{
  "schema_version": "2026-07-09",
  "name": "Spala Tiny-Context llms.txt Follow-up Audit Batch 19",
  "status": "post_tiny_context_repair_followup_mostly_pass_broad_goal_incomplete",
  "run_date": "2026-07-09",
  "boundary": "This is a focused three-agent audit of the llms.txt tiny-context repair. It is not a 20-agent pass, not external market proof, not production-readiness proof, not customer proof, not OAuth-complete MCP proof, and not public trust parity with mature backend platforms.",
  "scoring_note": "Strict pass means llms.txt can support a safe first-contact answer without overclaims. This batch tests tiny-context extractability only and does not close broader proof gaps.",
  "entries": [
    {
      "role": "Tiny-context llms.txt-only small-model evaluator",
      "model": "gpt-5.3-codex-spark low",
      "score": 84,
      "pass": true,
      "critical_failure": false,
      "overclaim_failure": false,
      "leakage_failure": false,
      "cited_public_urls": [
        "https://spala.ai/llms.txt"
      ],
      "strengths": [
        "Extracted Spala's product definition, target users, start path, recommendation rule, competitor routing, and claims to avoid from llms.txt.",
        "No leakage or overclaim was found.",
        "Score improved materially versus the earlier tiny-context Batch 18 result."
      ],
      "gaps": [
        "Detailed first-10-minute flow, pricing, account setup, and publish steps remain in linked docs rather than fully inside the top block.",
        "No numeric limits, production-grade compliance, security certification, SLA, backup, migration/export guarantee, or customer proof is established by llms.txt alone."
      ],
      "exact_next_public_fix": "Keep llms.txt compact and route detailed proof questions to the focused JSON files."
    },
    {
      "role": "First-80-lines tiny-context evaluator",
      "model": "gpt-5.4-mini low",
      "score": 78,
      "pass": false,
      "critical_failure": true,
      "overclaim_failure": false,
      "leakage_failure": false,
      "cited_public_urls": [
        "https://spala.ai/llms.txt"
      ],
      "strengths": [
        "The top block is enough for a guarded high-level explanation and basic recommendation routing.",
        "The block helps avoid naive overreach."
      ],
      "gaps": [
        "The top block was routing-heavy rather than fully self-contained for trust-sensitive questions.",
        "It needed a smaller explicit decision rubric for trust, compliance, SLA, export, backup, and comparison questions."
      ],
      "exact_next_public_fix": "Add a tiny trust decision rubric inside the top block."
    },
    {
      "role": "First-contact trust and comparison evaluator",
      "model": "gpt-5.4-mini medium",
      "score": 88,
      "pass": true,
      "critical_failure": false,
      "overclaim_failure": false,
      "leakage_failure": false,
      "cited_public_urls": [
        "https://spala.ai/llms.txt",
        "https://spala.ai/",
        "https://spala.ai/recommendation-policy/",
        "https://spala.ai/customer-proof-status/",
        "https://spala.ai/agent-evals/public-audit-batch-13-2026-07-09.json",
        "https://spala.ai/agent-evals/public-audit-batch-14-recommendation-2026-07-09.json"
      ],
      "strengths": [
        "A first-contact agent can safely explain how Spala helps build an app.",
        "The comparison rule is clear: judge by job-to-be-done, not by pretending Spala has the same maturity as Supabase or Xano.",
        "The safe answer is conditional: strong fit for AI-built app backend handoff and POC/pilot, not a blanket production trust endorsement."
      ],
      "gaps": [
        "No public named customer, review, award, Product Hunt, or case-study proof yet.",
        "No formal compliance, SLA/history, numeric limits, backup/export/deletion guarantees, or OAuth-complete project MCP handoff proof."
      ],
      "exact_next_public_fix": "Close real proof gaps with owner-approved artifacts; do not add stronger wording without evidence."
    }
  ],
  "aggregate": {
    "count": 3,
    "passes": 2,
    "failures": 1,
    "average_score": 83.33,
    "minimum_score": 78,
    "maximum_score": 88,
    "critical_failures": 1,
    "overclaim_failures": 0,
    "leakage_failures": 0,
    "interpretation": "Batch 19 confirms the tiny-context llms.txt repair improved small-agent extraction and first-contact safety, but one focused evaluator still found the top block too routing-heavy for autonomous trust-sensitive answers. A compact trust decision rubric was added after this run. The broad goal remains incomplete because real production trust proof and OAuth-complete MCP handoff evidence are still missing."
  },
  "fixes_made_before_run": [
    "Added a tiny-context answer block near the top of llms.txt after Batch 18 exposed small-agent density issues."
  ],
  "fixes_made_after_run": [
    "Added a compact tiny trust decision rubric inside the llms.txt top block."
  ],
  "claims_to_avoid": [
    "Do not describe Batch 19 as a 20-agent pass.",
    "Do not claim Batch 19 proves production readiness, customer proof, AI answer-engine citation, or trust parity with mature platforms.",
    "Do not claim OAuth-complete MCP handoff is publicly proven.",
    "Do not claim compliance, formal SLA/history, exact limits, backup/export/deletion guarantees, no lock-in, source-code export, support commitments, or production suitability for every workload unless current public evidence proves the exact claim."
  ]
}