skill-router

Skill Router

The library holds 191 skills across 15 categories. This skill answers which ones apply to a task, and how to combine them.

Core Concepts

Route on the Task, Not the Technology

"Fix this slow query" is not a PostgreSQL question until you know the query is in PostgreSQL. Start from what the user is trying to do, then narrow by the technology actually in the repository.

Two Shapes of Skill

Shape	Naming	Answers	Examples
Domain expertise	<domain>-expert	"How does X work, and what is good practice?"	postgresql-expert, react-expert
Procedure	<activity>-workflow	"What do I do, in what order?"	tdd-workflow, debugging-workflow

A task usually needs one of each: the workflow drives the sequence, the expert supplies the judgement inside it.

Compose, Don't Concatenate

Loading five skills fills the context and dilutes attention. Load the workflow plus the one or two experts whose material the task actually touches, and consult a third only if the work reaches it.

Finding a Skill

The catalogue is machine-readable and is the fastest route:

# By keyword across names, descriptions and tags
jq -r '.skills[] | select(
         (.name + " " + .description + " " + (.tags | join(" ")))
         | ascii_downcase | contains("kafka")
       ) | "\(.category)/\(.name)"' stdlib/catalog/skill-catalog.json

# Everything in a category
jq -r '.skills[] | select(.category == "security") | .name' stdlib/catalog/skill-index.json

# What a skill covers, before loading it
jq -r '.skills[] | select(.name == "rag-expert") | .description' stdlib/catalog/skill-catalog.json

Or by filesystem, which is often quicker for a name you half-remember:

find stdlib -maxdepth 2 -type d -name '*postgres*'
grep -rl "watermark" stdlib --include=SKILL.md