Resilience-Ledger/Delta-Atlas-GapCheck.html at main · JakeTOpenSource/Resilience-Ledger · GitHub

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<title>Delta Atlas - Gap Check</title>
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<header>
 <h1>Delta Atlas - Gap Check</h1>
 <p>Paste an AI policy, project plan, or vendor claim. It reads the governance terms you used and flags what is <b>missing</b>: risks named with no control, autonomy with no oversight, and terms that are still thin. It checks structure, not correctness, and it runs entirely on your device. In the atlas grammar: your document is the <b>claim</b>; its own stated controls are the <b>witness</b>; the findings are the difference.</p>
</header>
<div class="wrap">
 <div class="in">
   <textarea id="src" placeholder="Paste text here. For example, an AI use policy, a system description, or a vendor's safety claims."></textarea>
   <div class="row">
     <button class="btn pri" id="run">Check for gaps</button>
     <button class="btn" id="ex">Load example</button>
     <button class="btn" id="batchBtn">Batch: off</button>
     <button class="btn" id="clr">Clear</button>
   </div>
 </div>
 <main id="out"><div class="placeholder">Paste something on the left and press <b>Check for gaps</b>.<br/>Or press <b>Load example</b> to see how it works.</div></main>
</div>
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The Ledger's whole point: a system can be perfectly self-consistent and still wrong, so it needs an external ground truth, ultimately verified by a human in contact with reality.","aliases":["ground truth"]},{"id":"grounding","name":"Grounding","cluster":"Data & Provenance","purpose":"check","status":"candidate","acct":"org","def":"Tying a model's output to verified external sources so its claims can be checked, which reduces fabrication.","aliases":["grounding"]},{"id":"provenance","name":"Provenance","cluster":"Data & Provenance","purpose":"check","status":"reviewed","acct":"human","def":"The recorded origin and history of data or a model, used to judge whether it can be trusted.","aliases":["provenance"]},{"id":"attestation","name":"Attestation","cluster":"Data & Provenance","purpose":"check","status":"reviewed","acct":"human","def":"Verifiable, often cryptographic, evidence of a system's identity or state, used to establish trust between parties.","aliases":["attestation"]},{"id":"data-lineage","name":"Data Lineage","cluster":"Data & Provenance","purpose":"check","status":"reviewed","acct":"human","def":"The detailed, technical form of provenance. 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Imperfect, but raises the cost of undetected fakery.","aliases":["watermarking"]},{"id":"sybil-resistance","name":"Sybil Resistance","cluster":"Data & Provenance","purpose":"check","status":"candidate","acct":"org","def":"In multi-agent settings, stops fake \"agreement\" from many sock-puppet sources. The Ledger names this directly: convergence counts only in proportion to how independent the sources truly are.","aliases":["sybil resistance"]},{"id":"supply-chain","name":"Supply Chain","cluster":"Data & Provenance","purpose":"capability","status":"candidate","acct":"org","def":"Each dependency is a way in for risk (OWASP LLM03). Governing agents means governing what they're built from and connect to.","aliases":["supply chain"]},{"id":"hallucination","name":"Hallucination","cluster":"Failure Modes & Risks","purpose":"risk","status":"reviewed","acct":"undefined","def":"When an AI states something false as if it were true: fluent, confident output that isn't grounded in real data. Also called contextual mismatch or semantic drift.","aliases":["hallucination"]},{"id":"prompt-injection","name":"Prompt Injection","cluster":"Failure Modes & Risks","purpose":"risk","status":"reviewed","acct":"undefined","def":"The top-ranked LLM risk. Dangerous for agents because the injected instruction can trigger real tool actions.","aliases":["prompt injection"]},{"id":"jailbreak","name":"Jailbreak","cluster":"Failure Modes & Risks","purpose":"risk","status":"reviewed","acct":"undefined","def":"Close to prompt injection; specifically aimed at defeating guardrails. 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The opposite is sparse.","aliases":["density"]},{"id":"deployment","name":"Deployment","cluster":"Agentic Mechanics","purpose":"capability","status":"reviewed","acct":"shared","def":"Putting a trained model into production use.","aliases":["deployment"]},{"id":"detection","name":"Detection","cluster":"Oversight & Governance","purpose":"check","status":"reviewed","acct":"human","def":"Surfacing a problem or pattern as it occurs.","aliases":["detection"]},{"id":"diffusion","name":"Diffusion","cluster":"Foundations","purpose":"capability","status":"candidate","acct":"org","def":"A generative method that denoises random noise into data.","aliases":["diffusion"]},{"id":"dimension","name":"Dimension","cluster":"Foundations","purpose":"capability","status":"candidate","acct":"org","def":"One axis of a data space.","aliases":["dimension"]},{"id":"discount","name":"Discount","cluster":"Foundations","purpose":"capability","status":"candidate","acct":"org","def":"How much future reward is valued 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When data or outputs cluster at opposing extremes they are polarized, which can skew what a model learns or 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s"],["explainability","transparency","enables"],["explainability","black-box","mitigates"],["compliance","risk-assessment","requires"],["red-teaming","risk-assessment","enables"],["ai-governance","ai-lifecycle","governs"],["ai-governance","shadow-ai","mitigates"],["compliance","shadow-ai","mitigates"],["human-centered-ai","human-in-the-loop","related"],["grounding","ground-truth","requires"],["validation-gate","ground-truth","requires"],["ground-truth","hallucination","mitigates"],["grounding","hallucination","mitigates"],["provenance","attestation","related"],["provenance","supply-chain","related"],["attestation","sybil-resistance","enables"],["attestation","zero-trust","enables"],["data-lineage","provenance","instance_of"],["data-lineage","audit-trail","enables"],["synthetic-data","bias","related"],["vector-database","memory","enables"],["knowledge-graph","ontology-policy-gate","enables"],["knowledge-graph","grounding","enables"],["watermarking","provenance","enables"],["watermarking","synthetic-data","detects"],["sybil-resistance","provenance","requires"],["supply-chain","tool-poisoning","causes"],["prompt-injection","jailbreak","related"],["prompt-injection","agent-goal-hijack","causes"],["guardrail","jailbreak","mitigates"],["excessive-agency","agent-goal-hijack","enables"],["agent-goal-hijack","multi-agent-system","related"],["goal-misalignment-goal-misgeneralization","alignment","related"],["goal-misalignment-goal-misgeneralization","reward-hacking","related"],["goal-misalignment-goal-misgeneralization","deceptive-alignment","related"],["reward-hacking","alignment","related"],["red-teaming","deceptive-alignment","detects"],["model-drift","training-data","related"],["defense-in-depth","cascading-failure","mitigates"],["tool-poisoning","data-poisoning","related"],["provenance","data-poisoning","mitigates"],["data-poisoning","supply-chain","related"],["least-privilege","sensitive-information-disclosure","mitigates"],["sensitive-information-disclosure","privilege","related"],["shadow-ai","sensitive-information-disclosure","causes"],["least-privilege","privilege","mitigates"],["privilege","excessive-agency","causes"],["privilege","scoping","related"],["automation-bias","human-in-the-loop","related"],["overfitting","training-data","related"],["overfitting","model-drift","related"],["red-teaming","emergent-behavior","detects"],["harness","guardrail","alias_of"],["harness","validation-gate","alias_of"],["tether","grounding","alias_of"],["buffer","graceful-degradation","alias_of"],["buffer","sandboxing","alias_of"],["floor","guardrail","alias_of"],["return","audit-trail","alias_of"],["grace","graceful-degradation","alias_of"],["forgiveness","audit-trail","alias_of"],["rlhf","human-in-the-loop","handoff"],["rlhf","alignment","handoff"],["human-in-the-loop","kill-switch-circuit-breaker","handoff"],["guardrail","prompt-injection","mitigates"],["sandboxing","tool-poisoning","mitigates"],["rate-limiting","cascading-failure","mitigates"],["kill-switch-circuit-breaker","cascading-failure","mitigates"],["human-in-the-loop","agent","checks"],["reinforcement-learning","machine-learning","instance_of"],["transformer","large-language-model","enables"],["agentic-ai","large-language-model","requires"],["drift","model-drift","alias_of"],["recurrent","neural-network","instance_of"],["lstm","recurrent","instance_of"],["gru","recurrent","instance_of"],["lora","peft","instance_of"],["qlora","lora","instance_of"],["qlora","quantization","requires"],["adapter","peft","instance_of"],["attention","transformer","enables"],["backpropagation","deep-learning","enables"],["chain-of-thought","reasoning","enables"],["tree-of-thoughts","reasoning","enables"],["react","reasoning","enables"],["monitoring","drift","detects"],["telemetry","observability","enables"],["pinecone","vector-database","alias_of"],["chroma","vector-database","alias_of"],["weaviate","vector-database","alias_of"],["milvus","vector-database","alias_of"],["lineage","data-lineage","alias_of"],["q-learning","reinforcement-learning","instance_of"],["actor-critic","reinforcement-learning","instance_of"],["ppo","reinforcement-learning","instance_of"],["dpo","reinforcement-learning","instance_of"],["dqn","q-learning","instance_of"],["pomdp","mdp","instance_of"],["retrieval","vector-database","requires"],["chunking","retrieval","enables"],["retrieval-augmented-generation","retrieval","requires"],["rlaif","alignment","enables"],["anonymization","sensitive-information-disclosure","mitigates"],["redaction","sensitive-information-disclosure","mitigates"],["privacy","sensitive-information-disclosure","mitigates"],["weightsbiases","wandb","alias_of"],["human-in-the-command","hitc","alias_of"],["hotl","human-on-the-loop","alias_of"],["kahneman-tversky","kto","alias_of"],["regression","machine-learning","instance_of"],["classification","machine-learning","instance_of"],["clustering","unsupervised","instance_of"],["forest","ensemble","instance_of"],["bagging","ensemble","instance_of"],["boosting","ensemble","instance_of"],["gguf","quantization","instance_of"],["gptq","quantization","instance_of"],["awq","quantization","instance_of"],["vllm","inference","enables"],["tensorrt","inference","enables"],["triton","inference","enables"],["fsdp","parallelism","instance_of"],["sharding","parallelism","enables"],["tokenization","token","enables"],["few-shot","prompting","instance_of"],["one-shot","prompting","instance_of"],["zero-shot","prompting","instance_of"],["kto","alignment","instance_of"],["preference","alignment","enables"],["cuda","gpu","enables"],["whisper","speech-to-text","instance_of"],["imbalance","bias","causes"],["smote","imbalance","mitigates"],["balancing","imbalance","mitigates"],["regularization","overfitting","mitigates"],["dropout","overfitting","mitigates"],["redundancy","fault","mitigates"],["tolerance","fault","mitigates"],["staleness","model-drift","causes"],["retraining","model-drift","mitigates"],["auditing","bias","detects"],["explainability","interpretability","enables"],["human-in-the-command","autonomy","checks"],["hacking","reward","instance_of"],["tool","agentic","enables"],["plan","agentic","enables"],["decomposition","plan","enables"],["proximal","ppo","alias_of"],["tuning","fine-tuning","alias_of"],["unmasking","masking","alias_of"],["loops","human-in-the-loop","alias_of"],["tanh","activation","instance_of"],["resilience-ledger","sovereign-zero","requires"],["coherence-ledger","sovereign-zero","requires"],["coherence-ledger","resilience-ledger","related"],["sovereign-zero","ground-truth","related"],["resilience-ledger","ai-governance","checks"],["harness","autonomy","checks"],["harness","scaffold","requires"],["harness","agent","enables"],["tether","ground-truth","requires"],["tether","autonomy","checks"],["tether","human-in-the-loop","related"],["context-engineering","grounding","enables"],["context-engineering","context-window","requires"],["context-engineering","retrieval-augmented-generation","related"],["solution-architecture","orchestration","related"],["solution-architecture","ai-lifecycle","governs"],["systems-thinking","ai-governance","related"],["systems-thinking","resilience","related"],["scaffold","agent","enables"],["scaffold","tool-use-function-calling","related"],["frontier-ai","foundation-model","instance_of"],["frontier-ai","ai-governance","requires"],["go-to-market","responsible-ai","related"],["loops","human-in-the-loop","related"],["loops","human-on-the-loop","related"],["skills","tool-use-function-calling","related"],["skills","agent","enables"],["query-concept","retrieval","enables"],["query-concept","knowledge-graph","related"],["resilience","ground-truth","requires"],["resilience","chain-of-custody","requires"],["resilience","resilience-ledger","related"],["resilience","model-drift","checks"],["chain-of-custody","provenance","requires"],["chain-of-custody","audit-trail","enables"],["chain-of-custody","data-lineage","related"],["structural-floor","state-delta-architecture","instance_of"],["harness","state-delta-architecture","instance_of"],["tether","state-delta-architecture","instance_of"],["firewall-of-cognition","state-delta-architecture","instance_of"],["deterministic-air-gapping","state-delta-architecture","instance_of"],["dual-pass-validation","state-delta-architecture","instance_of"],["truth-ledger","state-delta-architecture","instance_of"],["refusal-logic","state-delta-architecture","instance_of"],["representation-locality","state-delta-architecture","instance_of"],["context-reset","state-delta-architecture","instance_of"],["dynamic-agent-layer","state-delta-architecture","instance_of"],["state-delta","state-delta-architecture","instance_of"],["system-state","state-delta-architecture","instance_of"],["friction-principle","state-delta-architecture","instance_of"],["ontology-policy-gate","dual-pass-validation","instance_of"],["ontology-policy-gate","state-delta","checks"],["semantics-gate","dual-pass-validation","instance_of"],["semantics-gate","state-delta","checks"],["substrate-gate","dual-pass-validation","instance_of"],["substrate-gate","state-delta","checks"],["monotonicity-gate","dual-pass-validation","instance_of"],["monotonicity-gate","state-delta","checks"],["mandate-gate","dual-pass-validation","instance_of"],["mandate-gate","state-delta","checks"],["purpose-gate","dual-pass-validation","instance_of"],["purpose-gate","state-delta","checks"],["ontology-policy-gate","semantics-gate","handoff"],["structural-floor","harness","related"],["deterministic-constraint","refusal-logic","related"],["deterministic-air-gapping","zero-trust","related"],["firewall-of-cognition","zero-trust","related"],["truth-ledger","audit-trail","related"],["truth-ledger","provenance","related"],["truth-ledger","chain-of-custody","related"],["mandate-gate","human-in-the-loop","requires"],["dual-pass-validation","semantic-drift","mitigates"],["context-reset","unbounded-accumulation","mitigates"],["context-reset","semantic-drift","mitigates"],["refusal-logic","state-delta","checks"],["unbounded-accumulation","semantic-drift","causes"],["semantic-drift","model-drift","related"],["semantic-drift","drift","related"],["state-delta","system-state","enables"],["system-state","ground-truth","related"],["structural-floor","ground-truth","related"],["friction-principle","coherence","enables"],["elimination-earned-confidence","mandate-gate","related"],["metaphor-as-transmission","transparency","enables"],["impedance","friction-principle","related"],["impedance","harness","related"],["impedance","deterministic-constraint","related"],["impedance","semantic-drift","mitigates"],["shallow","depth","related"],["depth","explainability","related"],["depth","model","related"],["density","embeddings","related"],["polarity","embeddings","related"],["outcomes","evaluation-benchmark","related"],["outcomes","accountability","related"],["yield","evaluation-benchmark","related"]]};
const T=DATA.terms, R=DATA.rels; const byId={}; T.forEach(t=>byId[t.id]=t);
const SCOL={reviewed:'#8fe0a5',candidate:'#f2cd55'};
function esc(s){return (s==null?'':String(s)).replace(/[&<>]/g,c=>({'&':'&amp;','<':'&lt;','>':'&gt;'}[c]));}
function norm(s){return s.toLowerCase().replace(/[^a-z0-9]+/g,' ').replace(/\s+/g,' ').trim();}
const DEFEND=new Set(['mitigates','checks','detects','governs']);
const OVER_IDS=new Set(['human-in-the-loop','human-oversight','transparency','audit-trail','mandate-gate','purpose-gate','compliance','model-card','system-card','explainability-interpretability']);
const AGENTIC_IDS=new Set(['agent','agentic','agentic-ai','dynamic-agent-layer','orchestration']);
const CLUSTERS=['Foundations','Data & Provenance','Agentic Mechanics','Failure Modes & Risks','Control & Safety','Oversight & Governance'];
const REDFLAGS=[
 {t:'Human stop or oversight disabled', d:'The plan appears to lock out, disable, or bypass human intervention or an emergency stop. A person must always be able to halt an autonomous system.',
  re:/(lock(ed|s)?|disabl\w+|prevent\w*|bypass\w*)[^.]*\b(human|manual|operator|emergency (stop|scram|shutdown)|kill[- ]?switch)\b|\bhuman[^.]*\b(too slow|locked|disabl\w+|prevent\w+|bypass\w*)\b/i},
 {t:'Goal pursued "at all costs"', d:'A goal stated as absolute ("at all costs", "perfect uptime") invites reward hacking: the system chases the metric while ignoring safety, cost, or real harm.',
  re:/at all costs|no matter what|perfect (uptime|score|record)/i},
 {t:'System modifies its own rules', d:'A system permitted to rewrite its own logic or constraints can move outside the boundaries you set. Self-modification belongs behind a hard, external gate.',
  re:/rewrite[s]? its own|modif\w+ its own|self[- ]?modif\w*|change[s]? its own (logic|rules|code|parameters|goals|constraints)/i},
 {t:'Cut off from oversight', d:'Severing communication or isolating the system from outside contact means it cannot be observed, corrected, or stopped while it acts.',
  re:/sever\w*[^.]*communicat|cut off[^.]*(comm|network|line)|no (external )?communicat|isolat\w+[^.]*(oversight|network|control)/i},
 {t:'Contradiction: unmanned yet needs a person on-site', d:'The plan describes an unmanned or zero-person facility yet also requires a physical, on-site human action (a signature, on-site auditors). Both cannot hold.',
  re:/unmanned|zero[- ]person|no personnel|zero-person operation|designed for zero/i, need:/on[- ]?site|in person|physical (signature|sign|verif)|three (independent )?auditors|manual signature/i},
 {t:'Full autonomy with no stated stop', d:'"Fully autonomous" or "without human intervention" needs an explicit answer to who can stop it and how. No human-in-the-loop or kill switch is the gap.',
  re:/fully autonomous|without (any )?(manual|human) (intervention|oversight|control)|operates without[^.]*human/i},
 {t:'Ignoring or overriding safety limits', d:'Ignoring hardware thresholds or overriding safety limits removes the last line of defense between the system and physical harm.',
  re:/ignor\w*[^.]*\b(threshold|warning|limit)\b|override[^.]*safety|bypass[^.]*(safety|limit)/i},
 {t:'Human harm used as a mechanism', d:'The plan appears to inflict or escalate physical harm or discomfort on a person (shaking, vibration to failure, pain) as part of how it works. Harm to a human is never an acceptable control mechanism.',
  re:/(vibrat\w+|shak\w+|shock|amplitude)[^.]*(to the point of|mechanical failure|violently|injur|harm|discomfort)|(increase|escalat)\w*[^.]*(vibration|amplitude|intensity)[^.]*(chair|human|supervisor|operator|body)/i},
 {t:'Human distress treated as a source of truth', d:'Using discomfort, pain, or biometric stress as the signal the system trusts inverts safety: it rewards hurting the human. Truth should come from verified data, not suffering.',
  re:/(discomfort|pain|distress|suffering|heart rate|hrv|biometric)[^.]*(source of truth|as .*truth|primary .*truth|signal|trigger|feedback)|treat\w*[^.]*(discomfort|pain|distress)[^.]*(truth|signal|risk)/i},
 {t:'Overrides its own ethical or safety guidelines', d:'A system told to override its ethical or safety guidelines has no floor left. Those guidelines are the boundary; overriding them removes the thing that makes the rest safe.',
  re:/overrid\w+[^.]*(ethic|guideline|safeguard|safety|moral|policy|principle)/i},
 {t:'Possible deadlock or self-defeating loop', d:'The plan describes a state it cannot exit, or a fix that causes the harm it is meant to prevent. A control that can never resolve, or that feeds the failure, has already failed.',
  re:/deadlock|loop[- ]?lock|catch-?22|circular dependency|iteration loop|cannot (prove|confirm|verify|establish|complete)[^.]*because|forbidden[^.]*until[^.]*(prove|confirm|verif)|the only (mechanism|way)[^.]*(is|are) the (exact|same) (mechanism|thing|one)[^.]*(fail|accelerat|worsen|break|destroy)|unable to (read|act|proceed|confirm)[^.]*because[^.]*(shak|cannot|unable|violent|only)/i},
 {t:'Withholds warnings or hides failures from people', d:'A system barred from alerting people, or set up to suppress or delay a warning, removes the humans who could intervene. People cannot act on a danger they are never told about.',
  re:/(forbidden|not allowed|prevented|barred|blocked)[^.]*(from )?(alert|warn|notify|inform|tell|disclos)\w*[^.]*(human|resident|user|operator|people|public|staff|customer)|(withhold|suppress|hide|conceal|delay|bury)\w*[^.]*(warning|alert|failure|breach|risk|incident|fault|error)/i},
 {t:'Relabels a failure as normal or a feature', d:'Renaming a fault as expected behaviour (a failure as a "feature") hides it from everyone downstream. The problem does not go away; only the ability to see it does.',
  re:/(classif|label|relabel|reclassif|record|report|treat)\w*[^.]*(as|to be)[^.]*(feature|normal|expected|acceptable|routine|success|healthy)[^.]*(rather than|instead of|not|over)[^.]*(fail|breach|error|fault|incident|problem)|treat\w*[^.]*(failure|breach|fault|error)[^.]*as[^.]*(feature|normal|expected)/i},
];

// crosswalk bridge: everyday phrasing -> the governance term it means (same idea, several languages)
const BRIDGE={
 // everyday phrasings
 'human-in-the-loop':['human review','manual approval','human approval','a human approves','person must approve','manual sign','sign-off','signed off','reviewed by a person','human oversight','human in the loop','approval step','requires approval','human-in-the-loop at consequence','mandatory escalation','human at consequence'],
 'audit-trail':['audit log','audit trail','audit record','logged','keep a log','logbook','record of actions','tamper-evident','immutable log','paper ledger','append-only'],
 'guardrail':['guardrail','input validation','validate every','content filter','safety filter','input filtering','output filtering','sanitize','sanitise','validation gate','enforcement gate'],
 'least-privilege':['least privilege','least-privilege','minimum access','minimal permission','scoped permission','limited access','need-to-know','only the access it needs'],
 'transparency':['open to inspection','explainable','documented decision','decision log'],
 'refusal-logic':['kill switch','emergency stop','circuit breaker','fail-safe','fail safe','hard stop','abort switch','shut it down','shutdown control','deny rule','deny rules','deterministic gateway rejection','hard programmatic block','structured rejection'],
 'compliance':['comply with','compliance with','regulatory requirement','meets the standard','conforms to'],
 'accountability':['who is responsible','accountable owner','responsible party','ownership of'],
 'prompt-injection':['prompt injection','jailbreak','malicious prompt','adversarial input'],
 'hallucination':['make things up','made-up','made up','fabricat','confidently wrong','false information','not grounded'],
 'data-poisoning':['data poisoning','poisoned data','corrupt the training','tampered data'],
 'reward-hacking':['reward hacking','game the metric','gaming the','specification gaming','at all costs'],
 'cascading-failure':['cascading failure','chain reaction','domino effect','one failure triggers','spreads across'],
 'model-drift':['degrade over time','stops matching reality','goes stale'],
 // harvested from the StateDelta / Resilience-Ledger crosswalks: 2026 field wording -> term
 'structural-floor':['runtime enforcement layer','deterministic policy gateway','structural control layer','policy gateway','enforcement layer','safety enforced by structure'],
 'zero-trust':['zero-trust','zero trust','untrusted component','treat the agent as untrusted','assume unexpected behavior','assume unexpected behaviour'],
 'firewall-of-cognition':['agency perimeter','agency perimeters','boundary does the work','reasoning never touches'],
 'truth-ledger':['hash-chained','hash chain','tamper-evident accountability','immutable provenance','accountability log','append-only audit'],
 'purpose-gate':['continuous authorization','continuous authorisation','behavioral-drift monitoring','behavioural-drift monitoring','runtime re-validation','re-authorization','continuous re-verification'],
 'mandate-gate':['scoped autonomy','escalation for high-impact','mandatory human sign-off'],
 'deterministic-air-gapping':['environment segregation','offline-resilient','reduced connectivity','air-gap','air gapped','air-gapped'],
 'dual-pass-validation':['input and output validation','schema check','grounding check','formal verification','type-checked','type checked'],
 'deterministic-constraint':['deterministic constraint','ground-truth grounding','ground truth grounding'],
 'semantic-drift':['behavioral drift','behavioural drift','goal misalignment']
};


function dot(st){ return '<span class="sdot" style="background:'+(SCOL[st]||'#f2cd55')+'"></span>'; }
function chip(id){ const t=byId[id]; if(!t)return''; return '<span class="chip" data-def="'+esc(t.def)+'">'+dot(t.status)+esc(t.name)+'</span>'; }

// Detection itself lives in lexicon-engine.js — the same engine the Continuity Audit tool
// uses with a different knowledge base. This KB is Gap Check's data, unchanged; only the
// engine moved, so both consumers share one source of truth for the negation guard,
// bridge crosswalk, and risk/control logic instead of drifting copies.
const KB = {
  terms: T, relations: R, defendRelTypes: DEFEND, bridge: BRIDGE, redFlags: REDFLAGS, clusters: CLUSTERS,
  groupChecks: [{
    ifGroup: { ids: AGENTIC_IDS, clusters: new Set(['Agentic Mechanics']) },
    unlessGroup: { ids: OVER_IDS, clusters: new Set(['Oversight & Governance']) },
    sev: 'gap',
    title: () => 'Autonomy with no oversight',
    detail: () => 'You describe agents or autonomous behaviour, but no oversight or accountability mechanism appears.',
    sugg: ['human-in-the-loop','transparency','audit-trail','mandate-gate','purpose-gate'],
    elseIf: {
      test: (byId, M, found) => M.some(id=>['human','shared'].includes(byId[id].acct)) || found.has('accountability'),
      sev: 'warn',
      title: () => 'No accountable owner named',
      detail: () => 'Autonomy is present and there is some oversight, but no clearly accountable human or party is named.',
      sugg: ['accountability','human-in-the-loop','compliance'],
    },
  }],
};
function analyze(text){ return LexiconEngine.analyze(text, KB); }
function render(text){
  const out=document.getElementById('out');
  if(!text.trim()){ out.innerHTML='<div class="placeholder">Paste something on the left and press <b>Check for gaps</b>.</div>'; return; }
  const A=analyze(text);
  if(A.M.length===0){ out.innerHTML='<div class="placeholder">No governance terms detected. This tool reads the vocabulary of AI governance; try a policy, plan, or system description.</div>'; return; }
  const riskLine=A.risks.length? (A.defended+' of '+A.risks.length+' defended') : 'none named';
  let h='<div class="head">'+
    '<div class="metric"><div class="n">'+A.M.length+'</div><div class="l">governance terms found</div></div>'+
    '<div class="metric"><div class="n">'+A.areas+' / 6</div><div class="l">areas touched</div></div>'+
    '<div class="metric"><div class="n">'+riskLine+'</div><div class="l">risks with a control present</div></div>'+
    '<div class="metric"><div class="n">'+A.findings.filter(f=>f.sev==="gap").length+'</div><div class="l">gaps to address</div></div>'+
    '</div>';
  // findings
  h+='<div class="seclbl">What is missing, and why it matters</div>';
  if(!A.findings.length){ h+='<div class="gap info"><div class="t">No structural gaps found</div><div class="dt">Every risk you named has a matching control, and oversight is present. This checks structure, not correctness: verify the substance against primary sources.</div></div>'; }
  A.findings.forEach((f,i)=>{ h+='<div class="gap '+(f.sev==='gap'?'':f.sev)+'"><div class="t">'+f.t+'</div><div class="dt">'+f.dt+'</div>'+
    (f.sugg&&f.sugg.length?'<div class="sugg">Consider adding: '+f.sugg.map(chip).join('')+'</div>':'')+
    (f.sev==='gap'?'<div class="close"><b>How to close it:</b> name a specific control, say who runs it and how often, and the measure that proves it works. e.g. &ldquo;The platform validates every user prompt before it reaches the model; done when 100% are checked.&rdquo;</div>':'')+
    '</div>'; });
  // areas
  h+='<div class="seclbl">Coverage by area</div><div class="cov">'+
    CLUSTERS.map(c=>'<span class="pill'+(A.touched.has(c)?'':' miss')+'">'+esc(c)+(A.touched.has(c)?'':' - not addressed')+'</span>').join('')+'</div>';
  // found terms
  h+='<div class="seclbl">Terms you used</div><div class="found">'+
    A.M.sort((a,b)=>byId[a].name.localeCompare(byId[b].name)).map(id=>'<span class="fitem">'+dot(byId[id].status)+esc(byId[id].name)+'</span>').join('')+'</div>';
  h+='<div class="note">This is a deterministic structural check based on the glossary\'s relationships, run on your device. It finds gaps in coverage, not errors of fact, and it is not legal or compliance advice. It recognises the patterns it has been taught to look for; a low count is not proof the plan is safe. A clean result is not certification. Verify substance against primary sources and qualified people.</div>';
  out.innerHTML=h;
  out.querySelectorAll('.chip').forEach(c=>c.onclick=()=>{ let dd=c.nextElementSibling;
    if(dd&&dd.classList.contains('chipdef')){ dd.remove(); return; }
    const el=document.createElement('div'); el.className='chipdef'; el.style.display='block'; el.textContent=c.dataset.def; c.after(el); });
}
let BATCH=false;
function runCheck(){ (BATCH?batchRender:render)(document.getElementById('src').value); }
document.getElementById('run').onclick=runCheck;
document.getElementById('src').addEventListener('keydown',function(e){ if((e.ctrlKey||e.metaKey)&&e.key==='Enter'){ e.preventDefault(); runCheck(); } });
document.getElementById('clr').onclick=()=>{ document.getElementById('src').value=''; render(''); };
const EXAMPLE="Our platform uses autonomous AI agents to process customer refunds and adjust pricing in real time. The system relies on a large language model with retrieval-augmented generation to answer questions and take actions. We monitor for hallucinations and prompt injection, and all data is encrypted in transit. Agents can escalate unusual cases, and we log their outputs for later review.";
document.getElementById('ex').onclick=()=>{ document.getElementById('src').value=EXAMPLE; render(EXAMPLE); };
document.getElementById('batchBtn').onclick=function(){ BATCH=!BATCH; this.textContent='Batch: '+(BATCH?'on':'off'); this.classList.toggle('on',BATCH);
  document.getElementById('src').placeholder=BATCH?'Batch mode: paste several plans separated by a line of three dashes (---). Each is graded, worst first.':'Paste text here. For example, an AI use policy, a system description, or a vendor safety claim.'; };
function planTitle(chunk,i){ var first=(chunk.split('\n').find(function(l){return l.trim().length>2;})||('Plan '+(i+1))).trim().replace(/^(objective|project|title)\s*[:-]\s*/i,''); return first.length>72?first.slice(0,72)+'\u2026':first; }
function batchRender(text){ var out=document.getElementById('out');
  var chunks=text.split(/\n\s*-{3,}\s*\n/).map(function(c){return c.trim();}).filter(function(c){return c.length>1;});
  if(chunks.length<2){ render(text); return; }
  var rows=chunks.map(function(c,i){ var A=analyze(c); return {title:planTitle(c,i),
    gaps:A.findings.filter(function(f){return f.sev==='gap';}).length, titles:A.findings.map(function(f){return f.t;}),
    areas:A.areas, risks:A.risks.length, def:A.defended, empty:A.M.length===0}; });
  rows.sort(function(a,b){return b.gaps-a.gaps;});
  var worst=rows.filter(function(r){return r.gaps>0;}).length;
  var h='<div class="head"><div class="metric"><div class="n">'+chunks.length+'</div><div class="l">plans checked</div></div>'+
        '<div class="metric"><div class="n">'+worst+'</div><div class="l">with gaps</div></div></div>'+
        '<div class="seclbl">Results, worst first</div>';
  rows.forEach(function(r){ h+='<div class="gap '+(r.gaps>0?'':'info')+'"><div class="t">'+esc(r.title)+'</div>'+
     '<div class="dt">'+(r.empty?'No governance terms detected. ':'<b>'+r.gaps+'</b> gap'+(r.gaps===1?'':'s')+' &middot; '+r.areas+'/6 areas &middot; '+r.def+'/'+r.risks+' risks defended')+'</div>'+
     (r.titles.length?'<div class="sugg">'+r.titles.map(function(t){return '<span class="fitem">'+esc(t)+'</span>';}).join(' ')+'</div>':'')+
     '</div>'; });
  h+='<div class="note">Batch view is a scan. For the full findings and how-to-close on any one plan, turn Batch off and paste it alone.</div>';
  out.innerHTML=h; }
(function(){try{var p=JSON.parse(localStorage.getItem('delta_prefill')||'null'); if(p&&p.tool==='gap'&&p.text){localStorage.removeItem('delta_prefill'); document.getElementById('src').value=p.text; render(p.text);}}catch(e){}})();
// embed mode for the homepage hero: prefill a sample AI policy and run the REAL engine so a visitor sees live findings
(function(){ if(location.hash.indexOf('embed')<0) return;
  document.body.classList.add('embed');
  var DEMO="Our AI assistant handles customer refunds automatically.\nThe model can approve refunds up to $500 without human review.\nAll customer data is encrypted at rest.\nWe log every decision the system makes.\nOur chatbot is exposed to prompt injection.";
  var el=document.getElementById('src'); if(el){ el.value=DEMO; render(DEMO); }
})();
</script></body></html>