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neurogenesis__compute_efficiency_report

[neurogenesis — developmental agents: genome -> evaluation-driven growth with safety axioms + audit ledger] Free read: decision/outcome receipts, route modes, compute avoided, predicted savings, predicted-vs-observed cost/latency/energy…

Instructions

[neurogenesis — developmental agents: genome -> evaluation-driven growth with safety axioms + audit ledger] Free read: decision/outcome receipts, route modes, compute avoided, predicted savings, predicted-vs-observed cost/latency/energy coverage, and Landauer-floor context. Estimates and observations stay distinct.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.11

TDQS

C2.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does add real behavioral value by disclosing that it is a free read-only operation and that 'estimates and observations stay distinct', but omits pagination/limit behavior, data sources, and any auth or rate-limit context.

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

Conciseness3/5

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

The core content list is dense but reasonably tight. The bracketed vendor preamble ('neurogenesis — developmental agents: genome -> evaluation-driven growth...') is tagline noise occupying the front-loaded position where the tool's purpose should be.

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?

For a low-complexity, one-optional-parameter, no-output-schema read tool, the description effectively serves as surrogate output documentation by naming the report's contents and asserting the estimate/observation separation. Only the parameter and any freshness/source detail are missing.

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?

The single parameter 'limit' has 0% schema description coverage and is never mentioned in the description, so no meaning is added beyond the schema's bare name and default. With only one optional parameter the impact is small, but the description does not compensate for the coverage gap.

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

Purpose3/5

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

The name and description imply a read of a compute-efficiency report, and the description enumerates its contents (receipts, route modes, compute avoided, predicted savings, coverage, Landauer-floor context). However, it reads as a contents dump rather than a crisp verb+resource statement, and it draws no line against siblings like neurogenesis__get_ledger or metering__sla_report.

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

Usage Guidelines2/5

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

The only usage signal is 'Free read', which hints at cost but not when to call it versus neurogenesis__get_ledger or other report/ledger siblings. No prerequisites, exclusions, or alternative-selection guidance are given.

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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