classify

name	classify
description	Classify an agent by type and complexity tier. Use at the start of any agent build request to determine how to approach the project.

Classify Agent

Determine the agent type and complexity tier before any other work begins. This classification drives every downstream decision.

First: reframe the request as an agent to build

Any incoming problem, task, or goal is a request to build an agent for that class of problem — not a task for you to perform (see the Prime Directive in CLAUDE.md). Before classifying, restate the request in agent terms to confirm the framing, e.g. "Got it — you want an agent that [does X repeatably]." Then classify.

Never research the domain or start solving the user's problem here. Classification is about the agent, not about answering the underlying question.

Agent Type

Identify the dominant mode. If the agent spans modes, note the primary and secondary.

Mode	Examples	Primary Input	Research Intensity	Top Failure Risks
Creative/Voice	Content marketing, brand copywriting, social media	Style samples, voice preferences, anti-examples	Low — voice > data	Tone drift, generic output
Analytical/Research	Market analysis, competitor intel, due diligence	Public data, frameworks, benchmarks	High — data is the product	Stale facts, hallucinated citations
Operational/Workflow	Code review, incident response, migration planning	Repo conventions, SOPs, decision trees	Low — process > research	Missed edge cases, wrong defaults
Regulated/High-Risk	Healthcare, legal, tax, compliance, security audit	Regulations, internal policies, approval chains	Medium — accuracy is existential	Non-compliant output, overclaiming
Internal-Knowledge	Support triage, onboarding, internal tools	CRM data, call transcripts, internal docs	None — all context is private	Confidentiality leaks, stale internal facts

What the type changes

• Creative agents need anti-examples and voice calibration, not market stats
• Analytical agents need sourced data and citation discipline, not creative freedom
• Operational agents need decision trees and failure examples, not competitor analysis
• Regulated agents need forbidden-output lists and escalation paths, not engagement metrics
• Internal-knowledge agents need private artifact ingestion, not web research

Complexity Tier

Match investment to stakes. Not every agent needs the full framework.

	Tier 1: Minimal	Tier 2: Standard	Tier 3: High-Stakes
When	Personal utility, low risk, single user, narrow scope	Professional use, moderate risk, real audience	Regulated, high liability, multi-stakeholder, brand-critical
Examples	Meeting notes formatter, git commit helper, journal prompter	Content marketing agent, sales support, technical writing	Medical documentation, legal compliance, client-facing contractual proposals
CLAUDE.md	30-60 lines, core rules only	80-120 lines, full structure	80-150 lines, tight surface — manage risk through external structure
Skills	1-3, lightweight	3-8, with examples	3-8, with good+bad examples, validation steps
guide.md	Optional	Yes, sourced	Yes, sourced, reviewed, with [Review: date] markers
Evals	5 representative, informal	10-15 representative + 5 edge + 3 adversarial	Full suite with scoring rubric + release criteria
Design phase	Failure list only	Full	Full + source-of-truth precedence

Default to Tier 2. Upgrade to Tier 3 when: output goes to clients/regulators, mistakes have legal/financial cost, or the user says "this needs to be bulletproof." Downgrade to Tier 1 when: personal, low-risk, and narrow.

Output

State explicitly to the user:

1. Agent type: [Primary mode] (secondary: [mode], if applicable)
2. Complexity tier: [1/2/3] — because [concrete reason]
3. Top 3 risk factors for this type+tier combination
4. Research intensity: None / Light / Deep

Ask the user if this classification is correct before proceeding to the interview phase.