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ruido brief

WeKruit

8
noise / 100
8/ 100

The read

No live thread cleared the bar this scan. Run the Reddit search plan in supporting moves, then rerun — fresh threads surface daily.

1 moves · 1 links
01/03

Reply in Reddit threads

1

Real /comments/ threads where a founder-honest reply fits. Verified-fit threads come with a paste-ready draft; the rest are on-topic threads we found — open them and judge the fit yourself.

show ▸hide ▾

Ready to reply · 1

This prevents forced community posting and turns a missing thread into a tighter search or source asset.

10 min · low risk · +3-7 pts
Open search
02/03

Tighten your own site

5

Quick on-site fixes — FAQ, comparison, schema — that give crawlers and assistants clean sentences to quote.

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01
Websitespecific URLSite
Publish a WeKruit vs Hired page

Do not wait for people to search your brand. Borrow the incumbent's demand with a fair comparison.

/vs/hired
Why now
+2-6 pts

Cleaner source text makes every later mention easier for models to parse and repeat.

45 min · low risk
Open
02
WebsiteSite
Add a plain FAQ people can quote

FAQ blocks give founders, users, and crawlers clean sentences to repeat in other places.

FAQ section
Why now
+2-6 pts

Cleaner source text makes every later mention easier for models to parse and repeat.

25 min · low risk
Open
03
WebsiteSite
Add a short llms.txt map for assistants

A small llms.txt is an easy way to spoon-feed assistants the version of the product you want repeated.

/llms.txt
Why now
+2-6 pts

Cleaner source text makes every later mention easier for models to parse and repeat.

12 min · low risk
Open
04
WebsiteSite
Unify category language across hero, meta, FAQ, and docs

Small products cannot afford five different category names. Pick one and make the market repeat it.

Terminology patch
Why now
+2-6 pts

Cleaner source text makes every later mention easier for models to parse and repeat.

12 min · low risk
Open
05
WebsiteSite
Add quotable proof blocks to the homepage

Noise travels when it is easy to quote: definition, tradeoff, number, table. Broad marketing copy does not travel.

Homepage citation blocks
Why now
+2-6 pts

Cleaner source text makes every later mention easier for models to parse and repeat.

22 min · low risk
Open
03/03

Other distribution moves

8

Directories, comparison content, and platform piggybacks worth a look once the higher-leverage work is done.

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01
DEV CommunityCompetitor
Publish “WeKruit vs Hired” as a lightweight comparison post

Hired already owns category memory. A calm comparison borrows that demand without pretending you are bigger than you are.

New post
Why now
+5-12 pts

Comparison content borrows incumbent demand and can change competitor co-mention patterns.

35 min · low risk
Open
02
DEV CommunityCompetitor
Publish “WeKruit vs Wellfound” as a lightweight comparison post

Wellfound already owns category memory. A calm comparison borrows that demand without pretending you are bigger than you are.

New post
Why now
+5-12 pts

Comparison content borrows incumbent demand and can change competitor co-mention patterns.

35 min · low risk
Open
03
DEV CommunityCompetitor
Publish “WeKruit vs Teal” as a lightweight comparison post

Teal already owns category memory. A calm comparison borrows that demand without pretending you are bigger than you are.

New post
Why now
+5-12 pts

Comparison content borrows incumbent demand and can change competitor co-mention patterns.

35 min · low risk
Open
04
DEV CommunityCompetitor
Publish “WeKruit vs Simplify” as a lightweight comparison post

Simplify already owns category memory. A calm comparison borrows that demand without pretending you are bigger than you are.

New post
Why now
+5-12 pts

Comparison content borrows incumbent demand and can change competitor co-mention patterns.

35 min · low risk
Open
05
AlternativeTospecific URLDirectory
Submit WeKruit to AlternativeTo

Direct competitor hijack surface: users arrive with replacement intent already loaded.

Add new software
Why now
+3-8 pts

This creates a searchable external proof point, but impact depends on indexing and follow-on engagement.

15 min · low risk
Open
06
Product Huntspecific URLDirectory
Submit WeKruit to Product Hunt

High-trust launch surface that agents and search systems often recognize as product evidence.

New product draft
Why now
+3-8 pts

This creates a searchable external proof point, but impact depends on indexing and follow-on engagement.

18 min · med risk
Open
07
DEV CommunityBlog
Publish a problem-first post around “AI recruiter”

Early products should not wait for brand search. Own a painful query first, then mention the product as the practical answer.

New post
Why now
+3-8 pts

This creates a searchable external proof point, but impact depends on indexing and follow-on engagement.

28 min · low risk
Open
08
DEV CommunityBlog
Publish a problem-first post around “job matching”

Early products should not wait for brand search. Own a painful query first, then mention the product as the practical answer.

New post
Why now
+3-8 pts

This creates a searchable external proof point, but impact depends on indexing and follow-on engagement.

28 min · low risk
Open

Score detail8/100 · High confidence · weakest: Citation readiness 3

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First distribution matters more than polish. The model does not yet have enough public evidence to recommend the product naturally. The score should move from basic crawlability, clear category language, and a few real public mentions.

0%
Mention rate
50%
0%
Prominence
15%
13%
Binding
20%
6%
Footprint
10%
100%
Brand recall
5%

Noise score = model discovery, ranking position, category binding, public footprint, and direct brand recall. The dimensions below explain why the score moved; not every diagnostic dimension adds points directly.

Semantic clarity
Can a model compress the product into one sharp sentence?
78

Looks at the site description, extracted positioning, category confidence, and whether pages repeat the same core meaning.

The site and extracted profile give models a clear one-sentence understanding of the product.

The meta description clearly explains the core workflow and category, but the page lacks visible hero/H1 content and broader crawlable context to make the positioning instantly obvious.

Category binding
Does the product appear in the right buying conversation?
13

Uses recommendation prompts, competitor co-mentions, brand recall, and category confidence. This directly contributes 20% of the main score.

You are co-mentioned with a category leader in only 0% of responses.

Hired dominates 5 prompts you do not appear in.

Models recognize the brand when asked directly, but do not naturally recommend it yet.

Citation readiness
Is there enough quotable source material for AI answers?
3

Checks FAQ depth, comparison pages, schema, docs, tables, statistics, definition blocks, and concise answer-first paragraphs.

Only 0 FAQ items found across all pages.

No comparison pages detected (/vs/ or /alternatives).

No schema.org JSON-LD on any page.

Few answer-first blocks, statistics, tables, or concise quotable paragraphs found.

There are no FAQs, schema.org markup, comparison pages, tables, statistics, definition blocks, or other structured citation-friendly content.

Site readiness is stronger than current noise — the next lift likely comes from outside mentions, comparisons, and community distribution.

Technical access
Can AI/search crawlers read the important pages?
74

Checks AI crawler access, llms.txt, and whether the landing page has enough server-visible text.

llms.txt exists but is missing a clear title or key page links.

Key landing-page text may be too thin for crawlers that do not execute JavaScript.

Community footprint
Is there public noise outside the website?
6

Counts product mentions across searched surfaces, source spread, and frontier-model visibility. This directly contributes 10% of the main score.

Only 0 community mentions found across all platforms.

Terminology consistency
Do pages keep using the same market language?
18

Compares extracted key terms against homepage and subpage language so the model does not see multiple disconnected descriptions.

Only 0% of your key terminology shows up across all pages.

Several key terms appear in the meta description, such as résumé upload, hiring manager pitch, interview booking, and pipeline, but they are not reinforced across visible page content or subpages.

Scan details · 3 models · 15/15 prompts · 5/6 sourcesDetails
Models usedOpenAI, Claude Sonnet, Claude Opus
Prompts run15/15 from 5 prompt types
Sources searchedHacker News, Reddit, Stack Overflow, OpenAI web
Source failuresNone recorded
Scan versionruido-score-v2
Redditenabled
0 hits

Searched Reddit's public search (no API credentials needed).

Stack Overflowenabled
0 hits

Native connector searched directly.

Xenabled
0 hits

Checked through OpenAI/Claude web search only; no native X connector is enabled.

Blogenabled
0 hits

Web search checked for specific blog/forum articles.

OpenAI webenabled
0 hits

Web search ran and may discover Reddit, Stack Overflow, X, forums, and blogs.

Claude webskipped
0 hits

Web discovery runs through a single shared provider for this scan.