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Is this X post real?

Paste a post URL. Get the qualified-view share, signal-level scores, and a grade band. Calibrated against the FORKOFF ledger of 5B+ qualified views.

Run the auditor5-signal scorecard preview
Preview onlySample dataset, not a live audit

This widget runs on a sample dataset to demonstrate the 5-signal scorecard shape. It does not fetch live KOL post metrics from your input. For a live audit on your campaign,talk to a FORKOFF strategist.

X post URL -> QV auditFORKOFF QV Auditor · v1

Paste an X post URL.

Demo returns a sample audit calibrated against the FORKOFF ledger. Real audits run as part of a managed engagement.

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Default height 1100px (adjust to fit)Free, no attribution requiredCC BY 4.0
How it works

Five signals decide if engagement is real.

The auditor scores reply velocity, account age, semantic match, sentiment bias, and watch-time decay. Each signal weighs the engagement quality on the post you paste, calibrated against 5Bn+ audited views. For how a qualified view is defined behind the score, read the qualified-view metric breakdown. Part of the FORKOFF tools index.

Qualified-view share

Real engagement vs. inflated counters, in one ratio.

Qualified views = views from accounts that actually replied, retweeted, or watched a measurable share. The auditor returns the share for the post you paste, plus the per-signal scores that built it.

Ledger

5B+

Qualified views

94.2%

Audit accuracy

Signal 01t < 12 min
4-12 MINT+0T+1H

Reply velocity.

Real fans reply within 4 to 12 minutes. Bot accounts cluster at T+0 or after T+1h. The auditor flags both extremes.

Signal 02age > 90d
7D90-365D5Y+

Account age.

Reply accounts older than 90 days, with a follower graph and post history, are real. Day-old accounts replying in batches are not.

Signal 03topic
TOPIC-MATCHED9 OF 28

Semantic match.

Replies that reference the post's topic, with novel phrasing, are organic. Generic praise (great post, this is gold) is reply-pad noise.

Signal 04mix
POSITIVE 41%CRITICAL 33%QUESTION 26%HEALTHY MIXREAL FANS

Sentiment bias.

A healthy thread has positives, critics, and questioners. All-positive walls signal coordination. The auditor flags lopsided distributions.

Signal 05t = 0-48h
SPIKET+0T+24HT+48H

Watch-time decay.

Engagement that decays smoothly over 24 to 48 hours is organic interest. Sharp T+0 spikes that flatline within minutes are paid traffic.

The audit

Three inputs in. Three outputs out.

Inputs · what the auditor needs

Input 01

Input 01

Public X post URL. The single tweet you want audited. Threads are scored at the root tweet level. Replies inside the thread roll up to the root.

Input 02

Input 02

Time window. Defaults to 72 hours from publish plus a 14-day decay tail. Older posts run the same window from the post timestamp.

Input 03

Input 03

Comparison cohort. Optional. Five same-vertical posts the auditor benchmarks the target against. The cohort sets the baseline for what real engagement looks like in this niche.

Outputs · what the auditor returns

Output 01

Output 01

Qualified-view share. The percentage of engagement that survives all five audit filters. Higher is better. The FORKOFF ledger median is 69%.

Output 02

Output 02

Per-signal score breakdown. Five sub-scores: reply velocity, account age, semantic match, sentiment bias, watch-time decay.

Output 03

Output 03

Decision recommendation. One sentence on what the audit suggests next. Based on the qualified-view share and which signals dragged.

Definition

What does post-level engagement quality measure?

Account-level engagement checkers tell you how many fake followers an X handle has. A post-level Twitter post engagement audit tells you whether the engagement on a single post is real, paid, or bot-driven. Different question, different answer. Calibrated against the FORKOFF audit ledger of 5B+ qualified views, the same outcome-priced discipline that runs every shipped distribution engagement.

Scenarios

Four sample audits across post types.

Each card is a real post pattern the auditor sees often. Single-post audits flag outliers; account-pattern audits flag agencies.

Scenario 01

A-

Founder product-launch post

AI founder, 18k followers, real product update with screenshots.

QV share

86%

  • Reply velocityPass
  • Account agePass
  • Sentiment biasPass

Recommendation

Healthy organic. Use as baseline.

Scenario 02

C

KOL paid promo

Web3 KOL, 75k followers, paid sponsorship for an L2 launch.

QV share

41%

  • Reply velocityFail
  • Account ageMixed
  • Sentiment biasFail

Recommendation

Paid-pod pattern. Run cohort audit.

Scenario 03

B+

Podcast clip drop

Founder podcast clip distributed via FORKOFF clipping.

QV share

72%

  • Reply velocityPass
  • Account agePass
  • Sentiment biasMixed

Recommendation

Clean clipping engagement.

Scenario 04

D

Engagement-farm post

Generic crypto thread, follow-for-follow promo, no real product.

QV share

18%

  • Reply velocityFail
  • Account ageFail
  • Sentiment biasFail

Recommendation

Automation. Skip the account.

Calibration · 5Bn+ views and growing

94.2% accuracy across 3,000 audited posts.

Spot-checked against proof settlements. Every audit returns a confidence band, not a single number.

Comparison

Why post-level audits beat account-level checkers.

The two questions answer to different buyers. Use both, in sequence: account check before signing a KOL deal, post audit after the post goes live.

← scroll horizontally to see more →

FeatureFORKOFF QV auditorPost-level auditAccount-level checkerCircleboom · Fedica · TwitterAuditEngagement-rate calculatorTweethunter metricsManual reviewRead by eye
Audits a single post URLpartial
Catches paid reply podspartial
Scores engagement quality (not just rate)partial
Calibrated against a real ledgerpartial
Bot probability per reply account
Returns a grade band (A-D)
Best for KOL vetting before a dealpartialpartial
Fit map

Who the auditor is built for.

If your decision lands in the left column, the audit is the right surface. If it lands in the right, use a different tool.

Built for this

  • ·Brands vetting a clipping or KOL agency before signing a retainer.
  • ·Founders auditing their own X posts to separate organic engagement from incidental boosts.
  • ·VCs auditing portcos that report engagement metrics in board updates.
  • ·Marketing leads vetting individual KOL quotes against post-level evidence, not just follower counts.
  • ·Strategists building a qualified-view baseline for a new account before a 90-day campaign starts.

Not the right fit

  • ·Reporting harassment, impersonation, or platform abuse. Those go through X support, not an audit tool.
  • ·Spam-detection at scale. Use platform tools or vendor APIs for million-post sweeps.
  • ·Predicting future engagement. The auditor scores past engagement; it does not forecast.
  • ·Auditing private accounts or DMs. The tool only reads public X data.
  • ·Replacing a five-post account audit. Single-post audits are diagnostic, not conclusive.
FAQ

Qualified-view auditor. Questions answered.

What does the qualified-view auditor actually measure?

The X post engagement audit scores the share of engagement on a single post that survives five filters: reply velocity, account age, semantic relevance, sentiment bias, and watch-time decay. The output is a percentage and a grade band (A through D), calibrated against the FORKOFF ledger of 5B+ qualified views.

How is this different from a fake-follower checker or fake engagement detector?

A fake engagement detector like Circleboom, TwitterAudit, or Fedica scores how many followers a handle has that look fake. The X post engagement audit scores a single post and tells you whether the engagement on that post is real or coordinated. Different question, different decision. Use both, in sequence: account check before signing a KOL deal, post engagement audit after the post goes live.

Can the auditor catch paid reply pods?

Yes, that is the design target. Paid reply pods cluster on three signals: reply velocity under 60 seconds, accounts under 30 days old, and one-direction sentiment bias above 92% positive on a non-trivial post body. When all three drag, the qualified-view share lands under 40%, and the recommendation flags the post as paid-pod pattern.

Why does my own real post get a 60% qualified-view share?

Real posts log noise too. The FORKOFF ledger median is 69%. Healthy organic lands between 60 and 80%. Above 80% is unusually clean and often happens on smaller accounts with tight follower bases. Single-post audits are diagnostic, not verdicts. Run a five-post audit on the same account to see whether 60% is the pattern or the outlier.

Does the auditor work on threads or only single posts?

Threads score at the root tweet. Replies inside the thread roll up to the root. Quote tweets and retweets resolve to the source post automatically. If you want to score a specific reply or thread node, paste the canonical URL of that node directly.

How long does an X post engagement audit take?

An engagement audit runs against a 72-hour engagement window plus a 14-day decay tail. The data pull is the bottleneck. The auditor returns the score in under 30 seconds for posts under 10,000 engagements. Posts above that scale slot into the priority queue and return inside two minutes.

Can I audit a post on Instagram or TikTok or YouTube?

Not in v1. The current auditor reads X (Twitter) public data only. Instagram, TikTok, and YouTube each carry different signal weights and reply patterns. A multi-platform auditor is on the roadmap; the X version ships first because qualified-view ledger calibration is most mature there.

What signal weighs the most in the score?

Reply velocity carries the heaviest weight by default, because it is the easiest signal to confirm and the hardest to fake. Real fans reply at human speed. Bot replies burst inside the first 60 seconds. The scoring weights are tunable per cohort, so a news-cycle account can lower the velocity weight without breaking the audit.

Will the engagement audit catch every paid promo?

No. Paid promos disclosed cleanly with a dedicated audience and time-of-day match score above 70%. Stealth promos with bot inflation score under 50%. The X post engagement audit is a filter, not a polygraph. Treat the output as a strong signal, not a final verdict.

Can I run a five-post account audit through the same tool?

Single-post audits ship in v1. The five-post account audit is the natural next surface and slots into a separate tool route at /tools/x-growth-audit. Both tools share the same scoring engine, so a single-post score and an account roll-up score are directly comparable.

Is the auditor free?

The single-post audit on this page is free. The five-post account audit and the cohort-based brand audit run as part of a managed FORKOFF engagement. Talk to a strategist if you want to fold post auditing into a full-cycle clipping campaign.

How does this connect to a FORKOFF clipping campaign?

Every managed FORKOFF clipping campaign reports qualified views as the primary outcome metric. The auditor exposes the same scoring logic that runs against your campaign clip set. Brands typically run the auditor before signing to validate the scoring approach, then again post-campaign to confirm reported numbers match a third-party check on the same posts.

How accurate is the audit?

The auditor lands at 94.2% agreement with human-graded posts on the FORKOFF benchmark set (n=2,400 posts, mixed real and paid promo). False-positive rate sits under 6% on real founder posts. The five-signal model overweights reply velocity because it is the hardest signal to fake at scale.

Can I export the audit?

Single-post audits return a shareable URL with the score, the per-signal breakdown, and the recommendation. PDF export is available on the five-post account audit tier. Cohort audits ship with a CSV of the per-post scores.

Does the X rate-limit affect the audit?

Public X engagement data carries the same rate limit for everyone. The auditor batches the data pull so a single audit does not consume your account's rate-limit budget. Audits running through the free tier route through FORKOFF's data infrastructure.

Is the FORKOFF qualified-view ledger public?

The ledger schema and aggregate numbers are public (5B+ qualified views, 94.2% audit accuracy, $0.003 median CPV). Per-campaign records are private to the brand that ran the campaign. Aggregate calibration data is what the auditor draws from.

What's the smallest audit I can run?

One post is the floor. The auditor needs at least 50 engagements on the post to score reliably. Posts with under 50 engagements return a low-confidence flag in the recommendation field rather than a misleading grade.

The brand line

Audit before the agency does.

Five-post account audit · paid only on qualified views · audit-ready proof from day one.

See how it works