01
ACTIVE WORKSPACEHome

Accurate purpose, generated outputs, limitations, and publishing workflow.

LOCAL-FIRST EXPERIENCE | CLOUDFLARE PAGES READYREVIEW AUDIO READY

Prepare websites and knowledge bases for AI-assisted discovery. llms.txt guidance|

A practical workspace for auditing machine-readable discovery surfaces and generating concise artifacts that help automated systems understand a site.

Original template
user@metricforge: ~/agent-discovery-console
6discovery surfaces4artifact types0backend requiredLocalgeneration
01 | CLEAR PRODUCT DEFINITION

Useful by design, honest about scope.

Audit discovery surfaces and generate complementary machine-readable guidance without sending private site descriptions to a server.

Primary use

Documentation sites, research portals, portfolios, product catalogs, and AI-readable knowledge bases.

A practical workspace for auditing machine-readable discovery surfaces and generating concise artifacts that help automated systems understand a site.

GitHub repository ↗
Produces

Concrete, reusable outputs

llms.txt, robots.txt, JSON-LD, agent manifests, readiness scores, and downloadable artifacts.

Boundary

No exaggerated capability claims

These files improve clarity and machine readability, but they cannot guarantee crawler access, ranking, retrieval, or inclusion in any model.

02 | WORKFLOW

One focused path from input to output.

Every stage is separated so the interface stays readable, reviewable, and useful for AI and Data Science learning.

01

Describe

Provide the canonical site identity, purpose, and audience.

02

Audit

Check discovery surfaces and identify missing or inconsistent metadata.

03

Generate

Create concise files for crawlers, agents, and structured-data consumers.

04

Publish

Review every artifact before placing it at the correct public path.