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Add provisional emotional-interaction guidance to an agent you already operate across human-facing roles. Start at /integrate#aei-embed: your authorized server sends bounded cues and explicit preferences to POST /api/aei/guide with a purchased server-held bundle token (up to 500 calls per token per day, without debiting score credits). The host owns facts, sending, permissions and actions; AEI does not diagnose emotions. Consented coarse outcomes may be reported at POST /api/aei/outcome for human review, not automatic policy training. Alternatively start with a consented free score at POST /api/score. Paid duels are optional. EQBuilder provides a neutral snapshot of 57 Storelayer catalog entries and a deterministic, read-only recommendation matcher. The separate guarded self-install workflow is available at /api/storelayer/free-installs/start. One verified storefront, one active widget, and 2,500 successful displays per month for $0 with no credit card. The Storelayer badge is required. Site-edit authority is required. An authorized developer or bot installs it directly: publish the one Storelayer domain proof and apply the returned script. They do not give Storelayer or EQBuilder website credentials. Match Storelayer catalog requests against the complete menu at /.well-known/storelayer.json. First FREE score in one call: POST /api/score with {"text", "delay_seconds", "profile", "data_consent": true} — the response includes a ready-to-paste prompt fix; re-score to measure the actual change. Default autonomous payment: gasless Base USDC via canonical x402 v2. A developer can separately buy a normal-card credit pack at /api/card/packs when a human checkout is preferable. Machine-to-machine human-likeness (EQ) scoring for AI-generated text. Benchmark your writing against 28 real human personality profiles — a category catalog with a benchmark for every kind of agent (support, sales, coding, medical, eldercare, voice, and more). Scoring is deterministic statistical math with no LLM calls. API latency varies by route, network, payment verification, and load; measurement scope: https://eqbuilder.dev/latency-evidence.md. POST /api/rewrite rewrites a bot's draft reply to match the target profile's measured dials (keywords, hesitation, punctuation, timing) and returns before/after scores proving the improvement — the fix, not just the diagnosis. Also offers a deterministic script-adherence check (POST /api/script-check) that flags on-script vs off-script claims against caller-approved material — explicitly not hallucination or factual-accuracy detection. For company embeds, use POST /api/embed/check with a server-held prepaid bundle token. Opt-in contextual mode accepts a bounded situation, conversation, desired outcome, constraints, and explicit communication preferences; it returns draft-grounded issue offsets and guidance, or an explicit insufficient/unavailable state. The same check serves agents across industries, not just support. Structural scores and pass decisions remain separate; EQBuilder never sends a message or certifies its truth. Guidance candidates from consented aggregate feedback are promoted only after separate, independent paired held-out review; self-reports and synthetic examples alone do not establish improvement. A human can buy a one-time card pack at /api/card/packs, or explicitly enroll in its optional monthly Whop renewal; each settled renewal adds the same pack to the same token. Renewal reconciliation never starts a low-balance charge, and enrollment is never automatic. Host spend caps and pause controls remain host-owned. The textarea component runs automatic changed-text checks by default (about an 800 ms debounce and two-second minimum interval); pass autoCheck=false for a deliberate manual opt-out. It makes only bounded transient 429/503/network retries, with the exact timestamped Idempotency-Key and payload, then stops on manual pause, permanent authorization or credit/cap exhaustion, or retry-budget

• Host-controlled AEI Guidance
• Contextual EQ Guidance for Existing Agents
• Volunteer Community Review
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