Agent skill · Workflow & Productivity

request-classifier

Classify any user request into a structured format for prompt generation. Use this skill whenever you need to understand what type of task a request represents, determine complexity, decide whether planning is needed, or route a request to the right skills and agent strategy. Trigger on: any request that needs to be analyzed before generating a Claude Code prompt, when someone says 'classify this', 'what kind of task is this', when the prompt-generator or prompt-router skills need input classification, or when deciding between solo agent vs subagent vs tmux team execution.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill request-classifier --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 15 KB
Bundled scripts: none
Path: skills/agent/request-classifier/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Request Classifier Classify a user request into a structured JSON object that downstream skills (prompt-router, prompt-generator) use to decide: what type of task this is, how complex it is, and whether to enter plan mode before generating a Claude Code prompt. **Read the full taxonomy** at `references/taxonomy.md` before classifying. It contains the complete keyword lists, scoring rules, and decision tree. The sections below give you the process and worked examples. --- ## How to Classify ### Step 1 — Read the request Extract the raw text of the user's request. If the request is embedded in a longer conversation, focus on the most recent action request, not background context. ### Step 2 — Load the taxonomy Read `references/taxonomy.md`. Pay attention to: - The 8 request type definitions and their keyword lists - The scoring dimensions table in the Complexity Scoring Algorithm section - The Plan Mode Decision Tree ### Step 3 — Identify the request type Match keywords and signals against the 8 types in priority order: 1. **pipeline** — check first; graph/node/state/LangGraph signals override other types 2. **bug-fix** — error/crash/failing signals are strong 3. **feature** — "add

What's inside
Steps it walks through
  1. How to Classify
  2. Step 1 — Read the request
  3. Step 2 — Load the taxonomy
  4. Step 3 — Identify the request type
  5. Step 4 — Score complexity
  6. Step 5 — Apply the plan mode decision tree
  7. Step 6 — Output the classification JSON
  8. Step 7 — Handle ambiguity
  9. Edge Cases
  10. Override Handling
  11. 10 Worked Examples
  12. Example 1 — Quick rename
  13. Example 2 — Bug fix with stack trace context
  14. Example 3 — New feature with cross-layer scope
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the request-classifier skill do?

Classify any user request into a structured format for prompt generation. Use this skill whenever you need to understand what type of task a request represents, determine complexity, decide whether planning is needed, or route a request to the right skills and agent strategy. Trigger on: any request that needs to be analyzed before generating a Claude Code prompt, when someone says 'classify this', 'what kind of task is this', when the prompt-generator or prompt-router skills need input classification, or when deciding between solo agent vs subagent vs tmux team execution.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill request-classifier --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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