REG-Vault

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

With no annotations, the description carries the full transparency burden. It discloses the returned data (title, year, publisher, etc.) and 'Fetch' implies read-only, but it does not address failure modes (e.g., not found), authentication, or other behavioral nuances. It provides basic context but lacks depth.

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 a single, tightly packed sentence that covers purpose, parameters, and return fields. No word is wasted, and it is front-loaded with the core action.

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 simple two-parameter lookup with no output schema, the description is largely complete: it explains what the tool does, how to invoke it, and what it returns. Missing details like error responses or system identifier format are not critical given the simplicity and the presence of sibling tools like list_systems.

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?

The schema already describes slug_or_hash, and the description reiterates that. It adds that the lookup is per system, but leaves the 'system' parameter vague (no format or example). Schema coverage is 50%, so the description partially compensates but doesn't fully clarify all parameter semantics.

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 clearly states the tool's function with a specific verb ('Fetch'), a specific resource ('a single game'), and the exact lookup criteria ('by system + canonical slug OR ROM hash'). It also lists the returned fields, making the purpose unmistakable. This distinguishes it from sibling tools like search_games (search) and list_systems (systems list).

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 description implies usage: use when you have both a system and a canonical slug or ROM hash. It does not explicitly mention alternatives or exclusions, such as 'use search_games when you don't have the exact slug.' The context is clear but the guidance is not explicitly articulated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns counts by letter (A-Z, 0-9, other), which gives some transparency about the output. However, it omits important details such as whether zero-count letters are included, what 'other' precisely covers, and the exact response format. This is a moderate disclosure.

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 a single efficient sentence that front-loads the core functionality and then adds the use case. There is no redundant or filler wording; every word contributes to understanding the tool.

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?

Given the absence of an output schema and annotations, the description must explain more about the return value and edge cases. It only says 'per-letter game count' without specifying the structure of the result, what happens for systems with no games, or how 'other' is defined. This is insufficient for a tool with no structured documentation to rely on.

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?

The schema description coverage is 0%, and the description only says 'for a system' without explaining what a system is, whether it's an ID or name, or any valid values. The tool name already implies the per-system scope, so the description adds minimal semantic value. The parameter meaning is largely left to the agent's inference.

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 clearly states what the tool does: it returns per-letter game counts for a given system, including numbers and 'other'. This is a specific verb+resource+scope that distinguishes it from sibling tools like get_game (individual game details) and list_systems (system list). The alphabet navigation use case further clarifies its purpose.

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 description provides a clear use case ('useful for alphabet navigation'), which tells the agent when to use it. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5 but earns a 4 for clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the burden. It implies a read-only aggregation but doesn't explicitly state side effects, data freshness, or any caveats. For a stats tool this is adequate but not rich.

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?

A single, well-structured sentence that immediately conveys the tool's scope. No filler or redundant information.

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 no-parameter tool with no output schema, the description provides the main output categories. However, 'assets coverage' is somewhat ambiguous and could benefit from a brief clarification of what it measures.

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?

The tool has zero parameters; the schema fully documents this. The description adds value by listing the fields the stats cover (total games, systems, assets coverage), which helps set expectations, though no parameter details are needed.

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 clearly states that the tool provides global REG-Vault catalogue statistics, specifying the three main outputs: total games, systems, and assets coverage. This distinguishes it from sibling tools like get_game (specific game) and list_systems (just systems).

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 description implies the tool is for obtaining global stats but does not explicitly mention when to use it over siblings or any exclusions. It lacks guidance like 'for specific game details, use get_game'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden. It clearly indicates a read-only list operation and the data included (game counts), but does not disclose potential response size, ordering, or authentication requirements.

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 a single 9-word sentence that front-loads the action and resource. It contains no redundant words or filler, making it highly efficient.

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?

This is a simple, parameterless list operation and the description conveys the resource and the output's key content (game counts). It does not explicitly state the return type (e.g., array), but for a no-param tool, the description is sufficiently complete.

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?

The tool has zero parameters, so the schema fully covers invocation. The description adds no parameter details, but none are needed; the baseline of 4 for no-parameter tools applies.

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 uses the specific verb 'List' with the resource 'retro-gaming systems' and the scope 'in REG-Vault with game counts'. This clearly distinguishes it from sibling tools that focus on individual games, letter counts, or stats.

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 phrasing 'List all...' implies the tool is used to retrieve the full inventory of systems with their game counts. However, there is no explicit guidance on when to choose this tool over alternatives or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It adds 'Returns up to `limit` results', which indicates result limiting, and 'across one or all systems' implying system filtering. However, it lacks details on case-insensitivity (delegated to schema), ordering, or what happens with no results, which prevents a higher score.

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 two short sentences, front-loaded with the main action and scope, and includes the key behavioral note about result limits. Every word earns its place, with no fluff or redundancy.

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 straightforward search tool with 3 parameters and no output schema, the description covers the core search behavior, system filtering, and result limiting. It is sufficient for high-level invocation, though it omits details about the exact interpretation of 'all systems' and the return format, which is acceptable given the absence of an output schema.

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 coverage is 67% with query and system described, but limit lacks a schema description. The description adds meaningful semantics for limit by stating it caps the number of returned results, and for system via 'one or all systems'. This provides value beyond the schema but does not fully compensate for the missing limit documentation.

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 clearly states the tool searches games by title across one or all systems, with a specific verb+resource. It distinguishes from siblings like get_game (exact lookup) and list_systems (system listing) by emphasizing title-based search. The phrase 'across one or all systems' adds scope clarity.

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 description provides clear context for when to use the tool (searching games by title substring) but does not explicitly mention alternatives or when not to use it. Sibling tool names suggest get_game is for exact ID lookup, but the description does not reference this distinction, leaving the agent to infer.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.