预算的目录snapshot()— 复制命令、插件命令和最近发现结果
Loaders
loadSkillMetadata()/loadSkillContent()— 分离 Skill 元数据与正文读取(packages/cli/src/skills/SkillLoader.ts)CustomCommandLoader.discover()— 递归读取四个命令来源(packages/cli/src/slash-commands/custom/CustomCommandLoader.ts)
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.
- 1mo ago First seen · 120 lines · 142 tokens per session scan A 81587e82d5bc
knowledge-extension-ecosystem-skills-and-custom-commands is a skill published in the GitHub repository echoVic/blade-code (181 stars, last pushed 3d ago), licensed MIT. It adds 142 tokens to every session and 2,811 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
clinical-reports
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation…
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading…
gget
Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
immunology-assays
Computational analysis of immunology experimental data. ATAC-seq differential accessibility, immune cell tracking from microscopy, ELISA data processing with 4-parameter logistic fitting, immunohistochemistry quantification, antibody titer analysis, and cell cycle phase duration estimation. For flow cytometry use…
molecular-cloning
Molecular cloning simulation and design. PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation. For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database.
geo-database
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.