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Homo Universalis — HU-DIAMOND v1.1 Cryptographic Verifier & AST Kintsugi MCP Server

by ai.homouniversalis
OverviewDiscussionsAdmin

simulate_diamond_spiral_budget

Read-onlyIdempotent

Compute deterministic LLM call counts, token budgets, and EUR/Seed costs for 1 to 4 spiral turns of the 8-vertex Diamond Wheel multi-agent orchestrator. Use this tool only to estimate call volume and cost before launching a multi-agent run, or use verify_diamond_crucible_and_ast to audit Python code and RM(1,3) proofs, and verify_sovereign_shield_merkle to notarize text in an RFC 6962 Merkle tree. Zero-auth, stateless, and free (0.00 EUR), executing pure arithmetic without invoking any LLM. Each spiral turn (rounds 1..4) adds 9 LLM calls (4 creators, 4 antipodal auditors, and 1 barycenter synthesizer, totaling 9, 18, 27, or 36 calls, plus 10 final inquisition calls when rounds=4), while tier='supreme' prices calls for gemini-4-argon (10,000 to 64,000 Seeds / 10.00 to 64.00 EUR) and tier='flash' prices calls for gemini-3.8-flash at reduced cost, and lang localizes vertex role descriptions.

Input Schema

NameRequiredDescriptionDefault
langNoOutput language for localized vertex and budget breakdowns ('en' English, 'es' Spanish, or 'ca' Catalan).en
tierNoModel pricing tier ('supreme' for gemini-4-argon Deep Think or 'flash' for high-speed gemini-3.8-flash).supreme
roundsNoNumber of spiral turns (`1..4`, corresponding to `9, 18, 27, or 36` spiral calls plus the 10-call Supreme Inquisition dome on round 4).

Output Schema

NameRequiredDescriptionDefault
langNo
budgetYes
oracleNo
statusYes
equationNo
verticesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / lang / description
      Previous value: -"Output language code ('ca', 'es', or 'en')."New value: +"Output language for localized vertex and budget breakdowns ('en' English, 'es' Spanish, or 'ca' Catalan)."
    • changedInput schema / properties / lang / enum
      Previous value: -[
-  "ca",
-  "es",
-  "en"
-]New value: +[
+  "en",
+  "es",
+  "ca"
+]
    • changedInput schema / properties / rounds / description
      Previous value: -"Number of spiral turns (`1..4`, corresponding to `9, 18, 27, 36` Deep Think calls)."New value: +"Number of spiral turns (`1..4`, corresponding to `9, 18, 27, or 36` spiral calls plus the 10-call Supreme Inquisition dome on round 4)."
    • changedInput schema / properties / tier / description
      Previous value: -"Engine tier ('supreme' for gemini-4-argon or 'flash' for gemini-3.8-flash)."New value: +"Model pricing tier ('supreme' for gemini-4-argon Deep Think or 'flash' for high-speed gemini-3.8-flash)."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, but the description adds materially new behavior: zero-auth, stateless, free at 0.00 EUR, and pure arithmetic that invokes no LLM. It also discloses the exact call-count formula (9 per turn, plus 10 inquisition calls at round 4) and the price ranges per tier.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first clause and every sentence carries information, so there is no filler. However, the final sentence is an extremely dense run-on that packs call-count math, tier pricing, and language behavior together, which makes it harder to scan than a short bulleted breakdown would be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description need not explain return values, and it still covers everything else an agent needs: safety profile, auth (none), cost (zero), what gets computed, and how each of the three parameters shifts the result. Nothing required to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description earns a step up by giving concrete outcomes for parameter values – tier='supreme' maps to gemini-4-argon at 10,000–64,000 Seeds / 10.00–64.00 EUR, and lang localizes vertex role descriptions. Some of this (the rounds-to-call-count mapping) duplicates the schema text rather than adding to it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource – computing deterministic LLM call counts, token budgets, and EUR/Seed costs for 1 to 4 spiral turns of the 8-vertex Diamond Wheel orchestrator. It also names both siblings and what they do instead, so the agent can route without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly scopes use to pre-run estimation ("Use this tool only to estimate call volume and cost before launching a multi-agent run") and points to the two alternatives for auditing code and notarizing text. When-to-use and when-to-use-something-else are both stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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