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

Beyond the readOnlyHint annotation, the description discloses the response structure ('mlbStats.columns names the aligned values in mlbStats.standard and the optional mlbStats.recent14d and mlbStats.recent30d arrays') and the authentication context. This gives the agent a clear picture of what to expect without an 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.

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

Three compact sentences with key information front-loaded: purpose, usage trigger, and data structure. No filler 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?

Even without an output schema, the description explains the return value layout (columns and arrays) and gives usage context, plus the readOnly annotation covers side effects. It is sufficient for an agent to select and invoke the tool correctly.

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 explains both parameters fully (season default, playerNames source and max items). The description adds no new parameter meaning; it only restates 'up to 10 players' and 'full player names,' which are already in the schema. With 100% schema coverage, the baseline 3 is appropriate.

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 opens with a specific verb 'Fetch' and names exact resources ('MLB Stats, Baseball Savant, and FanGraphs analysis') with a clear scope ('up to 10 players'). This distinguishes it from the singular sibling 'analyze_player_stats' and clearly states the tool's 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?

It explicitly states when to use the tool: 'Use this after reading roster or free-agent names from the signed-in Yahoo browser.' However, it does not name alternative tools or exclusions, so it stops short of a full 5.

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?

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds useful context about aggregating data from three external sources, but does not disclose potential latency, rate limits, or what specific statistics are included. This is acceptable but not rich behavioral detail.

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?

Two sentences, front-loaded with purpose and immediately followed by exclusion guidance. Every word contributes; no filler or redundant content.

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?

The tool is a read-only data fetch with simple parameters and no output schema. The description adequately explains what it does and when to use it, though it omits details about return format or which 'advanced statistics' are included. This is a minor gap for a tool of this complexity.

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 100%, with both parameters (playerName, season) already described. The description reinforces that playerName is for a single player but adds no new semantic meaning beyond what the schema provides. Baseline 3 is appropriate.

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 'Fetch and aggregate advanced statistics for a single player' from named sources (MLB Stats, Baseball Savant, FanGraphs). It explicitly notes 'single player', which distinguishes it from the sibling tool 'analyze_players_stats' (plural).

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?

Provides explicit guidance: 'Use Yahoo's browser pages separately for league scoring, ownership, roster, and lineup context.' This tells the agent when NOT to use this tool and directs to alternative methods for different contexts.

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?

Beyond the readOnlyHint annotation, the description adds meaningful context: data is 'locally saved' and the tool does not perform live Yahoo checks. This helps set expectations about source and side-effect-free behavior, though it could mention return format or missing-preference behavior.

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?

Two concise sentences with no fluff. The first sentence states the core function; the second adds a critical limitation. Every word earns its place, and the key information is front-loaded.

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 zero-parameter getter with no output schema, the description is complete: it explains what the tool returns, where the data comes from (local), and what it explicitly does not do (Yahoo verification). This is sufficient for an agent to invoke it correctly.

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?

With zero parameters, the baseline is 4. The description adds value by explaining the output content (the default league and team), which compensates for the empty input schema and clarifies the tool's purpose.

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?

Description uses a specific verb ('Get') and clearly identifies the resource: 'locally saved default Yahoo league and team'. It distinguishes itself from sibling tools like fantasy_set_default_team (a setter) and the analysis/list tools by focusing on local preferences.

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 states it is for 'browser-driven workflows' and clarifies a key limitation: it does not inspect Yahoo or verify signed-in status. This implies when to use it (offline/local preference retrieval) and when not to rely on it (live Yahoo data), though it doesn't name an explicit alternative.

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?

Annotations already indicate the tool is neither read-only nor destructive, so the description's added context that it 'stores local identifiers only and does not call Yahoo' provides valuable extra transparency about network behavior and side effects. This goes beyond the annotations and helps the agent understand the tool's actual impact.

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 sentences with no filler. The key facts are front-loaded: the action, the resource, and the crucial behavioral clarification about not calling Yahoo. Every sentence earns its place.

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 local save operation with no output schema, the description covers purpose, data source, and network behavior. It doesn't discuss overwrite behavior or failure modes, but the low complexity and rich schema/annotations make this sufficient for effective use.

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?

All four parameters have descriptions in the schema (100% coverage), so the description doesn't need to repeat them. It adds the context that identifiers come from the signed-in browser, but doesn't provide additional syntax or format details beyond what the schema already documents.

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 specifies the action ('Save') and the resource ('a Yahoo league and team discovered from the signed-in browser'), and distinguishes from sibling tools by noting this stores local identifiers only and does not call Yahoo. This makes the tool's purpose unambiguous and differentiates it from the analysis/query siblings.

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 a clear use case: when the agent has identified a Yahoo league/team in the browser and wants to persist it as the default. It doesn't explicitly state when not to use it or name alternatives, but the context provided is sufficient for an agent to infer appropriate usage.

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?

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds value by specifying the data source (MLB Stats only) and clarifying what is excluded (Yahoo ownership/availability), plus listing the output fields. No contradictions noted.

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?

Two concise sentences front-load the main purpose and add only necessary caveats. Every sentence earns its place with no 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 simple single-parameter list tool with a readOnly annotation, the description is complete: it states the output fields, the data source, and the important caveat about Yahoo data. No output schema exists, but the description sufficiently covers the return context.

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 input schema has 100% coverage with the date parameter described as 'Date as YYYY-MM-DD; defaults to today.' The description does not add further parameter detail, so it meets the baseline but provides no extra value beyond the schema.

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 lists every probable starting pitcher across MLB for a date, with opponent, home/away, and game time. This is a specific verb + resource + scope, and it distinguishes itself from the sibling fantasy tools by focusing on MLB stats rather than fantasy preferences or analysis.

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?

It explicitly says 'This tool uses MLB Stats only' and instructs to read Yahoo ownership/availability separately from the signed-in Yahoo browser, giving clear when-to-use and when-not-to-use context. However, it does not name a specific alternative sibling tool, so it falls short of a 5.

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