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

The description adds behavioral detail beyond annotations: it specifies what happens to members (not started vs running) and the credit release. Annotations already cover idempotent and destructive hints, but the description enriches them. No contradiction.

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 dense sentence, front-loaded with 'RELEASES RESERVED CREDITS' to capture the core effect immediately. It includes an essential instruction ('Ask the user first') and is efficiently structured with no waste.

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 primary behavior and user consent, but omits the return value and error conditions. Since there is no output schema, this is a notable gap. For a destructive tool, it should indicate what happens on success or failure. Adequate but incomplete.

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 provides no information about the group_id parameter beyond its name and pattern in the schema. It does not explain how to obtain or validate the ID. Since coverage is low, the description should compensate but fails to do so.

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 action: cancels a group and releases reserved credits, with specific behavior for members not started vs running. The title reinforces the purpose. However, it does not explicitly differentiate from sibling tools, though the action is distinct from reads or confirmation.

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 a clear prerequisite: 'Ask the user first,' which guides when to use this tool (after user consent). It implies it should not be used without confirmation, but does not mention alternatives or exclusions. This is useful context, though not exhaustive.

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 establish readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral nuance: results are clamped to the tier and reported, and music-led shows are marked rather than removed. This goes beyond what annotations provide.

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 contain a lot of useful information with no filler. The main purpose and key behavioral constraints are front-loaded, and the reference to search_shows is compact. 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?

The tool is simple and read-only, and annotations cover safety. However, there is no output schema, and the description relies on 'same shape as search_shows' rather than describing the response. It also does not address the language parameter or the mechanics of the reported clamp, leaving moderate gaps for an agent invoking this tool.

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 67%, covering size and language. The description adds meaning for size by noting clamping and 'up to size shows', and gives an example category ('Business'). Language is not mentioned in the description, and category values are only lightly exemplified, so it does not fully compensate for the undocumented category parameter.

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 identifies the resource ('one category's chart') and the behavior ('up to size shows, clamped to the tier and reported'). It references search_shows for shape, giving some differentiation. However, it lacks an explicit verb like 'list' or 'get' and does not precisely contrast its use case with siblings beyond the shape reference.

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?

Usage is implied: this tool returns a category chart, while search_shows is mentioned for shape. There is no explicit when-to-use or when-not-to-use guidance, and no alternative is named for comparison. The description gives context but leaves the choice between chart_shows and search_shows to inference.

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?

While annotations already flag destructiveHint=true and idempotentHint=false, the description adds crucial context: it warns 'SPENDS CREDITS' up front, explains that a mismatched expected_total_credits causes a refusal, and details idempotency_key reuse ('reused on retry so nothing spends twice'). This goes well beyond what annotations alone convey.

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 entire description is a single, information-dense sentence. It front-loads the most critical warning ('SPENDS CREDITS'), and every clause earns its place—covering user consent, parameter handling, and idempotency. There is 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 mutation tool with three required parameters, the description fully covers the operational context: credit implications, how to obtain the quote reference, the safety check on expected total, and retry behavior. No output schema exists, so its absence is not a gap. An agent has everything needed to call this 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 documents each parameter, but the description enriches them: it instructs to pass quote_ref as the quote returned it, restate the total as expected_total_credits (and warns about disagreement), and use a fresh idempotency_key that is reused on retry. These nuances are not present in the schema's bare definitions, so they add real 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 clearly states the tool's function: 'turns a quote into a job group, reserving up to its total_ceiling_credits.' This is a specific verb-action with a distinct resource, and it differentiates from siblings like quote and cancel_group by being the confirmation step. Even the title reinforces the 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 gives an explicit prerequisite: 'Ask the user first.' It also implies the proper context (after obtaining a quote) and provides behavior on disagreement ('a disagreement is refused'). However, it does not explicitly list when *not* to use it or name alternative tools (e.g., cancel_group) for the cancellation path, so it lacks explicit exclusions.

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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond annotations, particularly that include_previews=false polls without reading any content and that full transcript URLs require authentication. This extra context helps the agent understand side-effect-free polling and access 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 dense but front-loaded with the core purpose and contains no filler. It is a single long sentence that packs in rollup contents, transcript previews, URL details, and the polling behavior. More structure, such as separating the preview behavior, would improve readability, but every phrase 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?

With no output schema, the description does a good job enumerating expected return contents: member states, credits, transcript previews, and authenticated URLs. It also covers the include_previews polling variant. It is sufficiently complete for an agent to call the tool correctly, though some terms like 'member states' and 'already-paid cache read' could be more explicit.

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 documents include_previews with 'Default true.', and the description adds behavioral meaning by explaining the false case. group_id has no schema description, though the pattern and the overall description imply it identifies the job group. With 50% schema coverage, the description partially compensates but does not 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 identifies the resource as 'One job group's rollup' and lists what it contains, making the tool's purpose clear. It does not explicitly use a verb like 'get' or 'retrieve', but 'rollup' strongly implies a status read. It does not differentiate itself from sibling tools such as list_groups, so it stops short of a 5.

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 that this is for a single job group's status, which implies the primary use case. It also provides guidance on the include_previews parameter with 'include_previews false polls without reading any'. However, it does not explicitly state when to prefer this tool over list_groups or read_transcript.

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, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'newest first' ordering and mentions 'Trusted block' and 'Fenced block' fields, but these are cryptic and not explained. It doesn't mention pagination behavior or response structure beyond the schema's cursor and limit, so the added value beyond annotations is minimal.

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 convoluted and not front-loaded. The opening clause is clear, but the rest is a run-on with confusing dashes and cryptic phrases ('Trusted block', 'Fenced block'). It could be simplified to two clear sentences without losing meaning.

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?

There is no output schema, so the description should describe return values. The 'Trusted block: ids, dates, durations, estimates. Fenced block: titles' is too vague to tell the agent what to expect. Pagination is only hinted at via the cursor parameter in the schema, not explained in the description. Given the tool has 5 parameters and no output schema, this definition is incomplete.

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 only 40% (limit and cursor have descriptions, but show_id, feed_url, and itunes_id do not). The description tells the agent to pass these as returned by search_shows or chart_shows, which gives a source for the values but not their semantic meaning or format. It also implies all three should be passed, even though only show_id and feed_url are required, adding ambiguity.

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 phrase 'A show's episodes, newest first' clearly states the verb, resource, and ordering. However, the trailing clause 'with the episode_id a quote's episode_ids takes — how to reach an older episode' is cryptic and muddles the core purpose, making it less crisp than a clean definition.

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 no explicit when-to-use guidance or exclusions relative to sibling tools. It only instructs how to pass parameters ('Pass show_id, feed_url and itunes_id as search_shows or chart_shows returned them'), not when to choose this tool over alternatives. The 'how to reach an older episode' hint is vague and doesn't clearly route the agent to a decision.

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 cover safety (readOnlyHint, idempotentHint, destructiveHint). The description adds valuable behavioral context beyond annotations: ordering (newest first), the exact fields returned, and the explicit exclusion of members. This is useful for an agent to predict the tool's output and side effects, though it doesn't detail response format or pagination details beyond the limit parameter.

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 worded sentence that front-loads the core purpose and content, then immediately provides routing guidance. Every phrase carries information with zero waste.

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 list tool with one optional parameter and no output schema, the description is complete. It tells the agent what will be returned (fields and ordering), what will not be returned (members), and how to get a single group instead. Combined with the annotations and schema, nothing essential is missing for 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?

The schema covers the single parameter 'limit' with a clear description ('Page size.'), and schema coverage is 100%, so the baseline is 3. The tool description adds no additional meaning about the limit parameter, so the score remains at baseline.

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 verb 'list' and the resource 'job groups' for the account, and specifies the content: id, status, size, and timestamps, while explicitly excluding members. It also distinguishes itself from the sibling tool group_status by directing users to use that for a single group.

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 explicitly names the alternative tool group_status and the condition for using it ('for one'), providing clear routing. It also implicitly signals that if members are needed, this tool is not appropriate, which helps an agent decide 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?

The description discloses key behaviors beyond the annotations: it explicitly states 'reserves nothing', which is important given the idempotentHint is false and the tool could be mistaken as a side-effecting operation. It also reveals that it returns 'balance_credits and reserved_credits' as the only view of remaining credits for API-key callers, and notes the openWorldHint by saying 'usage pages are dashboard-only'. It also details the return contents (priced entries, exclusions with reasons, total_ceiling_credits, confirm_with) and that chart requires a category, going well beyond the annotations.

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, well-structured paragraph that front-loads the most critical information ('Price a selection before spending; reserves nothing') and then goes into detail. Every sentence provides value: it names the two input modes, describes the output fields, and highlights the credit balance functionality. There is no verbosity or repetition; it is concise yet comprehensive.

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 tool's complexity (nested objects, 4 parameters, no output schema), the description is highly complete. It explains the primary use case, the required input form, the output structure (including exclusions and total_ceiling_credits), and a unique side effect (credit balance view). It also mentions the open-world nature (usage pages are dashboard-only), which is not in the schema. The description fills in nearly all gaps an agent would need to call it correctly, including the critical constraint of 'exactly one' and the confirm_with detail.

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 50%, and the description clarifies key parameter usage: it explains that 'shows' must come from 'search_shows or chart_shows' (which is also in the schema but reinforces), and that the tool requires 'exactly one of shows or chart'. It also mentions the chart's 'category' field. However, it does not elaborate on all parameters like include_music_led or the meaning of episode_ids, but the schema provides some descriptions. The description adds the crucial constraint of 'exactly one' that is not explicit in the schema, so it adds significant value over 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 states a specific action ('Price a selection before spending; reserves nothing') and clearly identifies what the tool does: it returns pricing information for either shows or a chart. It distinguishes itself from siblings by mentioning 'Exactly one of shows (feed URLs from search_shows or chart_shows) or a chart' and clarifies it is a pre-spend step, unlike confirm which would execute. The purpose is unambiguous and distinct from the other 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 description clearly states when to use this tool: 'before spending' and 'reserves nothing', indicating it is for pre-purchase evaluation. It also provides a contrast with 'confirm' by mentioning 'confirm_with (what confirm takes)' and implies the tool should be used before confirm. However, it does not explicitly list exclusions or alternatives (e.g., when to use search_shows vs quote), but the usage context is clear enough for most cases.

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, idempotentHint, and destructiveHint, covering safety. The description adds important behavioral context: the preview is fenced and cut on segment boundaries, and the full transcript URL requires an Audivo API key. It does not contradict annotations.

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 with the exclusive-or condition, then details the output. Every sentence contributes. Minor redundancy exists in saying 'a job's status and, once completed, its transcript' but it is not wasteful.

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 tool with no output schema, the description covers the input choices, output structure (preview + URL), and authentication requirement. It lacks details on pagination or error handling but these are not critical given the tool's simplicity.

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 0%, so the description must compensate. It clearly explains what job_id and read_id represent, including the implication that read_id is free to read. It adds meaning beyond the schema's minimal patterns.

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 reads a transcript and provides a preview plus a URL, distinguishing itself from siblings like list_episodes and quote by focusing on transcript retrieval. However, it does not explicitly name a sibling as alternative for similar functionality.

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 explains the two mutually exclusive input options (job_id vs read_id) and their states (completed vs already paid), which guides when to use each. It does not mention exclusions or alternatives to this tool, but the context is clear enough for an agent to select it appropriately.

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 establish this is a read-only, idempotent, non-destructive call, and the description does not contradict them. It adds useful behavior beyond annotations by indicating the response is split into trusted and fenced blocks and which identifier fields are safe/needed for downstream calls, although it does not explain the trusted/fenced semantics in 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?

The description is four short, front-loaded sentences with no filler; the core action appears first, followed by output block fields and the downstream call pattern. The unfamiliar 'Trusted block'/'Fenced block' phrasing takes some decoding but is still compact.

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?

With no output schema, the description compensates by listing the returned fields in trusted/fenced blocks and telling the agent what to pass next. It omits any explanation of what 'trusted' vs 'fenced' means and does not discuss pagination or no-result behavior, but the annotations and parameter schema cover safety and parameter constraints.

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?

Input schema covers both parameters fully (q as 'Show name' and limit as 'Page size'), so the baseline is 3. The description merely reiterates q's meaning with 'by name' and adds no new parameter-level guidance such as matching behavior or defaults.

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 'Find shows by name,' a specific verb and resource that distinguishes it from sibling chart_shows, list_episodes, and quote. It further clarifies purpose by stating that a selected show's feed_url and itunes_id are meant to be passed to list_episodes or quote, so the agent knows this is the lookup/search precursor.

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 final sentence gives clear downstream context: use this tool to discover shows, then pass the trusted feed_url and itunes_id to list_episodes or quote. It does not explicitly list when-not-to-use cases or compare with chart_shows, but the practical workflow is clear enough to guide selection.

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