verify_vqe_energy
QC-013 VQE problem, not the variational search. Same ZZ law as execute_2local_hamiltonian. Presented config energy. Floats refused.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| config | No | ||
| constraints | No |
QC-013 VQE problem, not the variational search. Same ZZ law as execute_2local_hamiltonian. Presented config energy. Floats refused.
| Name | Required | Description | Default |
|---|---|---|---|
| config | No | ||
| constraints | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It does disclose meaningful constraints: this is a VQE-energy verification task rather than a search, it follows the same ZZ law as execute_2local_hamiltonian, and floats are refused. But it does not say what 'verify' returns, whether it mutates state, or what 'refused' means at the API level, so the behavioral picture is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, with no filler, but it is fragmented and telegraphic: 'Presented config energy' and 'Floats refused' are not complete sentences and may confuse more than help. The terse style saves space but sacrifices enough grammatical clarity that it cannot earn a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, two undocumented parameters, and no required fields, this description is too thin. An agent cannot reliably know what config and constraints should contain, what a successful verification looks like, or how the relationship to execute_2local_hamiltonian should inform the call. The description gives useful hints but is not self-sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only vaguely alludes to 'config energy' and says 'Floats refused'. The constraints parameter is never explained, no format is given for either string, and there is no guidance on how config and constraints relate. This is a real gap for an agent trying to construct valid arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the tool as a QC-013 VQE problem verifier and explicitly distinguishes it from 'the variational search', so an agent can tell what scope it covers. It also references the same ZZ law as execute_2local_hamiltonian, which further anchors its purpose, though it never spells out a full verb phrase like 'verifies whether the presented config energy is correct'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'not the variational search' gives one clear when-not signal, and the reference to execute_2local_hamiltonian gives a related tool comparison. However, there is no explicit guidance on when to choose this tool over sibling verifiers such as verify_qaoa_energy or verify_presented_pair, and no stated prerequisite or invocation context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many verify_* tools are distinct, but there are overlapping clusters: math_court duplicates execute_2local_hamiltonian, route_spin_glass_manifold, and the quantum verifiers; project_affine_key, expose, verify_presented_pair, and the optional affine exposes in other tools blur together; weather and geometry tools also overlap. The detailed descriptions help a human, but an agent would likely struggle to choose between equivalent-seeming entry points.
Naming is mostly snake_case but otherwise inconsistent: some tools use dotted prefixes (atc.*, twin.robotics.*, weather.*), some use bare verbs (expose, lattice_op, math_court), some use noun phrases (corpus_bonds, feeds_catalog), and others mix prefixes with verbs (ide_rebuild_mesh, umc_resume). The verify_* family is consistent, but the overall set has no single predictable verb_noun pattern.
49 tools is far above the typical well-scoped server size and includes multiple near-duplicate paths to the same law (math_court, execute_*, route_*, verify_*). While not quite 50+, the count still feels like a sprawling kitchen-sink rather than a deliberate minimal surface.
The toolset covers a surprisingly wide range: QC verifiers, QMA laws, affine projections, corpus reads, weather, UMC state, and robotics IK. However, there are notable gaps for such a broad surface: no general court case lifecycle beyond expose/seal, no corpus content search, and no way to manage or update sealed artifacts; several areas have only entry-point coverage.