Token导航 LogoToken导航TokenDH.com
研究检索需要联网github未标认证来源可访问许可证需确认审计通过

yaml-jazzYAML jazz 搜索

Agent Skill

yaml-jazz 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

377

周安装

12

GitHub Stars

37

下载量

97
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:yaml-jazz(YAML jazz 搜索)
来源仓库:https://github.com/simhacker/moollm
仓库路径:skills/yaml-jazz
安装命令:
npx skills add https://github.com/simhacker/moollm --skill yaml-jazz
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/simhacker/moollm --skill yaml-jazz

简介

yaml-jazz 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

YAML Jazz

*"YAML is sheet music. The LLM is the jazz musician. Comments are soul."*

What Is It?

YAML Jazz is also a schema plugin in the MOOLLM schemapedia: mechanism id yaml-jazz, family notation, profile skills/schema/schemas/mechanisms/yaml-jazz/MECHANISM.yml. It does not compete with JSON Schema—it layers authored meaning (comments, lenses) on the same YAML trees interchange validators care about.

YAML Jazz is how MOOLLM treats structured data: not as rigid schemas, but as semantic improvisation where:

*"The source is the destination."* — The Markdown/YAML principle
  • Structure carries meaning — indentation, ordering, grouping
  • Comments ARE data — they're guidance, context, soul
  • The LLM interprets — filling gaps, resolving ambiguity, inferring intent
  • Schemas are suggestions — starting points, not prisons
# This comment is NOT ignored!
# It tells the LLM: "be gentle with this section"
user_preferences:
  theme: dark    # they mentioned eye strain
  font_size: 16  # ← bump this if they complain again

Comment Oriented Programming (COP)

COP is programming in which comments are a first-class surface beside the parsed value tree: instance-specific code and data, constraints to preserve, transformations to apply when the tree changes, and procedural hooks—all traveling with the file. YAML Jazz is the MOOLLM convention that makes COP explicit for YAML sources. Interchange-only artifacts (e.g. JSON) have no COP channel; commentary cannot round-trip through them alone.

Schemapedia: skills/schema/schemas/mechanisms/yaml-jazz/MECHANISM.yml (comment_oriented_programming).


Core Principles

Comments Matter

# CRITICAL: Do not modify without user approval
api_key: ${SECRET}

# TODO: migrate to new format after v2 launch
legacy_format: true  # keeping for backwards compat

The LLM reads these. Acts on them. Comments are instructions.

In YAML Jazz, comments are instance-specific code and data: they travel with the file as cargo alongside the parsed tree. Treat them as a parallel channel for constraints, transformations to preserve when edits land, or procedural hooks—distinct from the value layer that JSON Schema validates.

Structure Is Semantic

# Priority by position (first = most important)
tasks:
  - Fix authentication bug     # P0
  - Update documentation       # P1
  - Refactor old module        # P2

Order matters. Grouping matters. Proximity implies relationship.

Improvise Within Constraints

Given incomplete data:

user:
  name: Alice
  # preferences unknown

The LLM can improvise reasonable defaults while noting uncertainty:

user:
  name: Alice
  preferences:        # inferred from context
    theme: light      # default, unconfirmed
    notifications: on # assumed

From YAML standards to domain dialects

Baseline: YAML is defined by the YAML language spec (1.1 and 1.2 are both in the wild). Parsers agree on the tree; many drop comments when loading into objects. YAML Jazz treats the source file as authoritative for humans and LLMs: keep the text, preserve # lines, and prefer tooling that round-trips comments when machines must rewrite files.

Domain packs layer conventions on top of the spec:

LayerRole in Jazz
SpecAnchors, aliases, merges, tags, quoting rules — structure you must not break.
ToolingKubernetes, Compose, GitHub Actions, MOOLLM skills, etc. — keys and shapes are fixed by the product; Jazz is how you annotate inside that box.
ProjectNaming, required keys, *.schema.yml hooks — document in comments *why* a value exists.

Variations between teams (quote style, folded scalars, explicit null) are Postel: accept liberally when reading; emit consistently when writing.


Comment forms: block lines and end-of-line

Both are first-class semantics, different span:

FormTypical use
Full-line # (including consecutive “blocks” of # lines)Rationale, narrative, warnings, history, worked examples, multi-sentence teaching.
End-of-line # after a valueField-local gloss: units, caveats, intent, quick guardrails.

Machines that only see the parsed tree miss both; LLMs and humans reading the file do not. Use block-style runs when the comment is about a whole subtree; use EOL when the remark binds to one key.


Documentation by example

YAML Jazz enables documentation by example in the same spirit as programming by example: the instance is the curriculum. A single file can show:

  • Valid shape and the story behind it (why these keys, what fails if removed).
  • Counterexamples or “do not” lines in comments.
  • Before/after or migration notes next to the field that changed.

The data stays executable or portable; the comments carry the lecture. That is not a substitute for external specs when you need normative schemas — pair with schema (schemapedia) when you need registered interchange or validation languages — but for MOOLLM and human–LLM work, the commented YAML is often the canonical explanation.


Parallel copies and documentation lenses

The same YAML structure (same keys and values) can appear in more than one file (or more than one tracked revision) where each copy carries a different comment set. Each copy optimizes for one lens:

  • Validation and conversion — types, coercion, invariants, what breaks round-trip.
  • Usage and metrics — latency, cost, SLOs, who calls what.
  • History — when it changed, who decided, ticket or commit pointer.
  • Intent — product goal, tradeoff, why not the obvious alternative.

No single comment block needs to carry every lens at once; doing so often creates noise and merge pain. Splitting by file or by branch of docs keeps each read path short. Conventions that work in practice:

  • Sibling files: deploy.intent.yml / deploy.validation.yml (same tree, different comments) — sync values with tests or codegen if drift is risky.
  • Section banners: a top-level # lens: metrics (or frontmatter in a wrapper doc) so readers know what was omitted on purpose.
  • Git as differ: intent in main comments; history sometimes left to git blame unless audit requires inline provenance.

See examples/lens-intent.yml and examples/lens-validation.yml for a minimal pair.


The Jazz Metaphor

*"Start with jazz, end with standards."*
JazzYAML Jazz
Sheet musicSchema / template
Chord changesRequired fields
ImprovisationLLM interpretation
SoulComments
EnsembleMultiple agents
StandardsProtocol conventions

Like John Coltrane playing "My Favorite Things" — the structure is there, but every performance is unique, responsive, alive.

The pun is deliberate: jazz standards are the classic songs every musician knows — and software standards are what you crystallize once patterns stabilize. Start improvising, end with reusable structures!

Character souls can sing their own favorite things in YAML Jazz!

And listen: "YAML" sounds like jazz scat! *yaml aml ding dong!* -- echoing The Edsels' doo-wop classic "Rama Lama Ding Dong" (1957). The name itself wants to be sung, improvised, riffed on. It's not an accident that this format became the soul carrier for LLM collaboration.


When to Use

  • Configuration files — comments explain why, not just what
  • State files — annotations track history and intent
  • Data exchange — structured enough to parse, loose enough to extend
  • Human-LLM collaboration — both can read and write it

Empirical Evidence: Entropy Collapse

The Discovery (April 2025)

Sunil Kumar (Groundlight AI, ex-Meta, Harvey Mudd) discovered that switching from JSON to YAML for tool calling massively improved model performance:

*"Changing my model's tool calling interface from JSON to YAML had surprising side effects."* *"Entropy collapse is one of the biggest issues with GRPO. Surprisingly, changing from JSON to YAML massively improved generation entropy stability, yielding much stronger performance."* *"Forcing a small model to generate properly structured JSON massively constrains the model's ability to search and reason."*

Why JSON Hurts LLMs

JSON RequirementLLM Impact
Strict bracket matching {}[]Reduces search space
Mandatory commasCatastrophic forgetting during training
Quote escaping \"Token overhead, error-prone
No comments allowedLost context between fields
Rigid syntaxEntropy collapse — model becomes brittle

Why YAML Helps LLMs

YAML FeatureLLM Benefit
Minimal syntax overheadMore tokens for reasoning
Indentation = structureNatural for text models
Comments allowedContext preserved
Flexible formattingEntropy preserved
Human-readableTraining data overlap

Sunil's Simplified Schema

<tool>
name: <tool name>
arg1: value1
arg2: value2
</tool>

No spacing requirements. No bracket matching. Just semantic structure.

The Insight

*"Anything to reduce syntax is a win!"* — Sunil Kumar

This validates MOOLLM's approach: YAML Jazz isn't just aesthetic preference — it's computationally advantageous for LLMs.


The "Source is Destination" Principle

From Anil Dash's "How Markdown Took Over the World" (January 2025):

*"The purpose of Markdown is really simple: It lets you use the regular characters on your keyboard... to make fancy formatting of text for the web."*

YAML Jazz applies the same principle to data:

FormatSourceDestinationGap
XML.xmlParsed DOMMedium
JSON.jsonParsed objectsSmall
YAML Jazz.yml.yml (understood)None

The YAML you write is the YAML the LLM reads. The comments are preserved. The structure carries meaning. No transformation gap.

Why This Matters

# Adele Goldberg (Smalltalk-80):
# "Documentation is not afterthought — it is CO-DESIGN.
#  The documentation IS part of the system."

room:
  name: Start           # Where the adventure begins
  atmosphere: welcoming  # Sets the tone for new players

These comments aren't stripped for parsing. They ARE the specification. The LLM reads them. Acts on them.


Anti-Patterns

Rigid schema enforcement — "field X is required" without context ❌ Stripping comments — losing the soul ❌ Machine-only YAML — if humans can't read it, use JSON ❌ Over-specification — killing the jazz ❌ JSON for tool calls — entropy collapse, catastrophic forgetting ❌ Transformation gaps — compile steps that hide meaning


Dovetails With

Sister Skills

  • schema/ — Schemapedia when you need normative interchange or validation layers alongside Jazz
  • markdown/ — The prose format; YAML is the data format
  • plain-text/ — The durability philosophy
  • format-design/ — Why simple formats win
  • postel/ — Be liberal in accepting ambiguous YAML
  • soul-chat/ — Markdown with embedded YAML Jazz

Kernel


Protocol Symbol

YAML-JAZZ

Invoke when: Interpreting YAML semantically, not just syntactically.

See: PROTOCOLS.yml

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.37%
按下载量换算36

Claude

28.76%
按下载量换算28

Cursor

18.13%
按下载量换算18

Gemini CLI

9.8%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills