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

With no annotations provided, the description carries the full transparency burden. It clearly signals a read-only diagnostic operation and discloses the quota cost of 1 unit. For a zero-parameter status check, this is adequate behavioral 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 two short sentences with no wasted words. The primary purpose is front-loaded, followed by a practical usage directive and quota cost.

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 authentication status tool, the description covers what it does, what it reports, when to run it, and its cost. Nothing necessary for correct invocation is missing.

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 baseline is 4. The description correctly avoids adding irrelevant parameter details, and the empty schema fully documents the parameter surface.

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 states a specific verb ('Confirm') and resource ('stored credentials'), and clearly indicates the output: which channel the credentials control. This also distinguishes it from sibling video-management tools.

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 instruction 'Run this first when something is misbehaving' gives a clear and actionable usage context for a diagnostic tool. It does not explicitly name alternatives, but no sibling serves the same auth-checking purpose, so this is sufficient.

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 and does disclose a non-obvious behavior: 'Figures lag real time by roughly two to three days.' It also clarifies the date-range scoping and dimension behavior; the read-only nature is strongly implied by 'analytics/performance,' though not explicitly stated.

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 short, front-loaded statements cover scope, dimension choices, and the staleness caveat. No filler or redundant restatement of the tool name.

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 read-only analytics call with no output schema or annotations, the description covers the essential invocation details: date format, dimension behavior, and data lag. The main gap is the undocumented metrics parameter and the absence of any return-shape hint, but these are minor for this level of 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 description coverage is 0%, so the description must compensate. It explains start_date/end_date format and the values of dimensions, but says nothing about the metrics parameter or how metrics should be formatted, leaving part of the parameter surface undocumented.

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 by identifying the resource and scope: 'Channel-wide performance over a date range.' It lacks an explicit verb like 'retrieve' or 'get,' but the parseable dimension options ('day' for time series, 'video' for per-video breakdown) make the tool's purpose and difference from video_analytics clear.

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 gives explicit within-tool routing: 'Pass dimensions="day" for a time series, or "video" for a per-video breakdown of the period.' It also provides the date format, but it never explicitly contrasts this tool with the sibling video_analytics or states when not to use it, so it stops 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.

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

There are no annotations, so the description carries the behavioral disclosure burden. It adds valuable context: ~3 unit quota cost, authorized-channel scoping, newest-first ordering, and a read-only retrieval purpose. It does not explicitly mention pagination or read-only status, but the core behavior is clear and useful.

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 short sentences with no filler: the primary behavior is first, followed by quota cost and the agent-relevant usage note. 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 read-only list tool with one optional parameter and an output schema, the description covers scope, ordering, cost, and the main use case. It could be slightly stronger with explicit alternatives or a mention of max_results, but it is otherwise sufficient.

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 description coverage is 0%, and the description never mentions max_results. The single parameter is optional with a self-explanatory title and default, so invocation risk is low, but the description does not compensate for the missing schema description.

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 and resource: 'List recent uploads on the authorized channel, newest first.' It clearly defines scope and ordering, and it is easy to distinguish from the mutation-focused siblings like upload_video and update_video.

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 'Use this to find the video_id the other tools need,' which tells an agent when this tool is the right entry point. It does not name specific sibling alternatives or state when not to use it, so it stops 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.

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

With no annotations provided, the description takes on the full transparency burden. It discloses quota cost, timezone behavior for publish_at, and the side effect of keeping the video private until the scheduled time. This is strong behavioral context, though it does not cover every possible edge case.

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 three tight sentences with the main purpose front-loaded. The remaining details—quota cost, timestamp format, and side effect—are all high-value and each earns its place. There is 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?

For a two-parameter tool with no output schema and no annotations, the description covers the essential invocation details: what the tool does, timestamp format, quota cost, and visibility side effect. Minor omissions like requiring a future publish_at date or describing the return value do not critically impair correct usage.

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 description coverage is 0%, so the description must compensate. It adds concrete semantics for publish_at by specifying ISO 8601 format, UTC interpretation, and an example. The video_id parameter is not explicitly detailed, but the phrase 'existing private video' clarifies that it refers to an already-uploaded video.

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 states a specific operation: scheduling an existing private video to go public at a given time. This clearly differentiates it from sibling tools like upload_video and update_video. The scope is precise and leaves no ambiguity about the resource being acted on.

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 correct usage context: use this for already-existing private videos that need to be published on a schedule. It does not explicitly name alternatives or exclusions, but the use case is clear enough to route an agent to the right tool.

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 behavioral burden and does meaningful work: it discloses a quota cost of ~50 units, an authorization requirement, and file constraints. It could further disclose whether the thumbnail replaces an existing one and what the response or failure modes are, but the key operational behavior is present.

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 three short, purposeful sentences with the action first. The quota cost, prerequisite, and file constraints each earn their place with no fluff or repetition.

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 mutation with no annotations and no output schema, the description covers prerequisites, quota, and accepted image inputs. It is slightly incomplete around whether image_path is local and what the effect on an existing thumbnail is, but not enough to hinder correct invocation.

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 description coverage is 0%, so the description must compensate; it adds concrete semantics for the image value (format, size, recommended dimensions) but does not explain video_id provenance or whether image_path is a local file path versus URL. The provided constraints clearly attach to image_path by context, making this partial rather than absent.

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 a clear verb and resource ('Set a custom thumbnail') and is supported by the video_id/image_path arguments, so an agent can infer the target is a video thumbnail. It does not explicitly contrast itself with siblings like update_video, so it misses full differentiation.

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 a concrete precondition ('verified channel with custom thumbnails enabled') and technical constraints (JPEG/PNG, under 2MB, 1280x720 recommended), giving clear context for when this tool is applicable. It does not name alternative tools or when-not-to-use conditions.

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 of behavioral disclosure. It reveals quota cost (~51 units), explains the read-then-merge-write mechanism, and clarifies that passing only 'title' will not blank the description—a subtle but important side effect. This is transparent and highly useful for an agent deciding how to call the tool safely.

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 compact and front-loaded with purpose. Every sentence earns its place: the first states the action, the second quantifies cost, and the third explains a non-obvious merge behavior. No filler or repetition.

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 description covers the essential behaviors—quota, merge semantics, partial update guarantee—and the schema covers required and optional parameters. However, it does not specify what happens when a field is passed as null (clear vs. no-op), nor does it describe the response format, which could matter given there is no 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 description coverage is 0%, but the description adds meaningful semantics beyond the raw schema: 'Only the fields you pass change' and the merge example explain how parameter omission behaves. Individual fields are self-explanatory from their names, though the description does not elaborate on each parameter or the meaning of an explicit null value.

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 starts with a specific verb and resource: 'Change the metadata on an existing video.' The phrase 'existing video' clearly distinguishes this from upload_video and other sibling creation tools. It is immediately obvious what the tool operates on and what action it performs.

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 when to use the tool—when you need to update metadata on an existing video without replacing unspecified fields—but it never explicitly names alternatives or states when not to use it. The merge behavior gives contextual guidance, but there is no direct 'use upload_video for new videos' type exclusion.

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 and does well: it discloses quota cost, that publish_at forces privacy_status to private, and that made_for_kids is a legal COPPA declaration. These are non-obvious behavioral traits beyond a simple upload action.

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 front-loaded with the core action, then adds quota cost, parameter constraints, and category examples in a logical order. Every sentence adds value and none simply repeats schema 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?

The description covers many important operational details, but with no annotations and no output schema it still leaves gaps: it does not describe the response/return value, file_path format or location requirements, or error/auth failure modes. For an 8-parameter upload tool, this is a noticeable but not fatal omission.

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 description coverage is 0%, so the description must explain parameters. It usefully explains privacy_status values, publish_at format and interaction, made_for_kids implications, and common category_id values. It does not explain file_path, title, description, or tags, but those are relatively self-explanatory.

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 first sentence, 'Upload a video file to the authorized channel,' identifies a specific verb, resource, and scope. It is unambiguous and clearly differentiates from siblings like update_video or set_thumbnail.

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 gives clear context for when to use the tool for uploading and provides parameter-level guidance like scheduling via publish_at. However, it never explicitly mentions alternatives or when not to use this tool, such as when schedule_video or update_video would be more appropriate.

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 disclosure burden. It usefully mentions the separate YouTube Analytics API quota and the two-to-three-day data lag. However, it does not disclose return format, pagination, authorization requirements, or how the default metrics list behaves.

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 concise and front-loaded: the first sentence states the core function and scope, and the second adds relevant operational caveats. Every sentence earns its place with no filler.

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 four parameters, no output schema, and no annotations, the description should provide more context. It covers date format, quota, and data lag, but omits metric semantics, output shape, and authentication expectations, leaving an agent with important gaps.

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 description coverage is 0%, so the description must compensate. It only clarifies the YYYY-MM-DD format for start_date and end_date. It does not explain video_id or the metrics parameter, leaving key semantics undocumented.

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 states the tool provides performance metrics for one video over a date range, clearly identifying the resource and scope. It distinguishes itself from sibling tools like channel_analytics by specifying 'one video,' though it does not explicitly name the alternative.

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 when to use the tool: when you need performance data for a single video within a date range. It does not explicitly state when not to use it, nor does it name alternatives such as channel_analytics for channel-wide metrics.

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