Cálculo de Juros e Multa

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

Beyond the annotations, the description discloses persistence behavior: config-based tokens are permanent and non-expiring, while passed tokens are session-only. It also clarifies that calling with no arguments yields a link rather than performing an action. This adds meaningful behavioral context without contradicting the idempotent and non-destructive hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is compact and front-loaded, immediately stating the tool's purpose and audience. Every sentence provides actionable guidance, and the two authentication paths are clearly separated without unnecessary elaboration.

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 single-optional-parameter auth tool with no output schema, the description covers the main scenarios: permanent config-based auth, session-only token auth, and no-arg link retrieval. It does not describe the exact response format of the no-arg call, but given the simplicity and the annotations, the coverage is 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 input schema only defines token as an optional string with no description, so the description carries the full semantic burden. It explains that the token should be a JWT pasted by the user and that omitting it returns the login link. This meaningfully compensates for the schema's lack of detail, though it does not explain JWT structure or validation.

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

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

The description clearly states the tool is for IDE-agent authentication: log in via browser, obtain an access token, and either configure it permanently or pass it for a session. The verb 'authenticate' plus the concrete login flow makes the purpose evident, though it does not explicitly contrast with the sibling 'connect' tool.

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 explicit usage guidance: use the server config header for a permanent, non-expiring connection, or call with { token } for session-only login, or call with no args to get the login link. It clearly distinguishes between the recommended long-term setup and the temporary paste-in path.

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

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

Annotations already declare readOnly and idempotent behavior. The description adds meaningful procedural detail: it reajusta by index, corrects each overdue month, applies 1% monthly interest and a late fine, and returns a monthly breakdown plus total. This goes beyond the annotations without contradicting them.

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: the first front-loads the legal context and calculation logic, the second states the return structure. No filler or repetition.

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

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

For a 9-parameter tool with no output schema and no parameter descriptions, the explanation covers the core workflow and output but omits input formats, optional parameter behavior, and enum choices. It is adequate for a familiar domain but not fully self-sufficient 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 description coverage is 0%, so the description must compensate. It implicitly explains core inputs like aluguel_inicial, inicio_contrato, inicio_atraso, and fim_atraso, and mentions indice, juros, and multa conceptually. However, it leaves optional parameters (data_calculo, periodicidade_meses) and the enum values for indice undocumented, so an agent cannot fully determine what to supply for all 9 parameters.

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 clear, specific operation: calculating overdue rent adjustments under Lei 8.245/91, including index-based correction, mora interest, and fine. It also states the output format (per-month breakdown plus total), which fully distinguishes this tool from sibling calculation tools like calculo_revisional or calculo_indice.

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 clear usage context: overdue rent under a specific Brazilian law. It does not explicitly name alternatives or exclusion criteria, but the legal and domain-specific framing makes it evident when this tool applies.

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

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

Beyond the readOnly/idempotent annotations, it discloses the critical non-additivity behavior of SELIC (includes correction + interest) and the post-2024 legal regime. It also states the return shape ('detalhamento por parcela e totais'). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two dense sentences: the first states the operation and return value, the second front-loads the most important legal caveats. No filler words or redundant restatement of the tool name.

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

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

For a complex 11-parameter financial calculation with no output schema, the description gives enough orientation: purpose, inputs, return summary, and legal warnings. It is not fully complete because some parameter interactions and defaults (e.g., pro-rata behavior, fee bases) are not specified, but the schema covers structural 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?

With 0% schema description coverage, the description compensates only partially: it maps parcelas, indice, juros, multa, and honorarios, and warns about SELIC combined with tax. It leaves several parameters (pro_rata, multa_incide_sobre_juros, data_calculo, installment type semantics) unexplained, though their names and enums provide some self-evident 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 names a specific domain and action: 'Atualização monetária / liquidação de débito judicial' that corrects parcelas by official indices and applies interest, penalties, and fees. This clearly distinguishes it from sibling calculo_* tools by judicial-debt settlement 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?

It gives clear legal context for when the tool is appropriate, including the SELIC rule and the post-09/2024 IPCA + legal-rate regime. It does not explicitly name alternative sibling tools or state exclusion conditions, so it stops short of a 5.

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

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond annotations by explaining the three-phase calculation sequence, the role of judicial circumstances, mitigating/aggravating factors, and proportional adjustments. No contradiction with annotations exists.

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, compact sentence that front-loads the core purpose and packs in relevant legal citations, phases, and configurability. Every element serves a purpose, and there is no fluff 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?

Given the high parameter count (9), no output schema, and zero parameter documentation, the description is not complete enough for reliable invocation. It omits the required inputs, the meaning of each fraction, and what the tool returns. The legal context is helpful but leaves too many operational gaps.

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

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

Schema description coverage is 0%, so the description must compensate by explaining the parameters, but it does not mention key inputs like pena_min_anos, pena_max_anos, fracao_fase1, or fracao_fase2. It provides high-level conceptual context about phases and configurable fractions, but agents cannot map these to the actual schema properties with confidence.

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

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

The description clearly identifies the tool's purpose: calculating criminal sentence dosimetry under the Brazilian three-phase system (art. 68 CP). It includes the legal basis and the phases involved, which distinguishes it from other 'calculo_*' siblings focused on different legal/administrative calculations. However, it lacks an explicit verb like 'calcula' and does not name sibling 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 description implies the tool is for sentencing calculations by describing the trifásico method, but it does not explicitly state when to use this tool versus the many sibling calculation tools. There are no exclusions or explicit alternative references, so usage guidance is only implied through the legal terminology.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it works per deposit, includes 3% a.a. interest, and accepts manual deposits, with OCR extraction only as a future capability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is compact and front-loaded: it states the purpose, the calculation logic, and the accepted input format in two sentences. No filler or redundant restatement of the tool name.

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

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

The description gives the essential calculation context and input mode, but it omits guidance on optional parameters and output behavior. Since there is no output schema, a bit more detail on what the result represents or how the index is chosen would make the tool more reliably callable.

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

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

With 0% schema description coverage, the description must compensate for undocumented parameters. It explains the core comparison (inflation index vs TR) and the 3% interest, but it does not explicitly describe data_calculo, incluir_juros_3aa, or how the indice enum interacts with the calculation. Parameter names and the enum partially fill the gap, but the description could do more.

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

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

The description opens with the specific domain ('Correção do FGTS (tese TR → INPC/IPCA-E, STF)') and a concrete verb ('calcula a diferença entre corrigir pelo índice de inflação vs pela TR'), so an agent can clearly identify what the tool does. It also distinguishes this tool from the sibling calculo_* tools by naming the FGTS thesis and per-deposit calculation 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 description implies when to use the tool: when FGTS correction is needed and deposit-level data is available manually. However, it does not explicitly name alternatives or state when not to use this tool, even though many similar calculo_* siblings exist.

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

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to re-establish safety. It adds useful behavioral context: the BACEN/IBGE date inclusion convention, the conditional outputs depending on `valor` and `incluir_valores`, and the fact that enabling `incluir_valores` pulls raw monthly index values. This goes beyond what the annotations and schema alone convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is compact and front-loaded with the resource and the core calculation outcome. The two sentences each carry distinct information: the main calculation convention and the conditional output behaviors. The informal phrase 'puxar os índices crus' is slightly loose but does not substantially hurt clarity or structure.

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 there is no output schema and six parameters, the description covers the essential calculation semantics, date convention, and optional outputs. Still, the unexplained `pro_rata` parameter and the lack of any detail on the return format or error conditions leave notable gaps. It is adequate for a straightforward read-only index lookup but not fully complete for all six 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 description coverage is 0%, so the description must compensate. It adds semantics for `data_inicial`/`data_final` via the date convention, for `valor` via the corrected-value behavior, and for `incluir_valores` via monthly variations. However, it does not explain `pro_rata` and gives almost no explicit guidance on the `indice` parameter beyond the fact that it is an official index, leaving a meaningful gap for a 6-parameter tool.

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

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

The description clearly identifies the tool's function: querying an official index and returning an accumulated correction factor between two dates. It also specifies key conventions (month start excluded, month end included) and optional behaviors (corrected value, monthly variations). It does not explicitly differentiate from sibling tools, though 'índice oficial' and the calculation semantics make the resource distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool based on parameters: if `valor` is provided it returns the corrected amount, and if `incluir_valores` is true it returns published monthly variations. However, it does not explicitly state when to choose this tool over sibling tools such as `calculo_aluguel` or `calculo_atualizar`, nor does it mention any prerequisites or exclusions.

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

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable algorithmic detail: shareable mass is computed as assets minus debts according to the regime, each spouse receives a quota, and a 'torna' compensates imbalance. It also discloses that entra_partilha overrides the regime default, which is non-obvious behavioral context.

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: the first front-loads the purpose and calculation formula, the second gives a targeted parameter instruction. There is no filler, repetition of schema details, or unnecessary 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?

The description captures the core algorithm and override behavior, but with no output schema it does not describe the return shape or result structure. It also omits semantics for several optional fields that might be relevant for accurate use. For simple cases an agent can proceed, but for edge-case inputs like oneroso or anterior_casamento it must guess.

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

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

With 0% schema description coverage, the description must compensate, and it does explain the roles of bens, dívidas, regime, and entra_partilha. However, it leaves several nested fields undefined—oneroso, titular, heranca_doacao, adquirido_na_constancia, nomes, and anterior_casamento—so an agent must infer their meaning. This partial coverage warrants a moderate score.

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 ('apura') and a specific resource ('massa partilhável', 'quota de cada cônjuge') within a clearly defined domain: divorce property division by marital regime under the Civil Code. It also mentions the override mechanism (entra_partilha), which clarifies behavior. This clearly distinguishes it from sibling tools like calculo_pensao and calculo_fgts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies the use case—divorce asset division by property regime—and lists the regimes in the schema. It gives a conditional usage instruction for the entra_partilha flag. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of a 5.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral detail: per-month calculation of the amount due, subtraction of payments, INPC correction, and 1% monthly interest from each due date, plus the legal basis. No contradiction with annotations was found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single dense sentence that front-loads the purpose and legal reference, followed by the calculation steps. Every phrase adds information, with no filler, though its compactness contributes to the parameter ambiguity.

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 complex tool with 9 parameters and no output schema, the description details the calculation methodology but omits the response format, date formats, how optional parameters (juros, indice, data_calculo) interact with defaults, and what 'referencia' means. It is not fully complete for an agent to invoke without further assumptions.

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 carries the burden. It explains the three 'forma' modes ('% do salário mínimo do mês, valor fixo ou % da remuneração') and the role of payments and remuneracoes, but it leaves the required 'referencia' parameter undefined and doesn't mention that 'indice' and 'juros' are configurable. It adds useful semantic context but incompletely maps to the 9-parameter 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 opens with 'Pensão alimentícia em atraso (art. 528 CPC)', identifying a specific legal scenario and calculation type. It states a concrete verb ('calcula') and outlines the monthly computation, payment subtraction, and index/interest application, making it easy to distinguish from sibling calculators like calculo_aluguel or calculo_trabalhista.

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 clearly identifies the target use case (arrears alimony under art. 528 CPC), so an agent knows when to select it. However, it does not explicitly name sibling tools or state when not to use it, so the guidance relies on the specificity of the legal domain rather than explicit alternatives.

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

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description adds value by disclosing the calculation logic: percentage based on legal categories, discounts for work/study remission and detention, and the returned progression date. It does not contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single dense sentence with no filler, and the legal domain is front-loaded. It encodes a complex formula compactly and is appropriately sized, though it is somewhat overloaded with legal qualifiers.

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

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

Given the tool's complexity, 9 parameters, and no output schema, the description gives the core calculation factors and the return value, but it leaves the required sentence-length and start-date inputs implicit and omits percentage specifics or output format details. It is adequate for selecting the tool but not fully sufficient for invoking it with complete confidence.

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

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

With 0% schema description coverage, the description must compensate for the 9 parameters. It does map most of them conceptually: reincidente, hediondo, violencia, resultado_morte, dias_trabalhados, horas_estudo, and dias_detracao. However, the two required parameters — pena_anos and inicio_cumprimento — are only implicit in 'percentual de cumprimento' and 'data de progressão' rather than explicitly described.

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 specific legal calculation — prison regime progression under LEP art. 112/Lei 13.964/2019 — and lists the decisive factors (reincidence, heinous crime, violence, death result), remission, and detention. It also states the concrete output: the progression date. This clearly distinguishes it from the other calculo_* sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides strong contextual clues that this tool is for calculating prison regime progression, but it never explicitly states when to use it versus alternatives or when not to use it. There is no mention of sibling tools or exclusions, so the usage guidance is implied rather than explicit.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond those annotations: it calculates by summing corrected discount installments and situates the operation within the STF agreement framework. No contradiction with annotations exists.

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 consists of two focused sentences with no filler. It front-loads the core purpose and adds relevant legal and code detail without unnecessary elaboration. Every part earns its place.

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

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

The description gives good domain context and a clear sense of the computation, but it leaves gaps: no output format description, no explicit explanation of how 'indice' affects the correction, and no guidance on required versus optional parameters. It is adequate but not fully complete for a tool with no output schema and low schema description coverage.

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 needed to compensate by explaining the parameters. It only loosely relates to 'descontos' by referring to 'parcelas descontadas'. It does not explain the role of 'indice' (despite mentioning 'corrigidas') or 'data_calculo', leaving the agent to infer their meaning from the schema alone.

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 names the operation (restituição de descontos indevidos no INSS) and the specific resource/domain, including the exact associative fraud codes (280/304/310/378). It states what the tool does: sum corrected discounted installments. This strongly distinguishes it from sibling calculation tools by domain and legal basis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when handling undue INSS discounts and administrative restitution via the STF agreement (ADPF 1.236). However, it does not explicitly state when not to use it or mention alternatives among the many sibling calculation tools, leaving routing partially to inference.

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

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

The annotations already establish readOnlyHint, idempotentHint, and destructiveHint. The description adds meaningful behavioral detail: it performs a live BACEN rate lookup by modality+month, uses Price or SAC systems, and clarifies that the average rate is a reference, not a ceiling (STJ legal context). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two concise sentences with no filler. The first sentence front-loads the core calculation and method, and the second adds a critical legal caveat. Every word 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 read-only calculation tool with no output schema, the description covers the algorithm, data sources, systems, and a legal nuance. It does not explain return value shape or date formats, but the mention of 'apura o excedente por parcela' gives a reasonable expectation of the output. Given the tool's complexity, this is nearly 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 semantically covers several parameters (modalidade, mês/data_contrato, Price or SAC, parcela, financiamento), but it does not explicitly define each parameter or their units. The Portuguese parameter names are self-explanatory, but the description does not fully replace missing schema descriptions.

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 ('recalcula') and a specific resource ('financiamento' via BACEN average rate), and adds scope ('Revisional de contrato bancário'). It clearly distinguishes this tool from siblings like calculo_aluguel or calculo_fgts by describing the bank-contract review use case and the Price/SAC surplus calculation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: it is for recalculating a bank loan under the BACEN average rate and computing the surplus per installment. It does not explicitly name alternatives or when not to use it, but the domain is specific enough that an agent can infer appropriate use from the 'Revisional de contrato bancário' framing.

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

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

The annotations already establish that this is read-only, idempotent, and non-destructive. The description adds useful domain context about computing 5% limits and corrected restitution of discounts, going beyond the annotations. Still, it does not clearly state operational behavior such as how inputs are used or what the calculation produces.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is compact and front-loaded with the key subject, and it avoids filler. The thesis sentence is short but somewhat cryptic; it adds context without fully explaining the calculation, so the structure earns a strong but not perfect 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?

There is no output schema, and the tool has five parameters with zero schema-derived descriptions. The description gives useful domain color but leaves out essential operational details: what the tool returns, how beneficio_mensal and descontos relate to the calculation, and how tipo/indice affect the result. An agent would need to infer too much to invoke this tool reliably.

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

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

With 0% schema description coverage, the description needed to compensate by explaining the input parameters, but it only vaguely references 'descontos' and the INSS margin context. It does not clarify beneficio_mensal, tipo, indice, data_calculo, or the meaning of the RMC/RCC and index enums. This is insufficient for an agent to know how to populate the parameters correctly.

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

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

The description clearly identifies the tool's domain: RMC/RCC calculations involving INSS consignable card margin, codes 217/268, 5% limits, and corrected restitution of discounts. It distinguishes this from sibling calculation tools by naming a specific and uncommon legal/financial subject. However, it lacks an explicit verb such as 'calculates' or 'returns', so the action is mostly inferred from the tool 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?

The description implies the tool is for RMC/RCC cases tied to INSS codes 217/268 and a revolving-card-sold-as-consigned thesis. This gives enough context for a domain-aware agent to narrow the selection, but it never explicitly states when to use this tool versus sibling tools, nor does it mention when not to use it.

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

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds useful behavioral context by detailing the coefficient rule (60% + 2% per year above 20H/15M) and the floor/ceiling logic, but it does not discuss edge cases, invalid inputs, or optional parameter defaults.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single dense, well-structured sentence that packs the benefit name, legal context, calculation formula, and floor/ceiling constraints. Every phrase contributes meaning, and 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?

Given the absence of an output schema, the description does not explicitly state that the return value is the computed RMI amount, though this is strongly implied. The formula and parameter coverage are complete enough for an agent to invoke the tool correctly, but explicit return-value and default-behavior notes would make it fully self-contained.

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 carries the full burden of explaining parameters. It successfully maps all inputs: media_salarios, sexo via the 20H/15M threshold, tempo_contribuicao_anos via the 'per year' coefficient, salario_minimo as the floor, and teto_inss as the ceiling. This compensates fully for the lack of schema descriptions.

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

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

The description clearly identifies the tool as calculating RMI (Renda Mensal Inicial) and gives the specific formula: average contribution salaries × coefficient, with minimum wage floor and INSS ceiling. It is resource-specific and effectively distinct from sibling calculators, though it lacks an explicit verb like 'calculates'.

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 by the RMI definition and formula: an agent would use this tool when it needs the post-reform initial monthly retirement benefit. However, there is no explicit guidance on when to prefer this tool over sibling calculators, nor any mention of exclusions or alternatives.

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?

As anotações já informam readOnlyHint, idempotentHint e destructiveHint, cobrindo a segurança da operação. A descrição acrescenta que o valor é dinâmico e provém do IPEADATA, mas não detalha comportamento adicional, como eventual necessidade de rede ou atualização da fonte.

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 descrição é curta, direta e sem redundância. A primeira frase já informa o objeto e a fonte; a segunda acrescenta os casos de uso relevantes sem desperdício.

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?

Para uma ferramenta simples com um único parâmetro opcional, a descrição é quase suficiente, mas não esclarece o comportamento sem 'ano' nem o formato do retorno. Como não há output schema, seria útil informar que o resultado é o valor monetário do salário mínimo para o ano.

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?

A cobertura do schema é 0%, e a descrição apenas menciona 'de um ano', insinuando que o parâmetro 'ano' se refere ao ano desejado. Não explica o que acontece quando o parâmetro é omitido (já que não é obrigatório), nem limites ou formato esperado para o ano.

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?

A descrição identifica claramente o recurso: salário mínimo nacional vigente de um ano, com fonte IPEADATA. Distingue-se dos irmãos ao explicitar que é a base para dosimetria, pensão por porcentagem do SM e mínimo existencial, embora não use um verbo explícito como 'retorna' ou 'calcula'.

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?

A descrição fornece contexto de uso ao indicar que o valor serve de base para dosimetria (dia-multa), pensão por % do SM e mínimo existencial. Não há exclusões explícitas nem menção a alternativas, mas o contexto de uso fica razoavelmente claro.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful semantic context about the calculation basis and the R$600 parametrizable minimum, but it does not disclose additional behavioral details such as output shape, rounding, or handling of missing optional fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single dense sentence with no filler. It front-loads the legal context and then lists the exact computed outputs, making it easy to scan and understand quickly.

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 calculator with four parameters and no output schema, the description gives a solid high-level picture but leaves some invocation details implicit, such as how prazo_meses is expressed (months vs. years), whether renda_liquida is gross or net, and what the return structure looks like. The schema covers parameter names, and annotations cover safety, so the description is adequate but not 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 adds meaning for key parameters: 'mínimo existencial (R$600, parametrizável)' maps to minimo_existencial, 'plano de até 5 anos' maps to prazo_meses, and 'renda disponível' relates to renda_liquida. It does not explain the structure of 'dividas' beyond what the schema provides, but it gives useful legal and financial context for most 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 clearly identifies the tool's domain (over-indebtedness under Lei 14.181/2021) and specifies the outputs: percentage of committed income, existential minimum, available income, and payment capacity over up to 5 years. This is enough to distinguish it from most sibling calculators, though it lacks an explicit action verb like 'calcula' and does not name a competing 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?

The legal citation and the specific financial concepts imply it should be used for over-indebtedness calculations, but there is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling tools are mentioned. The intended context is reasonably inferable but not 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?

Annotations already declare readOnly and idempotent, and the description adds valuable behavioral rules: concurrent bonds are counted once, special activity is converted to common using EC 103/2019 factors only up to 13/11/2019, and it returns both total time and attainment of the old-age threshold. This goes well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two dense sentences carry the full purpose, key algorithm rules, legal cutoff, and output summary. There is no filler, and the most identifying information is front-loaded.

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

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

For a no-output-schema, read-only calculation tool with moderately complex rules, the description covers the core inputs, the main calculation nuance (concomitance and special conversion cutoff), and the return value. It could be more explicit about input date formats or exact conversion factors, but nothing essential to choosing or invoking it is missing.

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

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

Schema description coverage is 0%, so the description must compensate. It does clarify the meaning of 'vinculos' (employment bonds to sum), the role of 'sexo' via the 35H/30M thresholds, and the notion of special activity conversion tied to the tipo values. It does not spell out date formats or enumerate each enum value, but it gives the essential semantics.

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

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

The description clearly names the resource ('Tempo de contribuição (CNIS)') and states a specific computation: summing employment bonds, counting concurrent periods once, and converting special activity into ordinary time. It also states the output (total time and whether the old-time threshold 35H/30M is reached), which fully distinguishes it from sibling tools like calculo_rmi or calculo_pensao.

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 context of use is implied: it is for calculating contribution time from CNIS records, not for calculating benefits or other legal indices. However, it does not explicitly name alternatives or state when not to use this tool versus the many sibling 'calculo_*' tools.

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

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds valuable behavioral detail by disclosing INSS/IRRF deductions using 2026 tables and the exemption of indemnity-only amounts, which an agent would not otherwise know. It does not contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two tight sentences front-load the scope and then add the tax-exemption nuance; there is no filler or repetition. It packs many components efficiently without becoming unwieldy.

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 gives a good high-level model of the calculation and its expected outputs, but with nine parameters, two enums, and no output schema, an agent will still be guessing about how motivo changes the calculation and what projetar_aviso and saldo_fgts mean. This is adequate but has clear gaps, so a 3 is appropriate.

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

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

With 0% schema description coverage, the description must compensate; it names several calculation components that map onto inputs such as salario, aviso, ferias_vencidas, and saldo_fgts. However, it never explains the key motivo enum or optional parameters like projetar_aviso and dependentes, and it does not clarify how the 40%/20% FGTS penalty relates to motivo. Thus it only partially compensates for the schema's silence.

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

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

The description clearly identifies the tool as the CLT termination-payout calculation, enumerating concrete components such as salary balance, prior-notice indemnity, proportional 13th, vacation, FGTS penalty, and INSS/IRRF deductions. It is far more specific than a tautology and can be distinguished from siblings like calculo_fgts or calculo_revisional, though it never names an alternative. Because it lacks an explicit verb and direct sibling differentiation, it falls just 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 domain label 'Verbas rescisórias / liquidação trabalhista (CLT)' gives clear context for when the tool is appropriate: computing Brazilian labor severance payouts. It does not state when not to use it or mention alternative tools, such as using calculo_fgts for standalone FGTS calculations. This is clear context without exclusions, matching a 4.

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

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

The description adds significant behavioral context beyond the annotations: it explains the conditional response when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (returns connect_url and per-install URLs). This transparently describes what the tool returns in different states, which is exactly what an agent needs. Annotations are consistent, with no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is concise, front-loaded with the main purpose, and every sentence earns its place by explaining key behavioral branches. There is no fluff or repetition of structural 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 parameterless status tool with annotations covering the read-only and non-destructive nature, the description is almost complete. It clearly explains the two main scenarios and their return fields. A small gap is that it doesn't explicitly describe partial credential scenarios, but 'pending[]' and per-install URLs imply this sufficiently for an agent to form correct 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?

This tool has zero parameters, so the baseline is 4. The description doesn't need to add parameter-level detail because the schema is empty and there is nothing to document. No missing semantic information could cause misuse of parameters.

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 ('Returns') and resource ('connection status and URLs'), and clearly conveys that this is a status-checking tool. However, it does not explicitly differentiate itself from sibling tools like 'authenticate', so it earns 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 description implies usage for checking connection status and provides conditional outcomes, but it never explicitly says when to use this tool versus 'authenticate' or any other alternative. No exclusions or routing guidance is given, so the usage guidance is only implied.

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

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

The description discloses key behavioral traits beyond annotations: invoke runs tools even when not installed, without bloating the tool list; it returns connect links for missing credentials and checkout/top-up links for empty wallets; writes require workspace owner/admin. It also explains that search/describe flag installation status (installed_in_toolkit vs installed_in_workspace). These are critical behavioral details that the annotations (readOnlyHint=false, openWorldHint=true) do not cover, and there is no contradiction with the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is long but information-dense, with a logical structure: core flow, key caveats (invoke behavior, auth/payment links), usage guidance, and prompt library. It front-loads the primary purpose and the most critical operational detail (invoke works without installation). While a few sentences are packed, they all add value; the length is justified by the tool's complexity and 0% schema coverage. It is not repetitive or bloated.

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

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

Given the tool's complexity (23 parameters, no output schema, no schema descriptions), the description is remarkably complete: it covers the main use cases, the action flows, permission requirements, error-recovery scenarios (connect/checkout links), and the prompt library sub-features. It also explains the distinction between permanent installation and one-off invocation, which is crucial for correct usage. No obvious gaps remain for an agent to select and invoke the tool correctly.

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

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

Schema description coverage is 0%, so the description carries the full burden, and it does well: it explains the 'action' enum categories (search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and prompt functions) and their purpose. It also explains the core flow parameters (query, mcp_id, tool_id, arguments) implicitly, though it doesn't detail exact types or defaults. Given the large parameter count (23) and 0% coverage, the description provides essential meaning for the most important parameters, but some parameters like 'tier_slug', 'immediate', 'conversation', and 'prompt_targets' are not explained.

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

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

The description clearly identifies the marketplace as the in-platform catalog and execution mechanism for MCPs, covering capability requests and the core search-describe-invoke flow. It explicitly distinguishes the tool from siblings by naming list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library functions with their specific roles. The verb 'discovers', 'returns', 'runs', and 'lists' are specific to actions, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance: use 'invoke' for one-off runs even when the MCP is not installed, use 'install' only for permanent toolkit additions, and prefer invoke for single/occasional use. It also clarifies when to use subscribe/cancel, report_bug, request_mcp, and the prompt library functions. Exclusions and alternatives are named, such as 'prefer invoke for a single/occasional use' versus 'install only to make an MCP PERMANENT'.

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

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

Annotations already convey that the tool is not read-only, not destructive, and idempotent. The description adds a meaningful behavioral instruction: include the conversation array for reproduction. It does not detail side effects or what happens after submission, but with annotation coverage this is acceptable.

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 conveys the core purpose and the key reproduction instruction without waste. Every word earns its place.

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

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

For a simple three-string-parameter tool, the description covers the main purpose and one important usage detail, but it omits parameter-level guidance for message and context. There is also no output schema, and the return behavior is not addressed, leaving a moderate completeness 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%, so the description must explain the parameters. It only mentions the conversation array; the required message parameter is implied but never explicitly described, and the context parameter is entirely unaddressed. This leaves the agent guessing about two of three parameters.

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: "Report a bug, missing feature, or send feedback." This clearly distinguishes report_bug from the many calculo_* calculator siblings and other utility tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage contexts: bug reports, missing features, and general feedback. It does not name alternatives or exclusions, but no sibling tool appears to compete for this purpose, so the context is clear enough.

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

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

The description is consistent with the annotations: read-only, idempotent, and non-destructive. It adds a little specificity by saying the report covers both platform and adapter versions, but it does not describe output format, potential errors, or other behavioral details. The annotations already cover the core safety profile, so this is adequate but not rich.

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 sentence that says exactly what the tool does with no filler or redundant information. It is front-loaded and every word adds meaning.

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

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

For a zero-parameter, read-only version reporting tool, the description is complete. There are no prerequisites, side effects, or input concerns to disclose, and the annotations already confirm the safe read-only nature of the operation.

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

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

The input schema has zero parameters, so there is nothing for the description to explain. A baseline of 4 is appropriate because no parameter ambiguity exists and the description does not need to compensate for schema gaps.

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 ('Show') and a clear resource ('current MCP platform and adapter versions'), making the tool's purpose immediately understandable. It also distinguishes this from the calculation, authentication, and marketplace sibling tools, which have visibly different purposes.

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 intended use is clear: obtain the current MCP platform and adapter version information. There is no explicit mention of alternatives or exclusions, but the tool is simple enough that the use case is self-evident from the 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful context about what information is returned (MCPs, statuses, accounts, tool counts), but does not disclose details like whether the state is live or cached. This is acceptable but not exceptional.

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, well-structured sentence conveys the full purpose and enumerates the key result components. There is no wasted wording or redundancy with the annotations.

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 parameterless read-only status tool with no output schema, the description covers all necessary information: what is returned, the scope (toolkit state), and the specific categories of data. An agent can decide to call it correctly without additional context.

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

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

The tool has zero parameters and the input schema is empty, so there is nothing for the description to explain. Per the baseline for 0-parameter tools, this receives a 4; the description's focus on the return value is appropriate.

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

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

The description uses a specific verb ('Returns') and identifies the exact resource ('current toolkit state') with concrete details: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from the sibling calculator and authentication tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when an agent needs an overview of the toolkit's current state, but it does not explicitly state when to use this over alternatives or mention any exclusions. Since there are no similar sibling tools, the usage context is reasonably clear without being fully explicit.

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