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

With no annotations, the description carries the full behavioral burden. It implies a write that attaches a source, but says nothing about whether the notebook must already exist, what happens on duplicate titles, whether removal is possible, or what the 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?

A single compact sentence with the purpose front-loaded and an example in parentheses. Nothing is wasted, though the brevity contributes to the missing usage and behavioral 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 required-3-parameter mutation tool with no annotations, no output schema, and 0% schema description coverage, the description is too thin. It gives a one-line purpose but does not compensate for the absent parameter and behavior 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 coverage is 0% and the description only hints that the text payload is the source content (via the parenthetical example). It adds no meaning for 'title' or 'notebook_id' beyond their self-evident names, leaving half the parameter semantics undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Adiciona') and resource ('um texto como fonte de um caderno'), and the parenthetical example clarifies the kind of text. It implicitly separates itself from the sibling add_source_url by specifying text rather than a URL, though it never names that sibling.

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 given, and the obvious alternative, add_source_url (also adding a source to a notebook), is never mentioned. An agent must infer from the word 'texto' alone that this is for inline text content rather than a link.

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 only restates the mutation. It does not disclose what happens on duplicate URLs, whether the notebook must pre-exist, what errors are returned, or whether the source is processed asynchronously.

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 compact sentence that front-loads the verb and resource. Nothing is wasted, though it is terse enough to omit useful context rather than being over-long.

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 mutation with no annotations, no output schema, and 0% parameter description coverage, the description is thin. It omits notebook_id semantics, prerequisite conditions, and result/error behavior, leaving the agent to infer much of how to invoke it correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It usefully tells the agent that 'url' accepts a website or YouTube link (a format constraint the schema does not convey), but it says nothing about 'notebook_id' beyond implying it identifies the target notebook.

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 ('Adiciona') and resource ('site ou vídeo do YouTube (URL) como fonte de um caderno'), clearly framing the action as attaching a URL source to a notebook. It implicitly contrasts with the sibling add_source_text by specifying URL-based sources, though it never names that sibling 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?

Usage is only implied: the mention of 'site ou vídeo do YouTube (URL)' suggests this is the tool for link-based sources, versus add_source_text for pasted text. There is no explicit when-to-use/when-not statement and no mentioned prerequisites such as the notebook having to exist 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?

No annotations are provided, so the description carries the full behavioral burden. It does not say whether the call is read-only, whether the answer cites sources, whether the notebook must already contain sources, or what happens if it does not. Only the answering basis ('fontes do caderno') is disclosed.

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 tight sentence with no filler, front-loading the action. It is efficient, though its brevity reflects under-specification rather than deliberate 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, no output schema, and 0% parameter description coverage, this two-parameter tool needs the description to explain prerequisites and return behavior. The single sentence leaves the agent without enough to invoke it confidently beyond guessing.

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 both parameters (notebook_id, question) are undocumented in the schema. The description only loosely implies that the question is answered against notebook sources; it adds no format, length, or ID semantics to compensate for 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?

States a specific verb ('Faz uma pergunta') and resource ('fontes do caderno'), making clear this is a question-answering tool scoped to notebook sources. It implicitly distinguishes itself from the generation-oriented siblings (mind map, quiz, audio), but never names an alternative 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?

No when-to-use guidance, no prerequisites, and no mention of when a different tool (e.g. get_notebook_summary) would be preferable. The agent must infer usage entirely from the purpose statement.

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 says nothing about permissions, whether a duplicate title is rejected or allowed, what identifier is returned, or that this is a write operation – all of which matter for a creation 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 front-loaded sentence with no filler. It is efficient, though the brevity is partly under-specification rather than disciplined concision.

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 one-parameter, no-output-schema tool the description is minimally viable, but with zero annotation coverage it should at least disclose that it is a mutating operation and what the caller gets back (an id/handle needed by sibling tools).

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but there is only one self-describing parameter (title, string, required). The phrase "com o título informado" merely restates the parameter name and adds no constraints such as length, uniqueness, or format.

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+resource ("Cria um caderno novo") and the input it requires, so the operation is unambiguous. It does not differentiate itself from siblings, though for a creator tool among list/generate siblings that is largely self-evident.

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, no prerequisites, and no mention of alternatives. The agent must infer that this is the tool to reach for when a new notebook must exist before add_source_* or generate_* calls.

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 discloses almost nothing behavioral. It does not indicate whether generation is asynchronous/long-running, whether it overwrites prior audio, what permissions are required, or what the result 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?

A single front-loaded sentence with no wasted words, which is good. However, it is so terse that it under-specifies the tool rather than being genuinely 'concise', and it omits any structure that would aid invocation.

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 generative tool with no annotations, no output schema, and 0% parameter coverage, the description is far too thin. It omits prerequisites, expected behavior, and return characteristics that an agent needs to call it correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description explains neither parameter. It never clarifies that notebook_id identifies the target notebook or that instructions customizes the podcast content, leaving both the required and optional parameters 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?

States a specific verb and resource: generates an 'Audio Overview' (podcast) in NotebookLM. It is distinguishable from close siblings like generate_video_overview and generate_mind_map by naming the audio/podcast output, though it offers no further differentiation among the family of generate_* 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?

No guidance on when to use this versus alternatives such as generate_video_overview or get_notebook_summary, and no statement of prerequisites (e.g., that the notebook must already contain sources). Usage must be fully inferred.

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, and it discloses almost nothing: not whether generation is synchronous or long-running, whether it requires existing sources, whether the table is persisted or returned, or any rate/cost considerations. Only the bare fact of creation is 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?

A single short sentence with no filler or redundancy, and the action is front-loaded. The problem is under-specification rather than verbosity, so it is efficient but too thin to be genuinely well-structured.

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 generative tool with no annotations, two undocumented parameters, and no output schema, the description leaves nearly every question unanswered — input requirements, output form, and relationship to sibling generators. It is far from complete for the tool's 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% and the description adds no meaning for either parameter. The agent gets no explanation of what notebook_id must reference or what the optional instructions field controls beyond its Portuguese default text.

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 clear verb and resource ("Gera uma tabela de dados") plus a scope ("no NotebookLM"), so the agent knows what action it performs. However, it offers no differentiation from sibling generators like generate_infographic, generate_mind_map, or generate_summary_report, all of which produce artifacts from notebook content. Purpose is intelligible but generic.

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. The agent must infer from the name alone that this should be chosen over generate_infographic or generate_mind_map when tabular output is wanted, and nothing states prerequisites such as needing sources already added to the notebook.

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, yet it discloses nothing beyond purpose: no mention of cost/credits, generation latency, language behavior, or what is produced. A mutation-like generation tool with zero annotation coverage leaves the agent guessing about side effects.

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 zero waste and the purpose front-loaded, which is structurally fine. But the brevity reflects under-specification rather than economy, so it earns only a middling score.

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 0% parameter coverage, the description is too thin for a tool that triggers content generation in a crowded sibling set. It leaves the agent without the information needed to call it correctly or to choose it over alternatives.

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 the undocumented parameters—and it does not. It never explains that notebook_id selects the target notebook or that 'instructions' controls generation prompt/defaults, missing the only chance to clarify the two inputs.

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 ('Gera') and resource ('cartões de estudo (flashcards)') in a named environment (NotebookLM), so the operation is unambiguous. However, it does nothing to separate itself from siblings such as generate_quiz or generate_mind_map, which share the same 'generate X from a notebook' shape.

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 tool versus generate_quiz, generate_mind_map, or generate_summary_report, nor any prerequisite or exclusion. The agent must infer usage purely 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 and discloses nothing. It does not say whether generation is long-running/asynchronous (as infographic generation typically is), whether it overwrites or appends, whether the notebook must already contain sources, 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?

It is a single short sentence, so structurally clean, but that brevity is under-specification rather than conciseness — there is no useful content to front-load.

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 generative tool with no annotations, no output schema, and two undocumented parameters, the description supplies none of the context an agent needs to invoke it correctly or predict its 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% for two parameters, and the description mentions neither notebook_id nor instructions. With zero compensation from the description, an agent cannot tell which notebook is targeted or what the default instruction string implies.

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 ('Gera um infográfico'), which distinguishes it from siblings like generate_mind_map or generate_slide_deck by artifact type. However, 'no NotebookLM' adds no differentiation since every sibling presumably operates there, and nothing indicates it acts on a specific notebook.

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, no prerequisites, no mention of alternatives among the many other generate_* siblings. The agent is left to guess when an infographic is appropriate versus a slide deck, summary report, or mind map.

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 one useful side effect — that the result is persisted as a note in the notebook — which implies a write operation. But it says nothing about permissions, whether an existing note is overwritten, source requirements, or how long generation takes.

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 compact sentence with the action and outcome front-loaded. No filler, though it is arguably too terse for the gaps it leaves.

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 generation tool with no annotations, no output schema, and an undocumented required parameter, the description should say more about what is produced, where the note lands, and what the notebook_id must reference. As written, an agent knows the gist but not the operational 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% and the single parameter 'notebook_id' is undocumented in both schema and description. The phrase 'no caderno' loosely implies the notebook is the target, but it does not clarify the identifier format or whether the notebook must already 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 description names a specific verb and resource ('Gera um mapa mental') plus an outcome ('salva como nota no caderno'), so the action is unambiguous. However, it offers no differentiation from the many sibling generate_* tools beyond the implicit resource name.

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 tool versus generate_summary_report, generate_data_table, or any other sibling generator. No prerequisites, no exclusions, no indication of when a mind map is the appropriate artifact.

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, yet it discloses nothing about generation time, whether the call is synchronous or queued, cost/quota implications, or where the resulting quiz is stored. It does not even clarify that this is a non-destructive generation call versus a mutation of notebook 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?

A single short sentence with no filler or repetition, so nothing is wasted. However, the brevity reflects under-specification rather than discipline; there is no front-loaded scope, output expectation, or parameter note.

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, 0% parameter documentation, and an artifact-generating tool whose behavior (async, language defaults, source dependence) matters, the description is far too thin. An agent cannot invoke this correctly without guessing at the meaning of instructions and the timing of the 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 two parameters, and the description adds no meaning for either: it never mentions notebook_id, which notebook the quiz targets, or that instructions can steer quiz content and language. With no compensating text for undocumented parameters, this is a clear 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 ('Gera um teste (quiz) no NotebookLM'), so an agent knows it produces a quiz artifact inside a notebook. It does not distinguish itself from near-siblings such as generate_flashcards or generate_summary_report, which are equally plausible for the same notebook, and it is written in Portuguese while the rest of the toolset is English.

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 indication of when to choose a quiz over flashcards, a summary report, or a data table, nor any prerequisite such as requiring sources to have been added first. The agent is left to infer usage entirely from the verb.

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 entire behavioral burden, and it discloses almost nothing: not whether generation is async/long-running, whether it overwrites existing decks, what permissions are needed, or what the result looks like. The only contextual hint is that it operates 'in NotebookLM'.

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 is appropriately front-loaded and contains no filler, but it is under-specified rather than genuinely concise — the brevity reflects missing information rather than tight editing.

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 generation tool with no annotations, no output schema, and zero parameter documentation, the description is far too thin. An agent cannot tell what inputs to shape, what the call returns, or how long it takes; only the high-level purpose is conveyed.

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 there are two parameters, yet the description says nothing about notebook_id (required) or instructions (with its default). It does not compensate for the documentation gap 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?

The description gives a specific verb ('Gera') and resource ('apresentação de slides') scoped to NotebookLM, which cleanly separates it from siblings like generate_mind_map or generate_quiz. It does not, however, explicitly differentiate itself from the other generate_* tools beyond the resource noun.

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 tool versus the many sibling generators, no prerequisites (e.g. whether a notebook must already exist), and no mention of when a slide deck is the appropriate output. Usage must be fully inferred.

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 discloses almost nothing: not whether generation is synchronous or long-running, whether it needs existing sources, whether it overwrites a previous report, or whether it consumes quota. Only the fact that a document is produced is communicated.

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 no filler, so nothing is wasted, but its brevity stems from under-specification rather than disciplined editing. It is front-loaded with the verb, which is the one structural merit.

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 generation tool with two undocumented parameters, no annotations, and no output schema, the description is too thin. In a sibling set containing get_notebook_summary, the overlap between a 'summary report' and a 'notebook summary' is exactly the gap that needed explaining.

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 mentions no parameters at all. The purpose of 'instructions' (free-text prompt steering, defaulting to 'Crie um documento de briefing.') and whether notebook_id must reference an existing notebook are left completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and artifact ('Gera um relatório / documento de briefing') scoped to NotebookLM, so the agent knows it produces a briefing document rather than a mind map, quiz, or audio overview. It does not, however, distinguish itself from the closely-named sibling get_notebook_summary, which is the main ambiguity an agent would face.

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 the many similar generation siblings (get_notebook_summary, generate_mind_map, generate_data_table) or what prerequisites (e.g., sources already added) must be met. The agent must infer usage 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 behavioral burden, and it discloses nothing. Video generation is presumably long-running and expensive; the description says nothing about async behavior, expected duration, quota/cost implications, or how the resulting video is retrieved.

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 no bloat and the action front-loaded, so it is structurally clean. It earns no more than a middling score because brevity here comes at the cost of under-specification rather than efficient information density.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-annotation, no-output-schema generative tool with 2 undocumented parameters and 13 siblings, this description is drastically incomplete. Nothing tells the agent the cost, latency, or output characteristics of the operation, nor how it differs from the other generate_* tools.

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 parameters. The description does not mention notebook_id (required) or instructions (with its default prompt), leaving an agent with no documented meaning, format, or constraints for either parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Gera um Resumo em Vídeo no NotebookLM' is essentially a Portuguese restatement of the tool name generate_video_overview. It adds only the platform name, not the scope, output format, or what distinguishes it from generate_audio_overview or generate_slide_deck.

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, no prerequisites, and no mention of the numerous sibling generation tools (audio overview, slide deck, infographic, mind map). The agent must infer entirely from the name which generation mode to pick.

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 but discloses almost nothing: it does not say the operation is read-only, whether it is expensive/slow (LLM generation), whether a summary must already exist, or what language/format the summary is in. Only the bare output concept ('main points') is 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?

A single short sentence that is front-loaded and free of waste, but it is under-specified rather than genuinely concise for a generation tool; size is appropriate, content is thin.

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?

No annotations, no output schema, and no param documentation mean the description is the only source of context, and it omits what the summary contains, how it is produced, and how it differs from generate_summary_report or ask_notebook. Incomplete for a generative 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?

One parameter (notebook_id) with 0% schema description coverage. The description merely implies the notebook is the subject via 'caderno', adding no format, ID-shape, or validity information beyond the schema's type string.

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 clear verb+resource: it generates (Gera) a summary (resumo) of the notebook (caderno), and the sole parameter name notebook_id corroborates the resource. However it gives no differentiation from the overlapping sibling generate_summary_report, so an agent cannot tell which summary tool to pick.

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 prerequisites (e.g. notebook must already contain sources), and no mention of the near-identical sibling generate_summary_report. The agent must guess the routing.

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 and no output schema, so the description carries the full burden. It does disclose scope ('todos ... da conta', implying no filtering and a single account-wide result), but says nothing about ordering, pagination, or return shape for what could be a long list.

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 sentence that front-loads the action and resource with zero padding. Nothing to trim.

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 zero-param list tool against a notebook-oriented sibling set, the description is functional but thin: it never indicates what a returned notebook object contains or how results are ordered, which matters since no output schema exists.

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 on this dimension; baseline is 4.

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 ('Lista') and resource ('todos os cadernos (notebooks)') with scope ('da conta NotebookLM'). It does not explicitly distinguish itself from siblings like get_notebook_summary, but the list-all semantics are clear enough to route correctly.

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: listing notebooks is the obvious first call before create/add/ask operations. There is no explicit when-to-use or when-not-to-use guidance, nor any named alternative, but for a zero-param listing tool this is minimally adequate.

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