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

With no annotations, the description carries the full burden, and it does add one genuinely useful behavioral fact: a language target may incur separate charges. However, it is silent on the critical paid-consent gating implied by the allow_paid and allow_unknown_cost flags, on whether the job runs asynchronously, and on what happens on failure or duplicate language targets.

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 short sentences with the action stated first and the cost caveat second; nothing is redundant or buried. The description is front-loaded and easy to scan.

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 four-parameter mutation tool with no annotations, no schema descriptions, and no output schema, the description is too thin. It omits the consent semantics of the boolean flags, the async nature of the resulting job, and how to check progress, leaving the agent under-informed about how to call it safely.

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 for all four parameters. It only gestures at project_id and target_language via prose ('to a dubbing project', 'target-language job'), and never explains the two boolean flags that determine whether a paid job is permitted. The 'may incur separate charges' line hints at cost but does not connect it to allow_paid or allow_unknown_cost.

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 gives a specific verb+resource: add one target-language job to a dubbing project. That is clearly distinct from siblings such as create_dubbing_project or get_dubbing_status, so an agent can place it in the dubbing workflow. It stops short of naming an explicit alternative, which keeps it from 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 phrase 'to a dubbing project' implies a project must already exist, but the description never states prerequisites or when to use this versus create_dubbing_project or get_dubbing_status. There are no exclusions and no guidance on calling it repeatedly for multiple languages.

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 exist, so the description carries full behavioral burden, yet it discloses almost nothing: not whether the operation is remote/paid (despite allow_paid and allow_unknown_cost parameters hinting at cost), not what is produced or where, and not whether anything is mutated. 'The documented forced-alignment endpoint' defers to external documentation rather than describing 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?

A single front-loaded sentence with no wasted words. It is concise, though the brevity comes partly at the cost of substance.

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 five-parameter tool with no annotations, no output schema, and no parameter documentation, the description is far too thin. An agent cannot know what the call returns, where alignment.json is written, or what the cost-gating flags do.

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% for 5 parameters, and the description only loosely implies that input_path is a local audio path and text is the transcript. The output filename, the max 100k text length, and especially allow_paid and allow_unknown_cost (which gate spending) are left completely unexplained.

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?

States a specific verb and resource: aligning supplied text to a local audio file via forced alignment. The phrasing slightly inverts the tool name (align_audio_to_text), which could momentarily confuse direction, but the operation is identifiable and distinct from any sibling (none of which do forced alignment).

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?

No guidance on when to choose this over transcribe_audio (the inverse operation) or transcript_to_subtitles, no prerequisites, and no mention of when it should not be used. Usage must be inferred entirely from the name and description.

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 supplied, so the description carries the entire behavioral burden and it discloses almost nothing: no file format/size constraints, no latency expectations, no upload behavior for the local path, and no mention of what happens on failure. Most importantly, the schema exposes allow_paid and allow_unknown_cost flags whose risk semantics (this operation can incur cost) are never explained despite being the highest-stakes aspect of the call.

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 front-loaded sentence with no filler or repetition. It is efficient, though the brevity comes at the cost of the specification gaps noted elsewhere rather than from tight editing of sufficient 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?

For an 8-parameter audio-transformation tool with no annotations, no output schema, and no schema descriptions, one sentence is not enough to call it correctly. The agent lacks cost-safety guidance, default behavior for model_id and output_format, and any expectation about the returned artifact.

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% across 8 parameters, so the description must compensate and only loosely does: 'target voice' gestures at voice_id and 'local recording' at input_path, but filename, model_id, output_format, remove_background_noise, allow_paid, and allow_unknown_cost receive no meaning at all. Six undocumented parameters with non-obvious semantics (notably the two cost-safety flags) is a substantial gap.

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 and resource ('transform a local recording into a target voice') and names the underlying operation ('speech-to-speech endpoint'), which distinguishes it from text-to-speech siblings like generate_speech and from isolate_voice. It stops short of explicitly differentiating itself from the neighboring voice tools, so an agent must infer the boundary.

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?

There is no guidance on when to use this instead of isolate_voice, generate_speech, or convert_audio, nor any stated prerequisites such as needing an existing source file on the local filesystem. 'Documented speech-to-speech endpoint' gestures at external documentation without providing the selection criteria an agent needs.

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 exist, so the description carries the full burden. It usefully discloses the consent gate, a three-sample cap, and that cost authorization is a two-part gate, but it never says what cloning produces (voice ID? preview?), whether the operation costs credits, or whether it can overwrite an existing voice. For a no-annotation mutation tool that is a meaningful gap, though the gating disclosures are above average.

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 with no filler, front-loading the action and then the prerequisites in the order an agent must satisfy them. Nothing could be removed without losing 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 an 8-parameter mutation tool with a nested labels object, zero annotations, and no output schema, the description covers the risky gates but leaves the agent guessing about side effects, cost, and result shape. Adequate to avoid a wrong call, not adequate to predict what a correct call yields.

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% across 8 parameters, so the description must compensate. It injects real meaning into three of them ('up to three sample files' → sample_paths, 'rights/consent confirmation' → rights_and_consent_confirmed, 'both paid authorization gates' → allow_paid and allow_unknown_cost), but name, labels, description, and remove_background_noise get nothing, leaving half the surface unexplained.

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?

States a specific verb and resource: 'Create an instant voice clone from local audio samples.' 'Instant' and 'local audio samples' distinguish it in kind from siblings like design_voice, create_voice_from_preview, and remix_voice, though none are named explicitly.

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?

Lists hard prerequisites (consent confirmation, max three samples, both paid authorization gates), which is genuine when-can-I-call guidance. It never says when to prefer this over design_voice or create_voice_from_preview, nor what to do if the user lacks consent or paid authorization.

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 behavioral burden. It usefully discloses that the output is actually encoded and verified rather than a rename, but says nothing about overwrite semantics, whether the input file is preserved, output destination, failure modes, or permission/disk 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?

Two tight, front-loaded sentences with no filler; the purpose leads and the caveat follows. The second clause is slightly awkwardly worded ('changing an extension alone is not used') but does carry real informational weight.

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 four-parameter, no-output-schema, no-annotation mutation tool, the description is too thin: it never states where the converted file lands, how it is named, or how errors and overwrites are handled. An agent could not reliably call this correctly without guessing at filename/overwrite behavior.

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 for four undocumented parameters. It clarifies the meaning of 'format' (real transcoding) but never explains the distinction between 'filename' and 'input_path' (output name? source name?) or what 'overwrite' controls, leaving the two most error-prone parameters ambiguous.

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?

States a specific verb and resource ('Convert a local audio file') plus the engine used (FFmpeg), which is enough for an agent to distinguish it from sibling tools like normalize_audio, trim_audio, or merge_audio. It never names those siblings explicitly, so the differentiation is inferred rather than stated.

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?

There is no when-to-use guidance and no alternatives named, so an agent must infer from the name alone whether to convert versus trim, normalize, or split. The phrase 'local audio file' gives a weak scoping hint (filesystem inputs, not uploaded assets) but no 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?

No annotations are supplied, so the description carries the full disclosure burden, yet it never says that this is a non-blocking job that returns an identifier to be polled, nor does it mention cost gating, permission needs, or failure modes. 'Validated against the checked-in current OpenAPI contract' is a process remark about the server, not observable behavior, so it does not compensate.

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?

It is short and the purpose sentence is front-loaded, but the second sentence mostly restates that validation happens rather than adding call-relevant information. Little is wasted, yet little is delivered either.

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 tool with a required opaque nested object, no output schema, and no annotations, the description leaves the agent without the shape of the request body or the asynchronous result. It is not enough to call the tool correctly without consulting external documentation.

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% across three parameters, including a free-form nested 'parameters' object whose allowed keys are entirely undocumented. The one useful hint, that the request must match the checked-in OpenAPI contract, is only a pointer to external documentation and adds no concrete meaning for allow_paid or allow_unknown_cost.

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?

It names a concrete verb and resource ('Create speech') and signals that this runs through a separate async flow API, which sets it apart from a plain generation call. However, it never explains how the async flow differs from generate_speech or generate_speech_stream, so an agent cannot confidently prefer one over the other from the description alone.

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?

There is no statement of when to use this tool, when not to, or which sibling to pick instead. The presence of get_async_speech strongly suggests a follow-up polling step, but the description never says so, leaving the agent to infer the whole workflow.

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 behavioral burden. It usefully discloses that the output is not claimed to have a seamless boundary, but it omits important behavior such as what file is written, how overwrite is handled, and whether the source audio is modified.

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 definition is two concise sentences with no wasted wording. The purpose is front-loaded, and the caveat follows immediately where it is relevant.

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 has no annotations, no output schema, and five parameters with 0% schema description coverage. The description covers the core operation and one output caveat but leaves output location, format behavior, and overwrite semantics undocumented.

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 should compensate for the five parameters. It only vaguely references the input audio and requested duration, leaving input_path, filename, format, and overwrite unexplained beyond their property names.

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 and resource: "Repeat an audio file to a requested duration." That clearly distinguishes it from sibling tools such as trim_audio, merge_audio, and split_audio, which manipulate audio in different ways.

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 basic use case of extending an audio file to a target duration, but it gives no explicit when-to-use guidance, no exclusions, and no comparison to sibling tools. The seamless-boundary caveat is a quality note, not usage guidance.

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 supplied, so the description carries the full disclosure burden. It does add one genuinely useful behavioral fact beyond the schema — the call consumes no credits but is rate limited — which is exactly the kind of operational context an agent needs before calling. However, it says nothing about whether the plan is persisted, what permissions are required, or what the response shape looks like, which matters for a creation-named tool with no 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?

It is short — two sentences — with no padding in length, and the cost/rate-limit fact is stated up front enough to be found. But the words that are there are largely spent on empty framing ("Ask the documented... endpoint", "Official docs state") rather than on information the agent can act on.

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 creation tool with no annotations, no output schema, and three undocumented parameters, an agent needs to know what the returned plan is for and how to consume it. The description omits that entirely, leaving the definition insufficient relative to the tool's complexity, though the credit/rate-limit note does cover one real gap.

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% across three parameters (prompt, model_id, music_length_ms), and the description adds no parameter meaning whatsoever. The bounds on music_length_ms, the enum of model versions, and the 4100-character prompt limit are left entirely to bare schema constraints with no guidance on how they interact with the planning behavior.

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?

"Ask the documented music planning endpoint to produce a structured plan" essentially restates the tool name (create_composition_plan) in other words. It never says what a "plan" actually is, what it contains, or how it differs from siblings like generate_music or generate_music_detailed, so the agent cannot distinguish it from the many music-generation tools by purpose alone.

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?

There is no when-to-use guidance, no mention of prerequisites, and no reference to any alternative tool. The only conditional information is an implicit hint that it is free to call, which is not the same as telling an agent when this tool is the right choice over generate_music.

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 supplied, the description carries the full burden, and it does add real value by disclosing that charges may occur before output and that paid authorization gates must be satisfied. It omits other important behavior: whether creation is asynchronous, what permissions are needed, and what happens if the cost is unknown or gates are not passed.

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 tight sentences with the operation stated first and the cost/authorization caveat second; no filler. It is efficient, though it spends its limited space on caveats rather than the undocumented parameters.

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 charge-incurring creation tool with 7 undocumented parameters and no output schema or annotations, the description is thin. It never clarifies the async lifecycle, the enum choice for model_id, or language parameter requirements, so an agent would still be guessing on most invocation details.

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% across 7 parameters, and the description explains none of them individually. The mention of 'paid authorization gates' loosely gestures at allow_paid and allow_unknown_cost, but model_id, source_language, target_language, reference, and input_path receive no added meaning, leaving the schema to speak for itself.

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?

States a specific verb and resource (create a dubbing project) and names the input source (local audio/video file), which cleanly separates it from siblings like add_dubbing_language, get_dubbing_status, and delete_dubbing_project. It stops short of explicitly contrasting with those siblings, so it lands at 4 rather than 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 signals a precondition for use ('requires both paid authorization gates') and warns of charging, which implicitly tells the agent this is a paid-path operation. However, it never says when to pick this over alternatives, nor how the project lifecycle continues (e.g., status polling via get_dubbing_status).

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 it does disclose real behavioral constraints: local enablement and dual paid-operation gates imply this can fail for non-technical reasons and may incur cost. It omits whether training is long-running/asynchronous, what happens to samples, and what a successful call returns.

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 short sentences with the action front-loaded and the prerequisites second — efficient and easy to scan. The only waste is the vague 'optional' qualifier, which earns no place without explanation.

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 9-parameter, annotation-free mutation tool with no output schema, the description is thin: five parameters are undocumented and nothing explains the model_id enum choice, visibility semantics, or the return value (presumably a finetune id to poll or fetch). The gating information is genuinely valuable but does not cover the whole surface an agent needs.

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 for all 9 parameters. It maps loosely to sample_paths ('audio samples'), rights_confirmed ('rights confirmation'), and allow_paid/allow_unknown_cost ('both paid-operation gates'), but name, primary_genre, tags, model_id, and visibility get no mention at all.

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?

States a specific verb and resource ('Create ... music finetune from audio samples'), which cleanly separates it from the sibling read/update/delete finetune tools. The word 'optional' is unexplained and adds ambiguity rather than precision.

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 lists prerequisites for invocation (local enablement, rights confirmation, paid-operation gates), which is useful gating context. However, it never says when to choose a finetune over the sibling generate_music family, nor what conditions make this the wrong 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 supplied, the description carries the burden and does disclose meaningful behavior: this is a mutating save, it needs an explicit confirm flag, and it is gated by two cost-related switches. It does not say whether the preview is consumed or remains available, whether repeated saves duplicate a voice, or what happens on gate failure.

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 short sentences, front-loaded with the action and immediately followed by the gating conditions. No filler, no 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 six-parameter mutation with no annotations and no output schema, the definition covers the highest-risk aspect (paid-operation confirmation) but leaves parameter meaning and return behavior unexplained. An agent could get the gating right yet still fail the minLength rules on voice_description.

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% across six parameters, so the description must compensate and largely does not: it names confirm_save and implies the two gates but never explains generated_voice_id, voice_name, or the 20-1000 character constraint on voice_description. It is unclear from the description which two switches constitute 'both paid-operation gates'.

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 and resource: 'Save one previously generated preview as a reusable voice,' which clearly separates it from siblings that create voices from other sources (design_voice, clone_voice, remix_voice) by pinning the input to an existing preview. It does not name those siblings explicitly, so differentiation is implied through the source object rather than stated.

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?

Prerequisites are given ('previously generated preview', confirm_save=true, both paid-operation gates), which tells an agent the conditions under which the call will succeed. There is no explicit when-not guidance or pointer to an alternative path (e.g., cloning from audio instead of a preview), so the routing information is only partial.

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 at all, the description carries the full behavioral burden, and it does disclose the two most consequential traits: the deletion is permanent and a confirmation flag is mandatory. However, it says nothing about permission requirements, whether in-use assets are blocked or cascaded, or what the response returns on success/failure — substantial gaps for an irreversible mutation.

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 short sentences with the destructive nature front-loaded and the required flag immediately after. Nothing is redundant and no sentence could be removed without losing required 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 two-parameter irreversible deletion with no annotations and no output schema, the definition covers the essentials (permanence + confirmation) but not the surrounding context an agent needs to act safely: scope of what is destroyed, error behavior on missing assets, and whether recoverability exists. It is minimum viable rather than 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?

Schema description coverage is 0%, so the description must compensate, and it does explain the non-obvious parameter: confirm_delete must be set to true, which the schema alone only shows as a boolean defaulting to false. The asset_id parameter is left entirely undocumented, so half the parameter surface still lacks meaning.

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 gives a specific verb and resource ('Permanently delete an asset') and names the owning system ('ElevenLabs workspace'), so the agent can distinguish it from the many generate_* siblings. It does not explicitly contrast with the other destructive siblings (delete_voice, delete_history_item, delete_music_finetune), but the resource noun 'asset' is precise enough to disambiguate.

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 prerequisite 'Requires explicit confirm_delete=true' tells the agent what to supply, and 'Permanently' signals this is irreversible rather than a soft delete. There is no guidance on when to choose this over related tools such as delete_history_item, nor any note on preconditions like whether the asset must be unreferenced first.

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 behavioral burden, and it does disclose the most important trait: the operation is permanent and gated by an explicit confirm flag. It does not disclose side effects on associated languages/dubbed media, permission requirements, or whether recovery is possible after the fact.

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 short sentences with zero filler, and the destructive nature is front-loaded via 'Permanently'. Every clause adds 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 destructive mutation with no annotations, no output schema, and 0% schema coverage, the definition covers the essentials (permanence + confirmation requirement) but omits cascade effects and failure modes an agent should know before invoking it.

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 partly does by explaining confirm_delete's role as an explicit confirmation gate, adding safety semantics beyond the bare boolean/default. project_id is self-explanatory by name, but neither parameter gets format or validation detail.

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?

States a specific verb ('Permanently delete') and a specific resource ('a dubbing project'), which naturally distinguishes it from the other delete_* siblings (delete_voice, delete_asset, delete_music_finetune, delete_history_item). It's clear but doesn't explicitly note any sibling relationship.

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 one concrete precondition ('Requires explicit confirm_delete=true'), which is a usable usage cue. However, it gives no when-to-use versus alternatives guidance (e.g., when to delete vs. just stop using a project), and no note on whether the deletion is recoverable or what dependent resources are affected.

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 supplied, so the description carries the full burden. It does disclose the two behavioral facts that matter most for a delete tool: the effect is permanent and a confirm flag is mandatory. It stops short of covering permissions, cascade effects, or error 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 short sentences, zero filler, with the destructive nature and the confirmation gate front-loaded ahead of any detail.

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 destructive tool with no annotations and no output schema, the description covers purpose, irreversibility, and the safety gate. The gap is the undocumented identifier parameter, which leaves an agent unsure how to source a valid history_item_id.

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 real meaning for confirm_delete by stating the required value, but history_item_id is left entirely unexplained — no hint about its origin (e.g., from listing or getting a history item) or its format beyond maxLength 150.

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?

Uses a specific verb plus resource: "Permanently delete one ElevenLabs history item." That is enough to separate it from read-only siblings such as get_generation_history_item and download_history_audio, though it never names those alternatives explicitly.

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 a hard precondition (confirm_delete=true), which implicitly signals this is a guarded, intentional operation. It does not say when to prefer deletion over simply ignoring an item, nor does it route the agent to list_generation_history to obtain the target id.

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 supplied, the description carries the full burden and does meaningful work: it discloses irreversibility ("Permanently"), that an explicit confirmation is required, and that a local module must be enabled for the call to work. It stops short of describing failure behavior or what happens to dependent artifacts.

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 short sentences, no filler, with the permanence warning and the prerequisites front-loaded in the order an agent needs them.

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 destructive tool with no annotations or output schema, this covers the essentials: irreversibility, the confirmation gate, and the enablement prerequisite. It could add the negative path (default confirm_delete=false behavior) and permission requirements to be fully 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?

Schema description coverage is 0%, so the description must compensate. It explains the meaning behind the confirm_delete flag ("explicit confirmation") but leaves finetune_id undocumented, and does not say what happens if confirm_delete is left at its default of false.

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?

States a specific verb and effect ("Permanently delete") on a specific resource ("one music finetune"), which cleanly separates it from the sibling list_music_finetunes, get_music_finetune, update_music_finetune, and create_music_finetune 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 word "Permanently" signals this is the destructive path, and it names a prerequisite ("local module enablement"), but it never says when to choose this over update_music_finetune or what to do instead when the module is disabled. The usage context is implied rather than stated.

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 whole burden. It does disclose the two most important behavioral traits — irreversibility and a mandatory confirmation flag — but says nothing about permissions required, what happens to compositions or generations that reference the voice, or the return result of the deletion.

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 tight sentences with the destructive nature front-loaded and the safety requirement second. Nothing is redundant, though a short clause on prerequisites could be added without bloat.

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 destructive tool with no output schema and no annotations, the essentials — resource, permanence, and the confirmation gate — are all present. Optional gaps are the deletion side effects and response confirmation, which are minor at 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 description coverage is 0%, so the description must compensate. It explains confirm_delete as an explicit opt-in guard (going beyond the schema's bare boolean default of false), but voice_id is left entirely undocumented beyond its obvious name.

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?

States a specific verb and resource ('Permanently delete a voice') with the scope 'from the account'. It is unambiguous against siblings like delete_asset or delete_history_item because the resource is named, though it does not explicitly route to alternatives such as update_voice_settings.

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 word 'Permanently' plus the confirm_delete requirement implies this is an irreversible operation to be used only for genuine removal, and it implicitly contrasts with update_voice_settings. However, there is no explicit when-to-use/when-not-to-use guidance or mention of prerequisites such as ownership or reference checks.

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 supplied, the description carries the full burden and does disclose non-obvious behavior: multiple sample audios are produced, they are written to local files and omitted from the tool response, and the call may consume credits. That is meaningful disclosure an agent could not get from structured fields. It stops short of naming where files land, how they are named, or what happens when credits are declined.

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, front-loaded with the action, followed by the response-shape caveat and the cost warning. Nothing is padded and the ordering matches what an agent needs before calling.

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 10-parameter mutation-adjacent tool with no annotations, no output schema, and zero schema coverage, the description leaves too much unknown: file naming and location, what an empty response actually looks like, and how the cost-consent flags gate the call. The return-omission note is valuable but the parameter surface is essentially undocumented.

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% across 10 parameters, so the description must compensate and it largely does not. It adds nothing about allow_paid, allow_unknown_cost, auto_generate_text, filename_prefix, guidance_scale, seed, loudness, or model_id. The single phrase 'may consume credits' faintly gestures at the two paid-consent flags but gives no guidance on how they interact.

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 names a specific verb and resource: 'Generate voice previews from a description.' That is concrete and unmistakable. It does not, however, differentiate itself from the nearby siblings create_voice_from_preview and get_voice_preview, which an agent could easily confuse with it in a list of 80+ 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?

There is no statement of when to use this instead of create_voice_from_preview or clone_voice, no prerequisites, and no exclusions. The only implied workflow is generating samples that later feed a voice creation, and that has to be inferred rather than read.

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 usefully discloses that the local output is saved only after a successful API response and an audio-signature check. It leaves other local-file behavior unspecified, including overwrite handling, cleanup after validation failure, and the downloaded file format.

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 short sentences front-load the operation and then state the important save-and-validation behavior. There is no redundant or unnecessary wording.

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 basic operation and an important failure-safety behavior for a simple three-parameter download tool. However, the undocumented parameters, absent completion-workflow pointer, and unclear destination-file semantics leave avoidable invocation 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%, and the description only indirectly connects language_id to the selected output and filename to the local destination. It does not explain where project_id and language_id are obtained or whether filename is a basename, relative path, or absolute path.

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 gives a specific verb, resource, cardinality, and destination: downloading one completed dubbing language output to a local file. The resource is distinguishable from the other download siblings, but the description does not explicitly contrast those alternatives.

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 word "completed" establishes a clear prerequisite for using the tool. It does not explain how to verify completion, such as by calling get_dubbing_status, or when another download tool would be 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, the description usefully discloses the single-item scope and local-storage side effect. It omits other relevant behavior, such as whether an existing file is overwritten, whether directories are created, and what success or failure returns.

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 single sentence is front-loaded and contains no unnecessary wording. However, its brevity leaves important parameter and behavioral details unstated.

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 core operation is understandable, but the definition is incomplete given the undocumented parameters, absent annotations, and lack of an output schema. ID discovery, filename handling, and local-file behavior are important omissions for reliable 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%, and the description only indirectly clarifies that history_item_id selects the history item. It does not explain where to obtain that ID or whether filename is a basename or path, including any extension or directory requirements.

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, resource, and scope: downloading audio for one history item to local storage. It does not explicitly differentiate this tool from siblings such as download_dubbed_media or the generation-history 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?

Beyond implying that the caller wants one history item's audio, there is no guidance on when to use the tool or which alternatives to choose. It does not explain that history_item_id can be discovered through list_generation_history or get_generation_history_item.

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 supplied, the description carries the full burden. It usefully discloses URL host validation, file signature validation, and local saving, but it does not cover overwrite behavior, error handling, permissions, or what is returned after saving.

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 definition is a single front-loaded sentence with no filler. Each clause adds operative detail about source, validation, and save behavior.

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 is adequate for a simple two-parameter download tool in purpose and safety behavior, but it leaves both parameters undocumented and omits basic local-save edge cases. For a tool with no annotations, no output schema, and 0% schema coverage, more context would be expected.

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 does not explain either parameter. It implies that a generation output is saved locally, but it never clarifies what generation_id identifies or how filename is used, so it does not compensate for the schema gap.

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 and resource: download completed image output. It also scopes the operation to the official signed generation URL and local saving, which distinguishes it from generation/metadata siblings like generate_image and get_image_generation.

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 clear context: the output must be completed and come from the official signed generation URL. It does not explicitly name alternatives or state when not to use it, but the intended usage is clear for a download 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 supplied, the description usefully discloses that the tool retrieves a remote signed URL, validates both the URL host and file signature, and writes the result locally. These are meaningful behavioral and security details, although overwrite behavior, filesystem handling, and possible failure conditions remain unspecified.

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 single sentence is front-loaded with the primary action and then presents validation and saving in a logical sequence. Every clause contributes useful operational information without redundancy or unnecessary wording.

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 download tool, the description covers the core workflow and important validation behavior. However, the absence of annotations, parameter documentation, and an output schema leaves gaps around prerequisites, filename and overwrite semantics, and what the caller receives after a successful save.

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 explicitly explains either generation_id or filename. It indirectly suggests that generation_id selects a completed video generation and filename controls the local save, but leaves destination-path rules, extension handling, and ID provenance 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 clearly states the action and resource: downloading a completed video output and saving it locally. The signed-URL and validation details further clarify its scope, though it does not explicitly differentiate itself from siblings such as download_image or get_video_generation.

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 phrase 'completed video output' establishes that the tool is intended for the post-generation stage, providing useful context for when to invoke it. It does not explain how to confirm completion or obtain a suitable generation, nor does it identify alternatives for incomplete generations or other media types.

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 supplied, the description carries the full behavioral burden. It usefully discloses that the local implementation does not invent prices and only returns an official estimate when one is available, but it omits whether the call is read-only, what happens when no estimate exists, and whether authentication or rate limits apply.

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 obvious filler, and the conditional estimate behavior is front-loaded. It is compact, though its brevity leaves important details unstated rather than explained efficiently.

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, 0% schema description coverage, no annotations and no output schema, the description is not complete enough. It does not explain the operation enum, how text/model_id/duration_seconds affect the estimate, or what the return value looks like when an estimate is unavailable.

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 for four undocumented parameters. It hints at per-character, per-second and per-generation pricing, but it does not map those concepts to text, duration_seconds, model_id or the required operation enum values.

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 says to return an official estimate only when available and mentions per-character, per-second or per-generation prices, implying a cost estimate. However, it never explicitly states that it estimates cost for the requested operation, and it does not distinguish itself from siblings such as get_budget_status or get_usage_report.

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?

There is no explicit guidance on when to use this tool versus alternatives, nor when not to use it. The conditional availability statement is a behavioral constraint, not usage guidance, so an agent must infer that this should be called before generation operations.

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 discloses that this is a write into an authorized location and that only one asset is handled per call. It omits overwrite behavior, whether existing files are replaced or errors are returned, and whether directories are created. That leaves meaningful mutation semantics unstated.

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 short sentences, front-loaded with the action and its scope. Nothing is padding, though the ALLOWED_ROOTS reference is unexplained jargon.

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 mutating export tool with no annotations, no output schema, and zero parameter documentation. The description should at minimum cover overwrite semantics, what profile values mean, and how relative_path is resolved; none of that is present.

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% across five parameters, so the description must compensate. It adds real meaning only for project_root (must be within ALLOWED_ROOTS); input_path, relative_path, overwrite, and the profile enum values are left entirely undefined.

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 and resource: exporting a single local audio asset into a Godot project root. It is clearly distinguishable from all sibling generation/processing tools. It stops short of naming a sibling or contrasting scope, which keeps it at 4 rather than 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?

It gives one prerequisite (the project root must fall within ALLOWED_ROOTS) but no guidance on when to choose this over other asset workflows, or when not to. Usage is implied by the naming rather than explained.

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 at all, the description carries the full behavioral burden. It usefully discloses the rejection rules (traversal, symlinks, non-audio entries, oversized expansions), which is real security context. But it omits critical behavior: whether rejected entries cause a hard failure or are silently skipped, what 'supported audio' formats are, and where files are written relative to filename_prefix.

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 tight sentences, front-loaded with the action and immediately followed by the safety guarantees. Zero filler and nothing repeated from the 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 two-parameter extraction tool with no annotations and no output schema, the description gives good security posture but leaves the outcome undefined — no statement of what is returned (paths? counts?), where files land, or what happens on partial rejection. An agent can attempt the call but cannot predict its result.

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% for both required parameters, so the description must compensate and it does not. Neither zip_path nor filename_prefix is explained — notably filename_prefix implies output naming and possibly per-file prefixing, but the description says nothing about how it is applied or what collisions do.

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?

States a specific verb and resource: extract audio tracks from a generated ZIP. An agent can tell this is a ZIP-unpacking tool rather than a stem-separation tool, though the description never acknowledges the similarly named sibling separate_music_stems, which is the main confusion risk here.

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 phrase 'from a generated ZIP' implies the input must come from an upstream generation step, giving implied context for when to call it. However, it never states preconditions explicitly, never names an alternative, and gives no guidance on what to do if the ZIP is invalid or partially extractable.

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 supplied, so the description carries the full behavioral burden. It mentions a loop-quality caveat but says nothing about cost implications (allow_paid, allow_unknown_cost are parameters), duration limits, model selection effects, output file handling, or whether generation is synchronous. For a 9-parameter generation tool with billing-related flags, this is a substantial gap.

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 short sentences with no filler, which is efficient. However, the second sentence is a hedge about loop seamlessness that arguably belongs in a caveat section, and the space saved is spent on nothing informative.

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 9-parameter generation tool with no annotations and no output schema, the description is far too thin. An agent cannot infer cost behavior, output location, duration constraints, or how this differs from the many other audio-generation siblings.

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% across 9 parameters, so the description must compensate and does not. It only alludes to the 'loop flag' without explaining loop semantics, and never addresses text, filename, model_id, duration_seconds, prompt_influence, output_format, or the two paid-cost consent flags.

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 and resource ('Generate an ambient sound loop'), which clearly identifies a text-to-audio generation tool. It does not differentiate itself from siblings like generate_sound_effect, create_audio_loop, or generate_music, so it falls 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?

There is no guidance on when to choose this tool over generate_sound_effect, create_audio_loop, or generate_music, which are close siblings. The only contextual hint is the mention of a loop flag, which is vague rather than a routing rule.

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 behavioral burden. It usefully discloses input-order processing, unique-voice and length-limit enforcement, and paid authorization, but it does not explain what those limits are, what happens when they are violated, or how cost-related flags behave.

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 short, front-loaded, and free of filler. However, the phrase 'documented unique voice and length limits' points to documentation that is not present, reducing its practical value.

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 complex nine-parameter generation tool with no annotations, no output schema, and no schema descriptions. The description is too thin to fully prepare an agent to invoke it correctly, especially regarding optional parameters, cost behavior, and output expectations.

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% across nine parameters, so the description must compensate. It only vaguely references inputs, voice uniqueness, length limits, and paid authorization, leaving filename, model_id, language_code, output_format, previous_text, future_text, and allow_unknown_cost unexplained.

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 and resource: generate a multi-voice dialogue, with input order called out. It is clear enough to distinguish from single-voice speech tools, but it does not explicitly differentiate from sibling dialogue variants such as generate_dialogue_stream or generate_dialogue_with_timestamps.

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 no guidance on when to use this tool versus the many sibling dialogue and speech tools. It mentions paid authorization, but that is a prerequisite rather than a usage-selection rule.

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 supplied, so the description carries the full burden. It hints at saving a completed response locally, but does not disclose cost/paid-generation behavior implied by allow_paid and allow_unknown_cost, whether the call blocks until the stream completes, auth needs, rate limits, or what is overwritten at filename.

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?

It is a single tight sentence with no wasted words, but its brevity reflects under-specification rather than disciplined conciseness, and it is front-loaded with a vague pointer to external documentation.

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 9-parameter, cost-gated, streaming multi-voice generation tool with no annotations and no output schema, the description is far too thin. It leaves an agent unable to call it correctly without external docs, which is precisely the resource it offloads to but does not summarize.

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% across 9 parameters, so the description must compensate and largely does not. It only weakly implies filename means local save and that dialogue is multi-voice, leaving model_id, allow_paid, allow_unknown_cost, future_text, previous_text, language_code, and output_format entirely unexplained.

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 verb (call), the resource (multi-voice dialogue), and the streaming variant plus local save. However, 'the documented streaming endpoint' is an indirect pointer, and it never distinguishes itself from the very similar siblings generate_dialogue and generate_dialogue_stream_with_timestamps, so an agent can't fully disambiguate from the sentence alone.

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?

There is no when-to-use, when-not-to-use, or alternative guidance. Given four closely related dialogue/speech siblings (generate_dialogue, generate_dialogue_with_timestamps, generate_dialogue_stream_with_timestamps), the absence of routing guidance is a real gap.

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 supplied, so the description carries the full burden. It does disclose one side effect (audio plus timing metadata are saved to disk), but omits billing/cost behavior implied by allow_paid and allow_unknown_cost, streaming semantics, and where the file lands.

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 front-loaded sentence with no wasted words, but the compactness comes at the cost of substance — the phrase 'documented alignment response' communicates nothing to an agent.

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 9-parameter generation tool with no annotations, no output schema, and zero schema descriptions, this one-liner is far too thin. An agent would not know how to shape inputs, what costs may be incurred, or how timing metadata is returned.

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% across 9 parameters, so the description must compensate and does not. Only 'save audio plus timing metadata' loosely gestures at filename and timing output; inputs, voice_id, model_id, output_format, previous_text/future_text, and the two cost flags are entirely unexplained.

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 names the operation (call the streaming dialogue endpoint) and states two outcomes (saved audio and timing metadata), which is more than a tautology. However, 'documented alignment response' is self-referential filler, and it never distinguishes this tool from the four sibling variants (generate_dialogue, generate_dialogue_stream, generate_dialogue_with_timestamps).

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?

There is no statement of when to choose the streaming variant over the non-streaming or non-timestamp siblings, and no mention of prerequisites. An agent must infer selection purely from the name suffix.

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 supplied, so the description carries the full burden. It hints at a cost gate ("Paid authorization is required"), which is genuinely useful, but it says nothing about what happens if the paid flag is not set, whether generation is blocking or asynchronous, what the timing data looks like, or what file is produced.

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 short sentences with the core capability front-loaded and no filler. The brevity is efficient, though it borders on under-specification given the tool's complexity.

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?

A 9-parameter generation tool with no annotations, no output schema, and no parameter descriptions is described in two sentences. An agent cannot tell from this text what it must supply, what the timing output looks like, or how cost authorization interacts with the call.

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% across 9 parameters, and the description explains none of them. The paid-authorization sentence only weakly gestures at allow_paid/allow_unknown_cost, leaving inputs, filename, model_id, output_format, language_code, and the previous/future_text context fields entirely undocumented in both schema and 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?

States a specific verb and resource ("Generate multi-voice dialogue") plus a differentiator ("segment timing data") that separates it from plain generate_dialogue and from the single-voice generate_speech_with_timestamps. It does not, however, name any sibling explicitly or distinguish itself from the stream variants.

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?

There is no when-to-use guidance, no exclusions, and no named alternatives among the many dialogue/speech siblings. The only guidance is the prerequisite "Paid authorization is required," which signals a cost gate but not 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.

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

With no annotations, the description carries the full burden. It does disclose useful behavior: the operation queues (async), validation happens locally via the OpenAPI discriminator before any remote call, and the tool is disabled by default. It omits cost/paid-gating semantics implied by allow_paid and allow_unknown_cost, and never says what a successful call returns.

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, front-loaded with the action, with no filler. The middle sentence leans slightly into implementation detail ('checked-in OpenAPI discriminator schema') but still conveys actionable validation behavior.

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 an async queueing tool with a nested free-form parameter object, no annotations, and no output schema. The description never states what is returned (presumably a job id) nor that siblings such as get_image_generation or download_image must be used to retrieve the result, which is the most important missing context for an agent.

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 valuably explains that parameters is a free-form bag whose accepted keys are determined by model_id via the discriminator schema — something the bare schema (additionalProperties: {}) does not convey. It leaves allow_paid and allow_unknown_cost, arguably the most safety-relevant flags, entirely unexplained.

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 gives a specific verb and resource ('Queue an ElevenCreative image generation'), which is clearly distinct from siblings like generate_video, generate_music, or list_image_generations. It does not explicitly name an alternative or scope boundary, so a 4 rather than 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 'Disabled by default' note gives a genuine prerequisite an agent must handle before calling, which is more than nothing. However, there is no guidance on when to pick this over generate_video or how to choose a model_id, and no explicit statement of when-not-to-use.

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 supplied, the description carries the full burden, and it does add real behavioral context: inputs are validated against current documented constraints and the call sits behind two paid-operation gates. It still omits what those gates are, what happens when they are not satisfied (error vs. silent downgrade), and whether generation is synchronous or long-running.

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, no filler, with the dual input mode front-loaded. The phrasing 'documented constraints' and 'paid-operation gates' is vague jargon that would benefit from one concrete clarifying clause, but nothing is 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 nine-parameter, nested-object, no-annotation, no-output-schema generation tool, the description is thin: it explains neither cost/budget behavior, nor the required filename, nor model selection, nor the result shape. An agent could not reliably construct a valid paid request from this text plus the bare 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% across nine parameters including a nested composition_plan object, so the description must compensate. It only gestures at two of them ('prompt' and 'chunk-based plan') and leaves model_id, seed, music_length_ms, filename, force_instrumental, allow_paid, and allow_unknown_cost entirely unexplained—especially costly since the paid gates map directly to those two booleans.

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?

States a specific verb and resource ('Compose music') and distinguishes two input modes: a prompt or a chunk-based composition plan. It does not differentiate itself from close siblings such as generate_music_stream, generate_music_detailed, or generate_music_from_video, so it falls 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 implies usage through 'either a prompt or a chunk-based plan', letting an agent infer the two calling modes, and hints that paid-operation gates must be satisfied. It never says when to choose this tool over the streaming/detailed variants or generate_music_from_video, and gives no prerequisites for the gates.

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 supplied, so the description carries the full disclosure burden, and it discloses only the response shape. For a generative tool with parameters like allow_paid, allow_unknown_cost, and store_for_inpainting, it says nothing about cost implications, whether generation is blocking or long-running, rate limits, or failure behavior. The multipart return note is the one genuinely useful behavioral fact.

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?

It is a single well-formed sentence with no filler, and the return-format information is front-loaded. But the brevity here reflects under-specification rather than discipline; the space saved is space that should have been spent on the 21 undocumented parameters.

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 21 parameters, a nested object, no annotations, and no output schema, the description should be doing substantial work and instead covers one sentence. Nothing tells the agent what filename is for, how generation_mode changes the call, or what happens with composition_plan. It is wholly inadequate 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 description coverage is 0% across 21 parameters including a nested composition_plan object and three enum fields, so the description needed to compensate and adds nothing. It never mentions prompt, lyrics_text, generation_mode, model_id, or the paid/unknown-cost flags, all of which require interpretation. An agent must guess at nearly every input.

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 names a specific verb and resource ('Generate music') and identifies the return shape (audio plus structured JSON metadata in a multipart response), which is more than a tautology. However, 'detailed endpoint' is a label, not an explanation, and it never clarifies what makes this 'detailed' compared with the sibling generate_music or generate_music_detailed_stream. An agent cannot distinguish the three variants from this text.

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?

There is no when-to-use or when-not-to-use guidance, and no sibling is named. With generate_music, generate_music_stream, and generate_music_detailed_stream all present, the description should route between them but instead leaves the choice entirely to inference. Only the mention of multipart metadata hints at a usage 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 full behavioral burden. It does disclose that output is written to a local file with audio plus metadata, which is useful, but it says nothing about cost implications despite parameters named allow_paid and allow_unknown_cost, nothing about streaming semantics, rate limits, or what happens on failure.

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 front-loaded sentence with no padding, so nothing is wasted, but the brevity is under-specification rather than tight editing given the tool's breadth.

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 21-parameter generation tool with a nested object, no output schema, and no annotations, one sentence covering purpose and local persistence is nowhere near sufficient. An agent cannot confidently choose among the music siblings or supply parameters such as generation_mode, allow_paid, or store_for_inpainting.

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% across 21 parameters, including a nested composition_plan object and several enums (generation_mode, model_style_prefix, model_id). The description mentions no parameter, its format, or its effect, so it compensates for none of the coverage gap.

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 largely restates the name: 'detailed streaming music endpoint' adds almost nothing beyond 'generate_music_detailed_stream'. The one genuinely informative clause is 'save its multipart audio and metadata result locally', which reveals a local-write side effect, but it never states that this generates music from a prompt or how it differs from generate_music, generate_music_stream, or generate_music_detailed.

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?

There is no when-to-use guidance at all. With four near-identical music-generation siblings (generate_music, generate_music_stream, generate_music_detailed), a routing sentence is exactly what an agent needs here, and none is supplied.

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 supplied, so the description carries the full burden and does disclose one useful behavioral fact: paid authorization is required. However, for a paid generation endpoint it omits whether output is an audio file or asset, whether the call is synchronous or asynchronous, cost implications, model behavior differences, and what side effects (e.g., C2PA signing, separate tracks) actually do.

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 the operation and followed by the authorization prerequisite. There is no filler or repetition, though the brevity is also the source of the documentation gaps rather than a model of efficient completeness.

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 complex: 11 parameters, one enum, paid model selection, no output schema, and no annotations. The description addresses only the core action and one prerequisite, leaving the agent without enough information to choose models, understand cost controls, or correctly interpret most parameters.

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% across 11 parameters, so the description must compensate. It adds meaning for video_paths ('one or more local videos') and hints at allow_paid via 'paid authorization,' but leaves filename, tags, model_id enum, add_sfx, description, sign_with_c2pa, separate_tracks, allow_unknown_cost, and use_audio_as_reference completely unexplained.

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 and resource: 'Generate music from one or more local videos,' which is clearly distinct from the audio-only siblings like generate_music. It also names the underlying 'video-to-music endpoint,' so an agent can tell what the tool does without opening the schema. It does not explicitly name an alternative sibling, but the video-input scope is distinctive.

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 only guidance is a prerequisite ('Paid authorization is required') and the implicit condition that you must have local video files. There is no explicit when-to-use vs when-not, and no routing advice relative to generate_music or generate_music_detailed. An agent must infer the selection criteria from the name alone.

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 entire behavioral burden. It does disclose two useful traits — this is a paid operation with two gates, and it writes a file locally — but it never names the gates, explains cost risk, describes streaming progress behavior, or states whether an existing file at `filename` is overwritten.

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 single sentence is tight and front-loads the action, so there is no padding. However, brevity here is achieved by deferring to a "documented endpoint" rather than by saying anything substantive, so the compactness buys little.

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 nine-parameter, nested-object, paid, file-writing tool with no output schema and no annotations, so the description needed to do real work. Instead it covers only the paid-gate mention and the local save, leaving the composition_plan structure, model choice, length limits, and the two boolean gates entirely unexplained.

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% across nine parameters, including a nested composition_plan with per-chunk style and adherence fields, yet the description mentions no parameter at all. The agent gets no meaning for seed, prompt, model_id, music_length_ms, force_instrumental, or the paid-gate flags beyond their schema keys.

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?

"Call the documented streaming music endpoint, then save the completed result locally" conveys the streaming-plus-local-save shape, which loosely separates it from generate_music and generate_music_detailed. But "documented streaming music endpoint" is a circular reference rather than a statement of what the tool produces, and nothing distinguishes it from generate_music_detailed_stream among the 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?

No when-to-use guidance is offered: the description never says to prefer this over generate_music or generate_music_detailed_stream, nor what the tradeoff (streaming vs. one-shot, file output vs. returned asset) is. The only hint is "paid-operation gates," which gestures at cost without explaining when the agent should enable those gates or avoid them.

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 must carry the behavioral burden. It usefully discloses the 30-second maximum and the cost/authorization requirement, but it does not explain the paid-authorization flow, unknown-cost handling, or what happens on failure.

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, front-loaded with purpose, followed by the key duration and cost constraints. 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 nine-parameter paid generation tool with no annotations and no output schema, the description is too thin. It covers duration and cost authorization but omits parameter guidance and sibling differentiation, which are necessary 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?

Schema description coverage is 0%, so the description must compensate for nine undocumented parameters. It does not explain text, filename, loop, model_id, allow_paid, allow_unknown_cost, output_format, or prompt_influence, leaving parameter semantics entirely to the bare 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 gives a specific verb and resource: "Generate one sound effect from a text prompt." It is clear what the tool produces, but it does not explicitly distinguish this from sibling generation tools such as generate_ambient_audio or generate_music.

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 provides an important prerequisite — explicit authorization is required because cost is not estimated — but it does not state when to use this tool versus alternatives like generate_ambient_audio or get_sound_effect_presets. Usage is implied rather than clearly guided.

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 usefully warns that the call consumes credits and can be blocked by dry_run or missing paid authorization, but it does not explain the interplay between allow_paid and allow_unknown_cost, whether credits are charged on failure, or what happens to an existing file with the same name. Given nine parameters and a nested voice_settings object, the behavioral picture is thin.

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 short sentences with the core action front-loaded, so it is compact. However, the second sentence is grammatically garbled ('blocked by dry_run or either missing paid authorization gate'), which forces the reader to parse ambiguous logic in the one sentence carrying the behavioral 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?

For a nine-parameter mutation tool with a nested settings object, no annotations, and no output schema, the description covers only the credit/gating behavior. It omits where the file is written, whether the same filename overwrites, default output format implications, and any return value information, so an agent cannot confidently construct a valid call from it.

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% across nine parameters, so the description must compensate. It gestures at the paid-gating concept implied by allow_paid and allow_unknown_cost but never explains voice_id, filename (destination path?), output_format, model_id, language_code, or voice_settings, leaving several parameters with no documented meaning anywhere.

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 definition gives a concrete verb and resource: 'Generate and save speech audio,' which implicitly distinguishes it from the streaming and timestamped siblings by emphasizing that output is saved. It does not explicitly name those siblings (generate_speech_stream, generate_speech_with_timestamps), so the differentiation is inferential rather than stated.

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 discloses prerequisites (dry_run must be disabled and paid authorization gates must be satisfied) which tells the agent when the call will fail, but it never says when to pick this over generate_speech_stream, generate_dialogue, or the timestamped variants. Usage context is implied by the saving behavior rather than spelled out.

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 supplied, so the description carries the full burden. It usefully discloses that audio is persisted to a file and that streaming does not exempt the call from paid-operation gates, which is real behavioral context. It stops short of explaining what happens when allow_paid is false (error vs. silent refusal), whether files are overwritten, or any permission 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?

Two short, front-loaded sentences with no filler, and the paid-gate caveat is placed as a qualifying clause where it belongs. The brevity borders on under-specification, but nothing written is wasted.

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 9-parameter tool with a nested object, zero schema descriptions, no annotations, and no output schema, the description leaves nearly all calling decisions undocumented. An agent would have to infer the meaning and consequences of allow_paid, allow_unknown_cost, output_format, and voice_settings entirely from bare property names.

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% across 9 parameters, including a nested voice_settings object and the consequential allow_paid / allow_unknown_cost booleans. The description only obliquely gestures at two of them ('save its resulting audio' for filename, 'paid-operation gates' for the allow_* flags) and says nothing about text limits, output_format, model_id, language_code, or voice settings.

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 names a specific action and resource: call the streaming TTS endpoint and save the resulting audio. That is enough to distinguish it as the streaming speech-synthesis variant, but it never differentiates itself from close siblings like generate_speech or generate_speech_stream_with_timestamps.

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?

There is no explicit guidance on when to choose streaming over non-streaming, or this tool over generate_speech_stream_with_timestamps. The only usage-adjacent signal is the paid-operation caveat, which implies gating but doesn't tell the agent when or how to satisfy 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 provided, the description carries the full behavioral burden and only partially meets it. It states that audio and timing metadata are saved separately and that paid-operation gates exist, but it does not explain streaming behavior, output destinations, permissions, cost implications, or what happens when allow_paid is false.

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 short and front-loads the core operation before adding behavioral context. It avoids unnecessary wording, though its brevity contributes to under-specification rather than clarity.

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 complex tool with 9 parameters, a nested settings object, no annotations, and no output schema. The description is far too thin to make the tool safely invocable, leaving key concerns like paid-operation behavior, file saving semantics, and parameter meaning unexplained.

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?

There are 9 parameters with 0% schema description coverage, including a nested voice_settings object. The description does not explain voice_id, text, filename, model_id, output_format, language_code, voice_settings, allow_paid, or allow_unknown_cost, adding essentially no parameter meaning beyond the bare 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 identifies streaming TTS with alignment/timestamp metadata, which is directionally correct. However, it does not clearly distinguish this tool from close siblings such as generate_speech_stream and generate_speech_with_timestamps, and the phrase 'documented alignment response' is vague.

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 no explicit guidance on when to use this tool versus the non-streaming or non-timestamp variants. The mention of 'paid-operation gates' hints at cost controls but does not explain when those gates matter or how they affect tool selection.

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 full burden. It discloses one useful behavioral fact, that audio and timing metadata are written to separate outputs, but omits permission/cost semantics implied by allow_paid and allow_unknown_cost, what the call returns, and how filenames are used.

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?

It is short and front-loaded with the action, which is good. But the second sentence is thin, and "the documented alignment response" is filler that consumes space without conveying usable 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 9-parameter generative tool with a nested settings object, no output schema, and no annotations, the description is far too sparse. An agent cannot learn what files are produced, whether cost gates apply, or how the timing metadata is returned.

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% across 9 parameters, including a nested voice_settings object, so the description needed to compensate and does not. The only hint is that audio and timing metadata are saved separately, which marginally suggests how filename is used, but text, voice_id, language_code, output_format, and model_id are entirely unexplained.

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 verb and resource are clear ("Generate speech"), and the phrase about an alignment response plus separately saved timing metadata hints that this variant returns timestamps, distinguishing it loosely from generate_speech. However, "the documented alignment response" is vague and points to documentation the agent does not have, so the tool's differentiating purpose is only implied by the name rather than stated outright.

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?

There is no guidance on when to choose this over generate_speech, generate_speech_stream, or generate_speech_stream_with_timestamps, all of which appear as siblings. The description also says nothing about prerequisites, cost implications, or streaming trade-offs.

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 usefully discloses that the operation is queued/asynchronous, that fields are validated by an official OpenAPI discriminator, and that the tool is off unless enabled — real behavioral context. However, it says nothing about cost implications of allow_paid/allow_unknown_cost, what identifiers are returned, or failure modes for unsupported model/parameter combinations.

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 dense sentences, front-loaded with the action and followed by the key constraint. No filler, though "the official OpenAPI discriminator validates fields" is jargon-heavy for the amount of information it delivers.

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 complex tool: a nested free-form parameters object, two paid-execution flags, a model_id that must come from list_models, and an async job whose results need get_video_generation. The description addresses none of the lifecycle or cost-safety questions, leaving an agent unable to invoke it safely on a paid model.

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 does explain the hardest part — that the free-form `parameters` object holds model-specific image/video/audio references validated by a discriminator — but the two cost-safety booleans (allow_paid, allow_unknown_cost) and model_id sourcing remain entirely undocumented in both schema and 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?

"Queue an ElevenCreative video generation" gives a specific verb (queue) and resource (video), which clearly separates it from generate_image, generate_music, and generate_sound_effect in the sibling list. It stops short of naming a related sibling such as get_video_generation, so it doesn't fully close the loop on how the queued job is tracked.

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?

"Pass model-specific text, image, video or audio references" and "Disabled by default" imply when the tool applies and hint at an availability gate, but neither is actionable: the agent is not told how to enable it, when to prefer this over other generation tools, or how allow_paid/allow_unknown_cost affect eligibility. Usage is implied rather than stated.

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 full burden. It does disclose that the call is read-only and requires authentication, which is genuinely useful behavioral context. It stops short of saying what the profile contains, whether the response is cached, or what happens on invalid credentials.

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 short sentences, front-loaded with the purpose. The second sentence ('Makes a read-only API call') is slightly redundant phrasing but does add the safety signal that annotations would otherwise supply, so it 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 zero-parameter, no-output-schema read tool this is close to sufficient, but without annotations or an output schema the description should say what the profile response includes (e.g., account ID, tier, name) so an agent knows what it can retrieve.

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 takes zero parameters, so there is no parameter semantics to explain; per the baseline rule this scores 4. The description correctly implies no inputs are needed since it acts on the authenticated principal.

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 and resource ('Read the authenticated ElevenLabs account profile'), which is clearly distinguishable from generation and asset tools in the sibling list. It does not, however, distinguish itself from the conceptually adjacent get_subscription, get_capabilities, or get_budget_status.

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?

No when-to-use guidance is offered beyond the implicit notion that this returns profile data. Several siblings (get_subscription, get_capabilities, get_budget_status) plausibly return overlapping account-level information, and the description gives no criteria for choosing among them.

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 supplied, the description carries the full burden, and it does add one genuinely useful disclosure: the operation is read-only despite using POST, which pre-empts a real misreading. However, it says nothing about permissions, pagination behavior, default time window, or what the log entries contain.

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 short sentences, front-loaded with the resource and immediately followed by the one non-obvious behavioral fact. Nothing is wasted.

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?

A five-parameter query tool with no annotations and no output schema needs the description to explain time-range semantics, default window, and result shape. The description covers only the POST/read-only quirk, leaving most of what an agent needs to call it correctly unstated.

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% across five parameters, and the description adds no meaning for sort, limit, search, start_time, or end_time. In particular, the epoch-millisecond time bounds and the 100/1000 limit defaults are left entirely to the schema's bare constraints.

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?

States a specific verb and resource: 'Query the workspace API request log.' This is clearly distinct from siblings like get_usage_report or list_generation_history, though the description never explicitly contrasts with those analytics 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?

No guidance on when to use this versus get_usage_report, get_remote_usage_report, or list_generation_history, all of which are adjacent analytics tools. The agent must infer the distinction from the name alone.

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 full behavioral burden. "Read" implies a non-mutating lookup, but the description says nothing about permission requirements, behavior when the asset_id does not exist, or whether the asset must have been uploaded through this service — meaningful gaps for an unannotated tool.

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 short sentence with the resource and scope front-loaded and no wasted words. It is efficient, though the brevity borders on under-specification rather than tightness.

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 and no annotations, the description was the only place to explain what "metadata" includes (fields, units, IDs) and what happens on failure. It supplies none of that, leaving an agent unable to anticipate the return shape for an otherwise simple 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?

Only one parameter exists and schema description coverage is 0%, so the description does add slight meaning: "remote asset" implies asset_id refers to a remote (server-side) asset rather than a local file. It does not explain the ID's format, source (from upload_asset or list_assets), or length constraints.

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?

"Read metadata for one remote asset" names a specific verb (read), a specific resource (metadata), and a scope (a single remote asset). It is clearly distinguishable from list_assets, upload_asset, and delete_asset, though it never names those siblings explicitly.

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?

There is no guidance on when to use this versus list_assets (to enumerate) or other asset tools, and no stated prerequisites. The agent must infer usage purely from the verb and scope.

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 supplied, so the description carries the full behavioral burden. 'Read' implies a safe non-mutating call, but the phrase 'reconcile terminal state locally' is unexplained jargon and the description says nothing about what happens for unknown/expired ids, whether partial results appear while pending, or how long generation records persist.

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?

One sentence, front-loaded with the verb and resource, with no filler. The trailing clause about reconciling terminal state is efficient in length but vague in meaning rather than 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?

There is no output schema and no annotations, so the description should convey at least the shape of the status states and what the 'result' contains when terminal. It conveys neither, leaving the agent unable to interpret the response, though the core call semantics are understandable from name plus description.

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 single parameter has no documented format, yet the description only says the id refers to 'one ... generation'. It adds no meaning about whether this is the id returned by create_async_speech, its length limits, or accepted formats, so an agent must guess the id source.

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 ('Read') and resource ('the status and result of one ElevenCreative async speech generation'), which clearly distinguishes it from the create/generate siblings in the list. It falls short of 5 because it never names the counterpart tool (create_async_speech) that produces the id this one consumes.

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 only implied: 'async' plus 'status and result' signals this is a polling tool to call after kicking off a generation, but the description never says so explicitly, gives no polling cadence guidance, and names no alternative for retrieving finished audio (e.g. download_history_audio or get_generation_history_item).

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 exist, so the description carries the full burden; it does confirm this is a read and names the three data groups returned, which is meaningful disclosure. But it says nothing about whether reading affects budget state, what 'unsettled reservations' means, or how fresh the observed usage is.

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 front-loaded sentence with no filler, listing the three outputs in one compact clause. Slightly terse to the point that 'unsettled reservations' reads as unexplained jargon, but no sentence is wasted.

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-argument tool with no output schema, the description is the only source of return-value information, and it enumerates the data groups reasonably. It remains thin on what those groups contain and how they relate to the sibling budget/usage tools, leaving the agent to infer the response shape.

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 takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description does not waste effort inventing parameter guidance that does not exist.

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 verb 'Read' plus three specific objects (local generation policy, observed local usage, unsettled reservations) makes the resource concrete. 'Local' implicitly distinguishes it from get_remote_usage_report and get_usage_report, but no sibling is named explicitly.

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?

There is no statement of when to call this versus get_usage_report, get_remote_usage_report, estimate_cost, or set_local_budget. Usage is only inferable from the word 'Read' and the 'local' qualifier; no exclusions or preconditions are given.

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 does carry useful behavioral detail: the account/model portion is read-only and plan access may be unreportable, which is a real caveat an agent should know. However, it does not say whether this is a single aggregate call, what shape the result takes, or whether local flags could conflict with server-reported data.

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 short sentences with no wasted words, and the caveat about unknown plan access is placed after the primary statement. It is efficient, though the opening 'Combine...' phrasing delays the point slightly.

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 tool with no output schema and no annotations, the description should explain what comes back, since no structured field does. It gestures at the content (local flags, account, model, plan) but leaves the return shape and the meaning of 'local implementation flags' undefined.

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 takes zero parameters and the schema is empty with additionalProperties false, so there is nothing for the description to clarify. Baseline 4 applies; the description correctly implies a no-argument call.

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 says it combines local implementation flags with account and model information, which hints at a diagnostic/capability-report tool, but it never states plainly what the tool returns (e.g. a list of supported features). An agent must infer the purpose from the name plus an oblique 'combine' verb.

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?

There is no when-to-use guidance and no mention of alternatives, despite close siblings like get_account_info, get_subscription, and list_models that an agent would naturally consider for the same information. The only guidance is an implicit caveat that plan access may be unknown.

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 it does disclose one non-obvious behavior: reconciliation of a terminal job state against the local budget reservation. However, it never states whether this is read-only or has a local side effect, whether it is idempotent, or whether it should be polled.

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?

One front-loaded sentence with the resource stated first and the reconciliation nuance second; nothing is wasted. The second clause is dense jargon ("terminal job state", "local budget reservation") that costs some immediate readability.

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 and no annotations, so the description must explain what "state and metadata" actually contains and what happens for non-terminal jobs, and it does neither. For a status-polling tool, an agent cannot tell what it will receive or how to interpret it.

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 project_id has no documented format or provenance in either place, and the description does not compensate by saying where to obtain the ID (e.g., create_dubbing_project or list_dubbing_projects) or what a valid value looks like. The single parameter remains fully unexplained.

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 gives a specific verb ("Read") and resource ("current state and metadata of a dubbing project"), which separates it from the list-style sibling list_dubbing_projects and from get_budget_status. It does not explicitly name an alternative, but the singular project scope plus required project_id makes the distinction inferable.

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 only implied: the tool is for checking a dubbing project's state, and the clause about reconciling a terminal job state hints that it matters after job completion. There is no explicit when-to-use, when-not-to-use, or named alternative such as list_dubbing_projects for enumerating projects.

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 full burden of behavioral disclosure and largely fails. "Reconcile its terminal state locally" hints at a possible local side effect, but it never clarifies whether the call mutates state, requires auth, or is idempotent — critical ambiguity for a tool described as a "read".

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 front-loaded sentence with no filler, which is appropriately sized for the tool. The second half, however, is opaque enough that its brevity costs clarity rather than buying it.

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 annotations, no output schema, and no parameter documentation, the description is the only source of behavioral context and it supplies almost none. An agent cannot tell what the response contains, what "terminal state" means, or whether calling it has side effects.

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 only loosely implies that a template identifier and a run identifier are involved. It adds no meaning about format, where run_id comes from (presumably run_flow_template), or constraints beyond the schema's length limits.

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 names a specific verb and resource ("Read a template run's status"), which is distinguishable from siblings like get_flow_template and run_flow_template. However, the trailing clause "reconcile its terminal state locally" introduces jargon that muddies rather than sharpens the stated 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?

There is no explicit guidance on when to call this versus alternatives, no mention of calling it after run_flow_template, no polling cadence, and no statement about which run states are terminal. The only hint of usage is the implicit association with template runs.

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 full behavioral burden. "Read" implies a safe retrieval operation, but the description does not disclose permissions, error behavior, whether missing templates fail gracefully, or what the returned definition and input schema contain beyond a brief mention.

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 front-loaded sentence with no wasted wording. Its brevity is appropriate for a simple getter, though it is under-specified rather than optimally complete.

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 one-parameter retrieval tool with no output schema, the description states what is returned at a high level. However, it does not compensate for the absent annotations or the undocumented template_id parameter, leaving gaps around identifier format and failure behavior.

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 only parameter, template_id, has 0% schema description coverage and no format or constraint details in the description. The description implicitly establishes that the ID identifies a template but adds no syntax, source, or validation meaning beyond that.

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 specific verb, "Read," and a clear resource, "a template definition and its input schema." It is distinguishable from siblings like list_flow_templates and run_flow_template by focusing on retrieving one template's definition rather than listing or executing it, though it does not explicitly name those alternatives.

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?

There is no explicit guidance on when to use this tool versus list_flow_templates, run_flow_template, or get_flow_run. The usage is only implied by "Read a template definition," leaving the agent to infer prerequisites and appropriate 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?

No annotations are provided, so the description carries the full behavioral burden. "Read" implies a non-mutating operation and "metadata" implies it does not download audio, but the description does not disclose permissions, error behavior, or what metadata is returned.

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 front-loaded sentence with no unnecessary wording. It states the operation and scope efficiently.

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 one-parameter read tool, the description adequately signals that it returns metadata rather than audio. However, it omits where to obtain the history_item_id and lacks behavioral context that would normally be covered by annotations.

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 single required parameter is history_item_id, but schema description coverage is 0% and the description does not explain where the ID comes from or what format it takes. The parameter name is largely self-explanatory, but the description adds only marginal meaning 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 states a specific verb and resource: "Read metadata for one ElevenLabs history item." The singular scope distinguishes it implicitly from list_generation_history and download_history_audio, but it does not explicitly name a sibling tool as 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?

Usage is implied: use this when metadata for a single history item is needed. However, the description gives no explicit when-to-use guidance relative to list_generation_history, download_history_audio, or delete_history_item.

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 behavioral burden, yet it says nothing about what status values are returned, whether the call is cheap/safe to poll, or what happens for an unknown or expired generation_id. Only the bare read semantics are conveyed.

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?

One sentence with zero waste and the key information front-loaded, but the brevity crosses into under-specification rather than economy.

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 annotations and no output schema, the description is the only source of behavioral information, and it omits the returned status semantics, polling expectations, and error behavior. For a status-check tool this leaves meaningful gaps for an agent wiring up a generation workflow.

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 single parameter has 0% schema description coverage, and the description never mentions generation_id, its expected format, or its provenance (returned by generate_image or list_image_generations). The name is self-explanatory, which keeps this from a 1, but no meaning is added.

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?

"Read the status of one image generation" gives a specific verb (read) and resource (image generation) with singular scope, which separates it from list_image_generations and download_image at a glance. It stops short of naming those siblings explicitly, so it is clear but not fully differentiated.

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?

There is no guidance on when to call this versus list_image_generations, download_image, or generate_image, and no mention of where a generation_id comes from or whether polling is expected. Usage must be inferred entirely from the name.

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 full burden. It adds one genuinely useful disclosure, the module-disabled-by-default prerequisite, but says nothing about permissions, error behaviour when the module is off, or the shape of the returned metadata. For a read with no annotation coverage, this is a real but partial contribution.

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 short sentences, zero waste, with the tool's purpose front-loaded ahead of the availability caveat. Nothing is padded or repeated.

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 lookup, the description covers the purpose and the module-disabled prerequisite. Because there is no output schema, it should at least sketch what 'metadata' includes, and it should say how to obtain a valid finetune_id. Those gaps keep it at minimally adequate.

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 has one required parameter, finetune_id, at 0% description coverage, so the schema supplies only a type and length bounds. The description implies the id addresses 'one music finetune' but never states the expected id format or where the id comes from, for example list_music_finetunes or create_music_finetune.

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 names a specific verb and resource: 'Get metadata for one music finetune'. This clearly separates it from list_music_finetunes, update_music_finetune, and delete_music_finetune, though those siblings are never named. An agent can infer the difference from the verb and the singular scope.

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 second sentence states that the optional finetune module is disabled by default, which is a real precondition for calling the tool. However, it never says when to use this tool rather than list_music_finetunes or get_music_finetune's other siblings, and it gives no guidance on what to do if the module is disabled.

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 supplied, so the description carries the full burden. It adds one genuinely useful behavioral fact — that workspace permissions may be needed — but says nothing about whether the call is read-only, whether results are aggregated or paginated, rate limits, or what a response looks like.

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 compact sentences with no filler, and the primary action is front-loaded. The phrase 'official workspace product usage' is slightly loaded with unexplained qualifiers, but overall the text is appropriately sized.

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 multi-parameter aggregation/reporting tool with no output schema and no annotations. An agent still cannot tell what the report contains, how group_by and interval_seconds shape the result, or how this differs from get_usage_report. The definition is under-specified relative to the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.