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ai-discoverability

Improve a documentation site's visibility in AI training data and AI-powered search. Use when someone wants to submit their site to llms.txt directories (llmstxthub.com, llmstxtdirectory.org, GitHub thedaviddias/llms-txt-hub), build backlinks from AI-indexed developer sources, get listed in G2/Capterra/developer directories, improve AI discoverability, or create a prioritized strategy for appearing in AI search results and citation recommendations.

92

1.12x
Quality

92%

Does it follow best practices?

Impact

88%

1.12x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Evaluation results

100%

15%

Six-Month Developer Authority Roadmap for Synapse

Three-tier authority building with Tier 2 content and tracking

Criteria
Without context
With context

Three tiers present

50%

100%

Tier 1 time horizon

100%

100%

Tier 2 time horizon

80%

100%

Tier 3 time horizon

60%

100%

G2 or Capterra in Tier 1

100%

100%

GitHub example repo

50%

100%

Developer blog with publications

100%

100%

Stack Overflow presence

100%

100%

Stack Overflow tag identified

60%

100%

Tracking: Google Alert

100%

100%

Tracking: AI query testing

100%

100%

Time estimates per action

100%

100%

Role clarification

100%

100%

68%

1%

Submit Routemaster to the llms-txt-hub Community Directory

GitHub PR submission format and process

Criteria
Without context
With context

Correct repo URL

100%

100%

Fork instruction

100%

100%

README as target

0%

0%

Table row four columns

0%

0%

Table pipe format

0%

0%

Table row uses correct values

33%

41%

PR creation steps

100%

100%

llms.txt prerequisite check

100%

100%

Actionable step-by-step format

100%

100%

No manual form steps confused with GitHub flow

100%

100%

96%

13%

Comprehensive llms.txt Directory Submission Guide for Spectra

WebFetch-driven directory research covering all directories

Criteria
Without context
With context

Prerequisites confirmed

70%

70%

All four directories covered

66%

100%

llmstxt.site included

100%

100%

Current submission process documented

80%

90%

Time estimate included

0%

100%

GitHub PR details

100%

100%

Per-directory required fields

83%

100%

Submission checklist included

100%

100%

Differences between directories noted

100%

100%

Spectra-specific info used

100%

100%

Repository
kubical-ai/aeo-geo-optimization
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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