Skills Plugins MCP Prompt Model 博客 我的中心

adr-create

Create a new Architecture Decision Record with sequential numbering and AgentDB registration

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

Get

https://deepseekmodel.com/api/download.php?id=ruvnet-ruflo-plugins-ruflo-adr-skills-adr-create-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name adr-create description Create a new Architecture Decision Record with sequential numbering and AgentDB registration argument-hint <title> allowed-tools mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-query mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search Bash Read Write Edit Grep Glob Create ADR Create a new Architecture Decision Record with the next sequential number, register it in the AgentDB graph, and link it to related ADRs. When to use When a significant architectural decision needs to be recorded -- new technology adoption, API design choices, data model changes, infrastructure decisions, or any cross-cutting concern that affects multiple components. Steps Find next number -- Glob for docs/adr/ADR-*.md and parse existing numbers to determine the next sequential ID (ADR-001, ADR-002, etc.). Create docs/adr/ if it does not exist. Slugify title -- Convert the title argument to a lowercase, hyphen-separated slug (e.g., "Use PostgreSQL for persistence" becomes use-postgresql-for-persistence ). Create ADR file -- Write the file at docs/adr/ADR-NNN-<slug>.md using the standard template: # ADR-NNN: < Title > - **Status** : proposed - **Date** : <today's date YYYY-MM-DD> - **Deciders** : < leave blank for author to fill > - **Tags** : < leave blank > ## Context <!-- What is the issue that motivates this decision? --> ## Decision <!-- What is the change that we are proposing? --> ## Consequences ### Positive - ### Negative - ### Neutral - ## Links Store in AgentDB -- Call mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store with: key: mem:ADR-NNN tier: semantic value: a JSON-encoded string: { "id": "ADR-NNN", "title": "<title>", "status": "proposed", "date": "<today>", "file": "docs/adr/ADR-NNN-<slug>.md" } Find related ADRs -- Call mcp__plugin_ruflo-core_ruflo__memory_search with the title as query in namespace adr-patterns to find related decisions. If matches are found, add them to the Links section and call mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge for each relationship with: sourceId: mem:ADR-NNN targetId: mem:ADR-RELATED relation: depends-on Store pattern -- Call mcp__plugin_ruflo-core_ruflo__memory_store in namespace adr-patterns with key ADR-NNN and the title + context as value for future semantic search. Report -- Output the created file path, ADR number, and any related ADRs found.
Keywords that activate this skill. Click one to copy it.

This skill does not provide trigger words.

The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

验证码 --

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。