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Ai Changes

boosthis_ai_changes
Read-only

What happened after the changes Boosthis witnessed here - only those that passed through it: a fix it served, or a sentence it was asked to check. Each reads kept, broken or cant_tell, in the promise vocabulary and refused for the same named reasons. cant_tell is the ordinary answer: thin evidence, never that the change was fine. No score for any assistant, and none derivable. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.3/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered structurally. The description adds genuine behavioral context: outcome values are kept/broken/cant_tell, cant_tell means thin evidence rather than approval, and no assistant score is exposed or derivable. It also reinforces 'Read-only,' which is redundant but consistent.

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 description is not bloated, but it is cryptic and domain-specific, with the core action buried behind 'What happened after the changes Boosthis witnessed here.' It front-loads the outcome theme reasonably, yet the sentence structure and unusual vocabulary reduce immediate clarity.

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 no-parameter, read-only tool with no output schema, the description does explain the meaningful return vocabulary and cautions that cant_tell is not a clean bill of health and no score is available. It is fairly complete on output interpretation, though the lack of a plain action statement keeps it from being fully self-explanatory.

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?

The tool has zero parameters, so there are no parameter semantics for the description to clarify. Schema description coverage is 100%, and the baseline for a 0-param tool is 4.

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 description gestures at a read operation over changes Boosthis has witnessed and describes their outcome labels, but it never plainly states the verb or resource, e.g. 'list AI change outcomes.' The phrasing 'What happened after the changes Boosthis witnessed here' is evocative but leaves an agent to infer that this returns per-change results.

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?

There is no explicit when-to-use guidance, no prerequisites, and no named alternative among siblings such as boosthis_record_change or boosthis_promises. The scope 'only those that passed through it' implies a boundary, but the description does not tell an agent when this tool 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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