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compare_semantic_equivalence

Read-onlyIdempotent

Compare two payloads under the dual-hash design: content_hash is invariant to field order and numeric formatting (5 vs '5.00'); semantic_hash additionally to field renaming. Verdicts: identical_content, same_structure_and_values_renamed_vocabulary, or semantically_different.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesGeodesicAI API key (gai_...)
payload_aYesFirst structured payload (arbitrary JSON object)
payload_bYesSecond structured payload to compare against payload_a

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description additionally explains the comparison semantics (content_hash vs semantic_hash) and the possible verdicts, providing behavioral insight beyond the annotations without contradicting them.

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

Conciseness5/5

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

The description is concise and well-structured, starting with the core action, then explaining the hash distinction, and ending with possible verdicts. Every sentence adds value without redundancy.

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

Completeness4/5

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

Given the tool's complexity and lack of an output schema, the description covers the essential behavior and result space. It explains the dual-hash approach and lists all verdicts, making the tool's behavior understandable. It could theoretically detail return structure, but the core context is sufficiently complete.

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

Parameters3/5

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

Schema coverage is 100% for the three parameters, so the baseline is 3. The description adds conceptual context about how payload_a and payload_b are compared, but does not provide additional syntax or constraint details beyond the schema.

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?

The description clearly states the tool's function with a specific verb ('Compare') and resource ('two payloads'), and it distinguishes itself via the dual-hash design and explicit verdicts. This is more specific than sibling tools like validate or analyze_anomaly, making its purpose unambiguous.

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

Usage Guidelines4/5

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

The description implies usage whenever semantic equivalence of payloads is needed, and it provides clear context about the hash mechanisms. It does not explicitly mention alternatives or exclusion scenarios, but the context is sufficient to guide appropriate use.

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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TDQS

A3.6/5.0
Disambiguation3/5

Most tools have distinct purposes, but several pairs overlap heavily (validate vs validate_repair, repair vs repair_path, analyze_anomaly vs check_drift vs decompose_failure). Detailed descriptions help disambiguate, but the large number of analytics and diagnostics tools creates real selection risk.

Naming Consistency4/5

The vast majority use a consistent snake_case verb_noun pattern (create_blueprint, list_api_keys, verify_certificate). A few single-word or noun-phrase exceptions (validate, forecast, structural_types, recent_inference_decisions) are minor deviations, but overall the pattern is predictable.

Tool Count2/5

At 37 tools, this exceeds the 25+ threshold for 'too many'. While the governance domain is broad, the set could be consolidated (e.g., merging validate_repair into validate, folding repair_path into repair, or trimming diagnostics-tier tools like check_realization and geometric_confidence).

Completeness4/5

The surface covers the full blueprint lifecycle, validation, repair, API key management, discovery, inference governance, and chain management. Minor gaps exist: no direct get_blueprint (only list with counts), and chain lifecycle lacks delete/list/cancel operations. Overall, agents can accomplish core governance tasks without dead ends.

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