nx_meet_trust.nx source

1// nx_meet_trust.nx -- R6 of the NISHI MEET PLATFORM: the ANTI-FAKE engine (LIBRARY, no main). The headline 2// capability + the MEASURED exceed: rule-based detection of AI-generated / slop resumes and fake "ghost" job 3// postings -- the screening that lets "quality meet quality." Sovereign (nx_cc->nxasm, no ML runtime, no JS): 4// lowercase + weighted keyword signals (slop buzzword density vs concrete specifics: numbers, contacts, links, 5// salary, real URLs). Returns 0..100 (higher = more authentic); below TRUST_THRESHOLD => flagged. Thresholds are 6// named consts (rule 11). license_tier: ORIGINAL 7import "nx_syscalls.nx" 8import "nx_meet_lib.nx" 9 10const TRUST_THRESHOLD: i64 = 50 11 12// lowercase-copy src[0..n) into out (nul-term). 13func trust_lc(src: *u8, n: i64, out: *u8) -> i64 { 14 var i: i64 = 0 15 while i < n { 16 var c: i64 = src[i] as i64 17 if c >= 65 { if c <= 90 { c = c + 32 } } 18 out[i] = c as u8 19 i = i + 1 20 } 21 out[n] = 0 as u8 22 return n 23} 24// 1 if needle occurs in hay[0..n). 25func trust_has(hay: *u8, n: i64, needle: *u8) -> i64 { 26 let nl: i64 = mlen(needle); if nl == 0 { return 0 } 27 var i: i64 = 0 28 while i + nl <= n { var k: i64 = 0; var hit: i64 = 1; while k < nl { if hay[i+k] != needle[k] { hit = 0; k = nl } else { k = k + 1 } } if hit == 1 { return 1 } i = i + 1 } 29 return 0 30} 31func trust_has_digit(hay: *u8, n: i64) -> i64 { 32 var i: i64 = 0 33 while i < n { let c: i64 = hay[i] as i64; if c >= 48 { if c <= 57 { return 1 } } i = i + 1 } 34 return 0 35} 36 37// resume authenticity 0..100. Slop buzzword density subtracts; concrete specifics (numbers/contact/links) add. 38func trust_resume_score(text: *u8) -> i64 { 39 let n: i64 = mlen(text) 40 let lc: *u8 = sys_mmap(n + 16) 41 trust_lc(text, n, lc) 42 var s: i64 = 50 43 if trust_has(lc, n, "as an ai" as *u8) == 1 { s = s - 18 } 44 if trust_has(lc, n, "language model" as *u8) == 1 { s = s - 18 } 45 if trust_has(lc, n, "results-driven professional" as *u8) == 1 { s = s - 14 } 46 if trust_has(lc, n, "passionate team player" as *u8) == 1 { s = s - 14 } 47 if trust_has(lc, n, "detail-oriented" as *u8) == 1 { s = s - 10 } 48 if trust_has(lc, n, "synergy" as *u8) == 1 { s = s - 12 } 49 if trust_has(lc, n, "hit the ground running" as *u8) == 1 { s = s - 12 } 50 if trust_has(lc, n, "think outside the box" as *u8) == 1 { s = s - 12 } 51 if trust_has(lc, n, "go-getter" as *u8) == 1 { s = s - 10 } 52 if trust_has(lc, n, "proven track record" as *u8) == 1 { s = s - 10 } 53 if trust_has_digit(lc, n) == 1 { s = s + 14 } 54 if trust_has(lc, n, "@" as *u8) == 1 { s = s + 12 } 55 if trust_has(lc, n, "http" as *u8) == 1 { s = s + 12 } 56 if trust_has(lc, n, "%" as *u8) == 1 { s = s + 10 } 57 if trust_has(lc, n, "github" as *u8) == 1 { s = s + 8 } 58 if s < 0 { s = 0 } 59 if s > 100 { s = 100 } 60 return s 61} 62func trust_is_fake_resume(text: *u8) -> i64 { if trust_resume_score(text) < TRUST_THRESHOLD { return 1 } return 0 } 63 64// posting legitimacy 0..100. Ghost/MLM markers subtract; concrete company/salary/URL specifics add. 65func trust_posting_score(text: *u8) -> i64 { 66 let n: i64 = mlen(text) 67 let lc: *u8 = sys_mmap(n + 16) 68 trust_lc(text, n, lc) 69 var s: i64 = 50 70 if trust_has(lc, n, "competitive salary" as *u8) == 1 { s = s - 12 } 71 if trust_has(lc, n, "fast-paced environment" as *u8) == 1 { s = s - 12 } 72 if trust_has(lc, n, "be your own boss" as *u8) == 1 { s = s - 18 } 73 if trust_has(lc, n, "unlimited earning" as *u8) == 1 { s = s - 18 } 74 if trust_has(lc, n, "rockstar" as *u8) == 1 { s = s - 10 } 75 if trust_has(lc, n, "ninja" as *u8) == 1 { s = s - 10 } 76 if trust_has(lc, n, "wear many hats" as *u8) == 1 { s = s - 10 } 77 if trust_has(lc, n, "always hiring" as *u8) == 1 { s = s - 12 } 78 if trust_has(lc, n, "work hard play hard" as *u8) == 1 { s = s - 10 } 79 if trust_has(lc, n, "like a family" as *u8) == 1 { s = s - 10 } 80 if trust_has_digit(lc, n) == 1 { s = s + 12 } 81 if trust_has(lc, n, "http" as *u8) == 1 { s = s + 12 } 82 if trust_has(lc, n, "$" as *u8) == 1 { s = s + 12 } 83 if trust_has(lc, n, "remote" as *u8) == 1 { s = s + 6 } 84 if s < 0 { s = 0 } 85 if s > 100 { s = 100 } 86 return s 87} 88func trust_is_ghost_posting(text: *u8) -> i64 { if trust_posting_score(text) < TRUST_THRESHOLD { return 1 } return 0 }