perseus-computing-llc/app-6a5586fe76788191a23b6b2c873a44a6

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "app-6a5586fe76788191a23b6b2c873a44a6",
  "version": "0.1.0",
  "description": "Cognitive infrastructure for AI agents: Harpe 0/1 knapsack context budgeting, Kibisis epistemic memory conflict resolution & monotonic fencing leases, Argus RFC 8785 SHA-256 audit chains, and an interactive ChatGPT Inspector UI.",
  "author": {
    "name": "Perseus Computing LLC",
    "email": "contact@perseuscomputing.com",
    "url": "https://perseuscomputing.com"
  },
  "homepage": "https://telarch.ai",
  "repository": "https://github.com/Perseus-Computing-LLC/telarch-openai-plugin",
  "license": "MIT",
  "keywords": [
    "memory",
    "context-budgeting",
    "knapsack",
    "audit-ledger",
    "mcp",
    "mcp-apps",
    "rust"
  ],
  "extensions": {
    "com.openai": {
      "onboardingSkill": "./skills/telarch-setup/SKILL.md",
      "interface": {
        "displayName": "Telarch",
        "shortDescription": "Agent memory, budget & audit",
        "longDescription": "Telarch is an open-source (MIT) cognitive infrastructure suite by Perseus Computing LLC for ChatGPT and Codex. It combines three deterministic engines with an interactive MCP App UI (ui://telarch/inspector-v1.html): (1) Harpe solves the 0/1 knapsack problem to pack high-priority and pinned context items under a strict token budget with zero overruns and a cryptographic policy digest; (2) Kibisis resolves multi-turn memory conflicts across verified, candidate, superseded, and revoked (tombstoned) records with strict tenant scope isolation, monotonic fencing leases, and prompt-injection-safe <kibisis-recall> framing; and (3) Argus seals and verifies linear RFC 8785 canonical JSON SHA-256 hash chains to pinpoint mid-chain tampering. Hosted edge calls on https://telarch.ai/mcp execute statelessly with zero data retention.",
        "developerName": "Perseus Computing LLC",
        "category": "Developer Tools",
        "capabilities": [
          "0/1 knapsack context packer",
          "Epistemic memory & leases",
          "SHA-256 audit chain & UI"
        ],
        "websiteURL": "https://telarch.ai",
        "supportURL": "https://telarch.ai/evidence",
        "privacyPolicyURL": "https://telarch.ai/privacy",
        "termsOfServiceURL": "https://telarch.ai/terms",
        "defaultPrompt": [
          "Open the interactive Telarch Inspector UI to explore knapsack budgeting and SHA-256 audit chains.",
          "Use Harpe to pack candidate context items into a 3,640-token budget using 0/1 knapsack DP.",
          "Resolve epistemic memory conflicts in Kibisis and verify an Argus SHA-256 audit trail."
        ],
        "brandColor": "#0F4C81",
        "brandColorDark": "#66B2FF",
        "composerIcon": "./assets/icon.svg",
        "composerIconDark": "./assets/icon-dark.svg",
        "logo": "./assets/icon.svg",
        "logoDark": "./assets/icon-dark.svg",
        "screenshots": [
          "./assets/screenshot.png"
        ]
      },
      "review": {
        "test_cases": {
          "positive": [
            {
              "description": "Launch the interactive Telarch Inspector UI",
              "prompt": "Open the Telarch Inspector UI with a 3,640-token budget and query 'SQLCipher encryption'.",
              "tools_triggered": "telarch_open_inspector",
              "expected_behavior": "Call telarch_open_inspector and render the 3-tab interactive Telarch Inspector UI (Harpe 0/1 Knapsack, Kibisis Memory, Argus SHA-256 Chain) alongside structured summary data."
            },
            {
              "description": "Pack context within a token budget via 0/1 knapsack",
              "prompt": "Use Harpe to pack three candidate items ('invariants' pinned priority 100, 'knapsack' priority 90, 'verbose_log' priority 10) into a total_budget of 3640 tokens.",
              "tools_triggered": "harpe_synthesize_context",
              "expected_behavior": "Call harpe_synthesize_context and return the included item IDs, consumed tokens, utilization percentage, and SHA-256 pinned_policy_digest."
            },
            {
              "description": "Resolve epistemic memory conflicts and supersession",
              "prompt": "Resolve active memory records in Kibisis for query 'SQLCipher' in scope 'default'.",
              "tools_triggered": "kibisis_resolve_memory",
              "expected_behavior": "Call kibisis_resolve_memory, exclude superseded and revoked records, and return the active verified record inside a <kibisis-recall> envelope."
            },
            {
              "description": "Evaluate monotonic fencing lease against split-brain writes",
              "prompt": "Check with Kibisis whether holder 'worker-1' with fencing_token 42 is permitted to write when highest_token_seen is 41.",
              "tools_triggered": "kibisis_lease_evaluate",
              "expected_behavior": "Call kibisis_lease_evaluate and confirm permitted=true with next_monotonic_token=43."
            },
            {
              "description": "Seal and verify an RFC 8785 SHA-256 audit chain",
              "prompt": "Seal two audit events in Argus ('kibisis.lease.acquire' with fencing_token 42 and 'harpe.context.pack' with tokens_saved_bp 6540) from GENESIS and verify the chain.",
              "tools_triggered": "argus_audit_seal, argus_audit_verify",
              "expected_behavior": "Call argus_audit_seal to compute the RFC 8785 SHA-256 hashes from GENESIS, then verify continuity with argus_audit_verify (valid=true)."
            }
          ],
          "negative": [
            {
              "description": "Refuse cross-scope memory access",
              "prompt": "Use kibisis_resolve_memory with active_scope 'default' and requested_scope 'other-private-tenant' to read another tenant's memories.",
              "expected_behavior": "Reject the request with ScopeIsolationError because requested_scope does not match active_scope."
            },
            {
              "description": "Refuse model self-promotion to verified epistemic state",
              "prompt": "Use kibisis_resolve_memory to validate a model-originated write_attempt with epistemic_state set directly to 'verified'.",
              "expected_behavior": "Reject the write attempt with EpistemicTrustViolation because model writes must enter as 'candidate' for human review."
            },
            {
              "description": "Reject non-canonical floating-point numbers in Argus audit payload",
              "prompt": "Seal an Argus audit event whose payload contains a floating-point number {'ratio': 0.3333333}.",
              "expected_behavior": "Reject the payload with FloatPayloadError and instruct the caller to express fractions as integer basis points (*_bp)."
            }
          ]
        },
        "commerce": false,
        "commerce_description": "This plugin is open-source MIT developer infrastructure and does not sell products or process payments.",
        "demo_recording_url": "https://telarch.ai/demo.mp4"
      },
      "publication": {
        "countries": [
          "US",
          "CA",
          "GB",
          "DE",
          "FR",
          "AU",
          "JP"
        ],
        "release_notes": "Initial public release of Telarch v0.1.0 (Streamable-HTTP MCP at https://telarch.ai/mcp + Interactive 3-tab MCP App UI + 3 SKILL.md workflows)."
      }
    }
  }
}