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UnboundCompute

lachesis-mcp

Official

candidate_census

Access constructor census metadata, exhaustive counts, and analysis frontiers to differentiate empty results from missing coverage.

Instructions

Report constructor metadata, exhaustive counts, and explicit analysis frontiers. Use this to distinguish an empty result from missing coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNotext (compact, default) | json (structured result page)
constructor_idNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully conveys that the tool reports exhaustive counts, analysis boundaries, and a meaningful empty-vs-missing distinction. However, it does not explicitly disclose side effects, read-only nature, or output shape, which would be valuable given the absence of annotations and output schema.

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 only two sentences, with no redundant phrasing. The primary function is stated first, and the actionable use case is provided second. Every sentence contributes meaningful information.

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

Completeness3/5

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

The description gives a solid high-level purpose but does not clarify whether constructor_id is expected or what the census scope is (one constructor or all constructors). It also does not explain what 'explicit analysis frontiers' means operationally. For a simple, two-parameter report tool, the description is mostly adequate but leaves room for ambiguity in a corpus of many sibling tools.

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

Parameters2/5

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

Schema description coverage is only 50%, so the description should compensate for undocumented parameters. It does not discuss 'format' or 'constructor_id' at all, leaving the meaning of constructor_id to be inferred from the tool name. The one enumerated parameter is described in the schema, but the description does not clarify how the two parameters interact with the census behavior.

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

Purpose4/5

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

The description clearly identifies the action ('Report...') and the object (constructor metadata, exhaustive counts, analysis frontiers). It also states the main semantic purpose: distinguishing an empty result from missing coverage. It lacks explicit differentiation from sibling tools like candidates or coverage_map, but the verb and resource are specific enough.

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 sentence 'Use this to distinguish an empty result from missing coverage' provides a clear trigger condition and application context. It does not explicitly name alternative tools or exclusions, but it gives the agent enough guidance to know when this report is the right choice.

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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