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

With no annotations, the description carries the full behavioral burden and does not meet it. It conveys that this is an append action on an incident timeline, but says nothing about whether the incident must exist or be in a particular state, what permissions are required, whether entries are immutable once posted, or what a successful response contains (the output schema covers returns, but the mutation semantics are undisclosed).

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 no padding beyond the numeric prefix "85.", which is an artifact rather than information. It is efficient but very thin for a mutation tool with two required params.

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 write operation with zero annotations and 0% schema coverage, the description leaves out preconditions, side effects, and payload expectations. The existence of an output schema relieves it of explaining return values, but the operational context an agent needs before calling it is largely 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, and it only partly does: "notas, ações ou comentários" loosely characterizes the mensagem payload as free-form text and "de um incidente" implies incidente_id. Neither parameter's format (IDs, length limits, markdown support) is clarified.

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 ("Adicionar") and a specific resource ("notas, ações ou comentários na linha do tempo de um incidente"), which distinguishes it from the read-only timeline generator in the sibling list. It does not explicitly name any sibling or state exclusions, so it falls short of a 5.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as grafana_atualizar_incidente (which likely changes incident fields) versus this tool (which appends timeline entries). An agent must infer the usage context entirely from the phrase "linha do tempo".

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 panel is appended or replaces something, whether the mutation is reversible, what permissions are needed, or how the query/datasource defaults are resolved — all critical for a write operation on a live dashboard.

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 sized and front-loaded, but the '13.' list-number prefix is a formatting artifact that adds nothing, and the extreme brevity is under-specification rather than efficiency for a 7-parameter mutation tool.

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 a write operation with 7 parameters, zero schema descriptions, and no annotations, the description is far too thin. An output schema exists so return values need not be explained, but the agent still lacks everything needed to populate the panel 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% across 7 parameters, and the description mentions none of them. It only obliquely implies uid_dashboard and titulo; the five remaining parameters (tipo, unidade, consulta, datasource_uid, datasource_tipo) and their defaults are entirely undocumented anywhere.

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

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

The description states a specific verb and resource ('Adicionar um novo painel a um dashboard existente'), so an agent can immediately tell this creates a panel rather than updating or removing one. It does not name the adjacent siblings (grafana_atualizar_painel, grafana_remover_painel) explicitly, and the leading '13.' numbering is noise rather than clarification.

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

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

There is no statement of when to use this versus grafana_atualizar_painel, grafana_configurar_visualizacao, or grafana_gerar_dashboard_por_prompt, nor any prerequisite such as the dashboard UID needing to exist. The 'dashboard existente' phrase only weakly implies a precondition; everything else must be 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 burden of behavioral disclosure. It does not state whether the tool is read-only, what permissions are required, what data it accesses, or what the analysis involves beyond the high-level purpose.

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 and front-loads the core purpose, but it begins with an extraneous number ('89.') that adds noise. Apart from that, it is efficient with no redundant wording.

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

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

Given the absence of annotations, 0% schema description coverage, and only one required parameter, the description is too minimal. While an output schema exists and return values need not be explained, the lack of parameter details, usage guidance, and behavioral context leaves significant gaps for correct invocation.

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

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

Schema description coverage is 0%, so the description should explain the parameters. It implicitly links 'SLO' to the required 'slo_id_ou_nome' but does not clarify that it accepts an ID or name, and it entirely omits the 'periodo' parameter (default '30d') and its 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 states a specific verb ('analisar') and resource ('queima de orçamento de erro' / error budget burn rate) plus risk of SLO violation. It is clear enough to distinguish the tool's purpose, but it doesn't explicitly differentiate it from sibling tools like grafana_consultar_slos.

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 alternatives (e.g., grafana_consultar_slos). The description only states what it does, leaving the agent to infer appropriate contexts without exclusions or prerequisites.

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

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

No annotations are supplied, so the description carries the full burden. It does not disclose that this is a read-only operation, whether it requires a live datasource, or how trends are computed over the interval. With an output schema present, return shape is covered, but operational behavior is not.

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, but it begins with a leftover ordinal prefix ('39.') that carries no meaning and wastes the most salient position.

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 3-parameter analysis tool with no annotations and zero schema documentation, the description leaves the agent without parameter syntax, prerequisites, or scope. The output schema covers the return side, but the invocation side is under-specified.

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 three parameters, and the description does not clarify that 'consulta' is a query expression, what form 'datasource_uid' takes, or the time syntax accepted by 'intervalo'. Only a loose hint ('de uma métrica') connects to the query 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?

States a specific verb (analisar) and resource (tendências estatísticas de uma métrica) plus the three trend directions it classifies. An agent can tell it apart from mutation siblings, though it never explicitly contrasts with grafana_comparar_metricas_periodos or grafana_detectar_anomalias_metricas.

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 other analysis tools in the sibling list (comparar_metricas_periodos, detectar_anomalias_metricas, executar_consulta). The agent must infer selection from name alone.

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

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

No annotations are provided, so the description carries the full behavioral burden. It implies a mutation of an existing object but says nothing about whether the supplied definition replaces the dashboard wholesale, what happens to fields not supplied, whether a commit message or version history is required, or what permissions/irreversibility apply.

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

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

One short sentence, so there is no wasted prose, but the leading '6.' is a leftover list-numbering artifact that adds noise, and the terseness comes at the cost of missing information rather than being efficient.

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

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

The tool is a mutation with a nested object parameter, four parameters, no annotations, and no schema descriptions; an output schema exists, so return values need not be explained. The description does not cover the destructive-overwrite semantics, folder targeting, or commit-message behavior that an agent needs before invoking it.

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

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

Schema description coverage is 0% across four parameters, including a nested free-form 'dashboard' object. The phrase 'a definição de um dashboard existente' loosely hints that the 'dashboard' parameter carries the new definition, but pasta_id, pasta_uid, and mensagem_commit are left entirely unexplained in both schema and description.

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

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

States a specific verb and resource: updating the definition of an existing dashboard, in Portuguese. An agent can tell it is a dashboard-mutation tool. However, it does not differentiate itself from nearby siblings such as grafana_atualizar_painel, grafana_criar_dashboard, or grafana_mover_dashboard.

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

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

The only implied guidance is that the dashboard must already exist. There is no explicit statement of when to use this versus grafana_criar_dashboard or grafana_atualizar_painel, and no prerequisites such as permissions or validation steps are mentioned.

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 and falls well short: it doesn't say whether omitted parameters leave existing values untouched (partial update) or reset them to defaults, whether secure fields like passwords can be changed, whether dashboards using the data source are affected, or what permissions are needed. "configurações permitidas" gestures at restrictions without saying what they are.

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

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

One short sentence keeps it front-loaded with no filler, but the brevity comes at the cost of substance, and the stray "24." prefix wastes the first tokens. The result is under-specification rather than genuine efficiency.

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

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

For a mutation tool with 5 parameters, 0% schema coverage, and no annotations, this description is not complete enough for safe invocation; the output schema does cover return values, so that omission is acceptable. The agent still has to guess at update semantics, field meaning, and restrictions.

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

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

Schema description coverage is 0% across 5 parameters, so the schema offers no field documentation and the description must compensate, which it largely does not. The generic phrase "propriedades e configurações" only loosely maps to the property fields (nome, url, padrao) and the free-form dados_adicionais bag; uid, the sole required parameter, is never 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 pairs a specific verb ("Atualizar") with a specific resource ("fonte de dados existente"), which is clearly distinct from criar/excluir/obter/listar siblings. However, it never names those alternatives or narrows which properties are in scope, so differentiation relies on the tool name rather than the text. The leading "24." is a stray numbering artifact, not content.

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

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

There is no explicit guidance on when to use this versus grafana_criar_fonte_dados or grafana_excluir_fonte_dados, nor any prerequisite or exclusion. The word "existente" is the only hint that the target must already exist, which an agent must infer. This is implicit-only usage guidance with clear gaps.

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 disclosure burden for a mutation tool. It never says whether the status change triggers notifications/on-call pages, whether it requires the incident to be in a particular state, whether it is idempotent, or what happens to the optional 'resumo' field — significant gaps for a state-changing operation.

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 compact sentence with no wasted clauses, and the actionable content is front-loaded. The stray '84.' prefix is a formatting defect that does not belong in agent-facing text and slightly hurts 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?

For a 3-parameter mutation tool with zero annotation coverage and zero schema description coverage, the description is too thin. An output schema exists, so return values need not be explained, but the missing side-effect disclosure and the undocumented 'resumo' parameter leave real 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% across 3 parameters, so the description must compensate. It only partially does so: the example status strings document the 'status' field's expected vocabulary, but 'incidente_id' (the sole required param) and 'resumo' receive no explanation of format or purpose anywhere.

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

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

The description states a clear verb+resource ('Atualizar status de incidente operacional') and enumerates example status values, so an agent immediately knows this changes incident state. It does not, however, distinguish itself from nearby siblings like grafana_adicionar_atividade_incidente or grafana_obter_incidente, and the leading '84.' is a numbering artifact that adds noise.

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 example statuses ('investigating', 'mitigated', 'resolved'), which signal the intended lifecycle-update scenario. There is no explicit statement of when to prefer this over grafana_adicionar_atividade_incidente or grafana_gerar_resumo_pos_incidente, and no prerequisites or exclusions are given.

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

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

No annotations are provided, so the description carries the full burden. It never says whether omitted/null fields leave existing values untouched (partial update), whether the operation is destructive to existing panel config, what permissions are required, or how failures are reported. For a mutation tool with zero annotation coverage this is a meaningful gap.

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

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

It is a single efficient sentence, but the leading '14.' is a stray numbering artifact that adds no value, and the sentence is not structured to front-load the when/why before the field list.

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?

An output schema exists so return values needn't be described, but for a 6-parameter mutation tool with no annotations the description omits update semantics, required-context prerequisites, and any routing advice, leaving an agent underspecified for correct invocation.

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

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

With 0% schema description coverage, the description partially compensates by naming four of the six parameters (título, tipo, consulta, unidade) as the updatable properties. However, it says nothing about the required identifiers uid_dashboard/id_painel or about the meaning of a null default, leaving half the parameter surface unexplained.

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

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

States a specific verb ('Atualizar') and resource ('painel específico') and enumerates the affected properties (título, tipo, consulta, unidade), so the agent knows it mutates an existing panel. It doesn't distinguish itself from nearby siblings like grafana_configurar_visualizacao or grafana_gerenciar_consultas_painel, which also touch panel configuration.

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 indication of when to use this versus grafana_adicionar_painel, grafana_configurar_visualizacao or grafana_gerenciar_consultas_painel, and no prerequisites (e.g. panel must already exist, requires dashboard UID). The only implied usage is the enumeration of properties.

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 says 'update' but not whether the change is reversible, whether permissions are required, whether unspecified properties are preserved, or what happens on a missing folder. For a mutation tool with zero annotation coverage this is a significant gap.

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

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

A single short sentence keeps it tight, but the leading '63.' is leftover numbering noise that adds no value and slightly degrades front-loading.

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?

An output schema exists so return values need not be explained, but with no annotations, 0% parameter documentation, and an unsupported 'propriedades' claim, the definition leaves an agent without enough to call it correctly in edge cases.

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

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

Schema description coverage is 0%, so the description must compensate and does not. It implies a title parameter but never explains that 'uid' identifies the target folder or that it is required and immutable, and never clarifies the 'novo_titulo' semantics beyond 'title'.

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 (Atualizar) and resource (pasta existente) plus the fields touched (título/propriedades), which distinguishes it from criar_pasta and excluir_pasta by name. However, 'propriedades' is not backed by any schema parameter, so the stated scope overreaches the actual capability.

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 grafana_criar_pasta or grafana_mover_dashboard, no prerequisites such as needing the folder's uid to exist, and no note about what happens if the uid is invalid. Usage must be inferred entirely from the name.

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

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

No annotations are provided, so the description carries the full burden. It states that properties, expressions, limits and annotations can be updated but never says whether 'regra_payload' is a full replacement or a partial merge, what happens to omitted fields, or what permissions/irreversibility apply to this mutation. The leading '54.' is an unexplained numbering artifact.

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 sentence itself is tight and front-loads the verb, but it is prefixed with a stray '54.' that adds no meaning and wastes the most salient position. Otherwise no filler.

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

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

For a mutation tool with no annotations, a completely undocumented nested payload object, and 0% parameter coverage, the single sentence is far too thin. An output schema exists so return values need not be explained, but the agent still lacks the payload contract and any safety or replacement semantics.

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 two parameters are undocumented in the schema; 'regra_payload' is a free-form object with additionalProperties:true and no structure hints. The description's mention of properties, expressions, limits and annotations gives only a loose hint at payload contents, leaving the required shape of the nested object unexplained.

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

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

The description gives a clear verb ('Atualizar') and resource ('uma regra de alerta') and even enumerates the aspects that can be changed (propriedades, expressões, limites, anotações). It does not explicitly distinguish itself from siblings like grafana_criar_regra_alerta or grafana_excluir_regra_alerta, though the verb makes the intent fairly obvious.

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

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

There is no statement of when to use this tool versus grafana_criar_regra_alerta, grafana_obter_regra_alerta, or grafana_excluir_regra_alerta, and no prerequisites such as needing an existing rule UID or prior retrieval of the rule. Usage is only implied by the word 'Atualizar'.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a read-oriented audit but does not explicitly state whether the operation is read-only, what permissions are required, what scope is covered, or whether any state is modified.

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

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

The description is a single efficient sentence that front-loads the action and resource. The leading '99.' appears to be a numbering artifact rather than meaningful content, which is a minor structural flaw.

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

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

The description is adequate for a zero-parameter tool with an output schema, since return-value details need not be repeated. However, without annotations it should say more about the audit's read-only nature, scope, or expected operational context to be fully complete.

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

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

The tool has zero parameters and schema description coverage is 100%, so the parameter-semantics baseline is 4. There are no parameters whose meaning needs to be explained in the description.

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

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

The description states a specific verb ('Executar auditoria') and resource ('segurança, conformidade e boas práticas na instância Grafana'). It clearly identifies a distinct audit operation, though it does not explicitly contrast itself with sibling diagnostic tools such as grafana_diagnosticar_alertas or grafana_obter_informacoes_instancia.

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

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

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no conditions or exclusions. An agent must infer usage solely from the stated purpose.

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

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

No annotations exist, so the description carries the full burden, yet it doesn't say this is a read-only query, what happens with an invalid datasource or query, whether the two periods must be non-overlapping, or how the comparison is expressed. An output schema exists, which relieves it of describing return values, but the operational behavior is unstated.

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

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

A single front-loaded sentence with no padding, but it opens with a stray '38.' enumeration artifact and the brevity reflects under-specification rather than disciplined economy. Adequate, not tight.

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 presence of an output schema covers the return-value side, but for a 6-parameter analytical tool with zero schema coverage and no annotations, the description leaves the agent without parameter formats or behavioral guardrails. It is not sufficient to call the tool confidently without inspecting the schema.

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

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

Schema description coverage is 0% across six parameters, so the description must compensate and largely does not. The phrase 'dois períodos temporais distintos' hints that the four periodo_* parameters form the two comparison windows, but nothing is said about 'consulta' syntax or the datasource_uid, and the relative-time format is only inferable from defaults like 'now-1h'.

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 ('Comparar') and resource ('o comportamento de uma métrica') plus the comparison axis (two distinct time periods), so the operation is unambiguous. It does not differentiate itself from near-neighbors such as grafana_analisar_tendencias_metricas or grafana_detectar_anomalias_metricas, which keeps it out of 5 territory.

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 pick this over the many sibling query/analysis tools, no prerequisites (e.g., a valid datasource_uid or a query language), and no exclusions. The agent must infer usage purely from the one-line purpose.

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 disclosure burden, and it does not say whether this is a read-only operation, what form the comparison takes, or whether both traces must belong to the same service/datasource. The presence of an output schema offsets some of this, but the behavioral profile of a comparison operation is left essentially unexplained.

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

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

A single front-loaded sentence with no padding in the body. The leading '45.' is an artifact from a list and is pure noise, but otherwise the sentence is tight.

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?

Return values are covered by the output schema, so that is not a gap. But for a 3-parameter comparison tool with no annotations and 0% schema coverage, the description provides almost none of the context needed to call it correctly — notably what datasource_uid does and what the two traces must have in common.

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

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

Schema description coverage is 0% and the description only implies that two trace identifiers are needed ('dois traces'), adding no format, source, or constraint details. The third parameter, datasource_uid, is completely undocumented in both the schema and the description.

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

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

States a specific verb (comparar) and specific resource (dois traces distribuídos), plus a concrete example use case (fast execution vs slow erroring execution). It does not, however, distinguish itself from nearby siblings like grafana_obter_detalhes_trace or grafana_correlacionar_logs_metricas_traces, so the agent must infer the boundary.

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

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

The parenthetical example ('execução rápida vs execução lenta com erro') implies the scenario where this tool is useful, which is a genuine usage hint. There is no explicit when-not-to-use guidance and no named alternative for single-trace inspection.

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

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

No annotations are supplied, so the description carries the full behavioral burden and does not meet it. It never says whether existing thresholds are replaced or merged, what passing null (the schema default for unidade and thresholds_steps) does, or whether the change requires write permissions on the dashboard.

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 is appropriately sized, but it opens with a stray list marker '18.' that is noise and it is not structured (no separated statement of effect versus inputs). No wasted clauses beyond the numbering artifact.

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?

An output schema exists, so return values need no explanation, but for a 4-parameter mutation with zero schema descriptions and no annotations the description is thin. The agent still lacks the shape of thresholds_steps, the semantics of null/defaults, and the effect on pre-existing color configuration.

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

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

Schema description coverage is 0%, so the description must compensate and largely fails. It names 'unidade' and 'limiares' but gives no format for thresholds_steps (an untyped array of arbitrary objects), and it advertises an 'escala de cores' capability that has no corresponding parameter, leaving the mapping between prose and schema unclear.

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 concrete verb ('Configurar') and concrete resources (unidade de medida, thresholds, escala de cores) scoped to 'um painel', so the agent knows this is a panel-styling mutation. It does not, however, distinguish itself from nearby siblings such as grafana_configurar_visualizacao or grafana_atualizar_painel, leaving overlap for the agent to resolve.

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 statement of when to use this instead of grafana_configurar_visualizacao, grafana_atualizar_painel, or grafana_adicionar_painel. There are no prerequisites either (e.g. whether the panel must already exist or whether the dashboard must be in a specific state).

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 but only implies a mutation. It does not say whether existing visualization options are replaced or merged, whether permissions on the dashboard are required, or what the response contains. Only the enumeration of visualization types adds real behavioral signal.

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

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

One sentence, front-loaded with the action and resource, with zero filler. The only defect is the stray list numbering ('17.') that adds nothing and slightly obscures the opening verb.

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

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

For a mutation tool with no annotations, an opaque 'opcoes' object parameter, and an output schema the caller must interpret, the description is too thin. It never explains what shape opcoes takes or how the tool interacts with the panel's existing state, which an agent would need before invoking it.

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

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

Schema coverage is 0% across four parameters, so the description must compensate. It does partially by effectively enumerating accepted tipo_visualizacao values, which the schema lacks as an enum, but says nothing about uid_dashboard, id_painel, or the free-form 'opcoes' object, which is the most important and least constrained 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?

States a specific verb and resource in Portuguese: configuring a panel's visualization type and visual options, with example types (line, bar, stat, gauge, table). The purpose is unmistakable, but nothing distinguishes it from overlapping siblings such as grafana_atualizar_painel or grafana_configurar_limites_cores, and the leading '17.' is stray numbering noise.

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 instead of grafana_atualizar_painel, grafana_adicionar_painel, or grafana_configurar_limites_cores, which all plausibly touch the same panel. It also omits prerequisites such as whether the dashboard and panel must already 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?

No annotations are provided, so the description carries the full burden. It does disclose one meaningful behavioral constraint — only SELECT statements are accepted — which is useful safety context for a SQL-execution tool. However, it says nothing about permissions required, row/timeout limits, whether the query is rejected or rewritten on violation, or error behavior.

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

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

A single front-loaded sentence with the core constraint early and no wasted clauses. The leading '36.' is a numbering artifact that adds no 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?

An output schema exists, so return values need not be explained, and the supported engines plus SELECT restriction cover the essentials of what the tool does. But with zero parameter documentation and no annotations, the definition leaves an agent guessing about argument format and execution limits.

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 neither of the two required parameters is documented. The description only indirectly hints that sql_query is a SELECT statement and that datasource_uid identifies a relational datasource; it adds no syntax, format, or constraint details beyond that.

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

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

States a specific verb (executar) and resource (consultas SQL) plus the supported engines (Postgres, MySQL, MSSQL) and the SELECT-only restriction. This lets an agent distinguish it from the Prometheus/Loki/InfluxDB query siblings without opening a schema, though it never names those alternatives explicitly.

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

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

There is no when-to-use or when-not-to-use guidance. The 'estritamente SELECT' parenthetical implies a read-only query scenario, but nothing tells the agent how this differs from grafana_executar_consulta or the engine-specific consultar_* 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?

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only query but does not disclose permissions, pagination, freshness of the queue data, or any other behavioral trait beyond the basic purpose.

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 and is not bloated. However, the leading '87.' is extraneous metadata that does not help an agent and slightly reduces front-loaded clarity.

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

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

For a zero-parameter read tool with an output schema, the description is minimally sufficient to identify the action. It still leaves behavioral context such as queue semantics or permission requirements undefined, which is a notable gap without annotations.

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

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

The tool has zero parameters, so there are no parameter semantics to document. The baseline of 4 applies for a parameterless 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 uses a clear verb ('Consultar') and a specific resource ('grupos de alertas ativos na fila do Grafana OnCall'). It is distinguishable from the dashboard-oriented siblings, though no sibling alternative is named.

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 only states what the tool does, with no explicit guidance on when to use it versus alternatives or what context is required. The implied use case is visible from the name, but no exclusions or prerequisites are provided.

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

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

No annotations exist, so the description carries the full burden. 'Consultar' implies a read operation, and 'através do proxy do Grafana' adds a bit of architectural context, but nothing is said about permissions, whether the datasource must exist, rate/size limits on queries, or pagination. An output schema exists, so return formatting need not be covered, but the operational behavior remains undeclared.

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

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

A single front-loaded sentence with no padding. The leading '35.' ordering artifact is noise that does not serve the agent, but the sentence itself is efficient.

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 query-execution tool with zero annotation coverage and 0% schema description coverage across four parameters, one sentence is insufficient. The agent is left to guess the datasource_uid sourcing and the accepted time-range syntax, which are the main failure modes for this call.

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

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

Schema coverage is 0% and four parameters are undocumented. The description only hints that 'consulta' should be a Flux or InfluxQL query; it says nothing about 'datasource_uid' (how to obtain a valid one), 'de'/'ate' (defaults now-1h/now are visible in schema but the accepted time-expression format is 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?

States a specific verb (Consultar) and resource (métricas no InfluxDB) and even names the two supported query languages (Flux or InfluxQL) plus the access path (proxy do Grafana). It implicitly separates itself from influxdb-adjacent siblings like grafana_consultar_prometheus/loki, but never names them explicitly.

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

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

There is no statement of when to use this tool versus grafana_executar_consulta, grafana_consultar_prometheus, or grafana_consultar_fonte_sql. The InfluxDB reference implies the context, but no alternatives, prerequisites, or exclusions are given.

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

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

No annotations are provided, so the description carries the full disclosure burden, and it only implies a read-only query. It says nothing about default time windows (now-1h to now), the 100-row default limit, whether results are capped server-side, or whether a datasource_uid is required to disambiguate when several Loki sources exist.

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 efficient sentence, but the leading '33.' artifact is noise that reads like a truncated list item rather than tool documentation. It is front-loaded with the action, which is good, but the stray numbering hurts a text meant to be parsed by an agent.

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

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

An output schema exists, so return-value explanation is not strictly required, but the combination of 5 params at 0% schema coverage and zero annotations leaves the definition incomplete. An agent cannot tell how to format de/ate, what limite affects, or whether datasource_uid is needed when multiple Loki sources are configured.

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 five parameters exist, so the description must compensate; it mentions only the LogQL query itself. The Portuguese time-range params (de/ate), limite, and datasource_uid receive no explanation of accepted formats or defaults, leaving four of five params undocumented anywhere.

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

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

The description states a specific verb ('Executar consulta LogQL') and resource ('fluxos de logs no Grafana Loki'), so an agent immediately understands it runs LogQL against Loki. It does not name the sibling it differs from, notably grafana_pesquisar_logs or grafana_consultar_prometheus, so the LogQL-vs-generic-log-search boundary is left implicit.

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

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

There is no guidance on when to use this instead of grafana_pesquisar_logs, grafana_executar_consulta or the other datasource-specific query tools in the sibling list. No prerequisites, no note that a LogQL string is mandatory and other params are optional, and no exclusions are given.

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

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

No annotations are provided, so the description carries the full behavioral burden. It conveys only that this is a read of ACL entries; it does not say whether admin permissions are required, whether inheritance from parent folders is included, or what happens if the resource has no explicit ACL. An output schema exists, which excuses return-value detail, but the access/auth behavior remains undisclosed.

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; the only waste is the leading ordinal '96.' which is an artifact of an external list rather than tool documentation.

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

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

For a tool with two completely undocumented parameters and zero annotations, the description does not provide enough to call it correctly without guessing valid values for tipo_recurso and the ID format. The existing output schema covers return values, but request-side completeness 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?

Both required parameters have 0% schema description coverage, so the description must compensate and largely does not. The mention of 'dashboard ou pasta' loosely maps to tipo_recurso, but no allowed values, ID format, or distinction between numeric dashboard IDs and folder UIDs is given.

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 (consultar) and resource (permissões ACL) scoped to a dashboard or folder, which distinguishes it from the mutating siblings grafana_gerenciar_permissoes_dashboard/pasta. It does not explicitly name those siblings, so the distinction relies on the agent inferring that 'consultar' is read-only versus 'gerenciar'.

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 statement of when to use this versus the two permission-management siblings, nor any prerequisite (e.g. admin rights needed to read ACLs). Usage is only implied by the verb 'consultar'.

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 says nothing about whether the call is read-only, what permissions or datasource_uid resolution rules apply, timeouts, or result-size limits. It adds no context beyond the tool name.

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 clauses, but it opens with a stray '32.' list-numbering artifact and is terse to the point of being under-specified rather than concise.

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 5-parameter, unannotated query tool, the description leaves the agent without enough to call it correctly: how to switch between instant and range mode, what datasource_uid does when null, and what range/step defaults mean. The output schema covers return values, but the input side is severely under-described.

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

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

Schema description coverage is 0% across 5 parameters, so the description must compensate and does not: de/ate (time range with defaults now-1h and now), passo_segundos (step), and datasource_uid (datasource selection vs default) are never explained. Only the promql parameter is implicitly covered by 'consulta PromQL'.

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?

Specific verb + resource: executes a PromQL query against a Prometheus datasource, with the instant/range distinction stated. It is clearly not a Loki, Tempo, or InfluxDB query, but it does not explicitly position itself against the generic sibling grafana_executar_consulta.

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

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

No guidance on when to choose this over grafana_executar_consulta (generic query execution) or the other backend-specific consultar_* tools, and no prerequisites or exclusions. The 'instantânea ou de intervalo' phrase hints at mode but never says which parameters select 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?

No annotations are supplied, so the description carries the full behavioral burden, and it discloses nothing beyond the topic: no statement that it is a read-only listing, no note about which Grafana SLO backend/version is queried, and no mention of behavior when no SLOs are configured. The output schema covers return values, but the operational profile remains blank.

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

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

One short sentence with no padding, so it is efficient, but the leading '88.' is pure noise and the sentence is topic-only rather than front-loaded with actionable detail. Brevity here reflects under-specification as much as discipline.

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 presence of an output schema relieves the description of explaining return values, but for a tool with an undocumented optional filter and zero annotations, the definition leaves the agent guessing about both the parameter's semantics and the call's behavior. It is not sufficient to invoke confidently without trial and error.

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

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

The single parameter 'nome_ou_tag' has 0% schema description coverage, and the description never mentions it at all — not what a name filter matches, not whether tags are exact or substring, not whether omitting it lists everything. With one undocumented parameter, the description should compensate and does not.

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 (Consultar) and resource (SLOs and configured SLI metrics), which is clear enough to distinguish it from every dashboard, alerting and query sibling in the list. The only defect is the stray '88.' ordinal prefix, which carries no meaning for an agent.

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

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

There is no guidance on when to use this instead of the alerting tools (grafana_listar_regras_alerta) or the report tools (grafana_gerar_relatorio_disponibilidade), which are the natural alternatives for SLO-adjacent questions. The agent must infer the context entirely from the tool 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?

With no annotations, the description carries the full behavioral burden and does not meet it: it says nothing about result limits, whether TraceQL queries require a time range, or how datasource_uid defaults. It does at least imply a read-only retrieval pattern via 'pesquisar e recuperar', which prevents a 1.

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 the resource and lookup modes stated immediately. The only noise is the stray list numbering prefix '34.', which is a formatting artifact rather than content.

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

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

An output schema exists, so return values needn't be explained, but for a query tool with zero annotation coverage the description should cover datasource selection and TraceQL/time-range expectations. Neither is present, leaving an agent to guess at invocation constraints.

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

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

Schema description coverage is 0%, so the description must compensate. It identifies that trace_id_ou_traceql accepts either an ID or a TraceQL expression, but says nothing about datasource_uid (what it is, the null default, or how the datasource is chosen), leaving half the parameters undocumented everywhere.

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 pair (pesquisar e recuperar) and resource (traces distribuídos no Grafana Tempo), plus the two lookup modes (por ID ou TraceQL). It is distinguishable from the dashboard/alert siblings, though the overlap with grafana_obter_detalhes_trace is not addressed.

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

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

There is no statement of when to use this tool versus grafana_obter_detalhes_trace, grafana_comparar_traces, or grafana_explorar_atributos_trace, all of which operate on traces. The 'por ID ou TraceQL' clause hints at scope but does not guide selection between siblings.

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 disclosure burden. It says what is correlated but not whether the operation is read-only, what permissions are required, expected latency, or how results are structured; an output schema exists, but mutation/safety traits remain undisclosed.

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

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

The single sentence is front-loaded and wastes little beyond the extraneous '47.' prefix. However, it is so terse that it omits useful context, making it under-specified rather than optimally concise.

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 cross-signal correlation tool with three parameters, no annotations, and no schema descriptions, the description is too thin. The existing output schema reduces the need to explain return values, but the lack of operational context leaves meaningful gaps.

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

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

Schema description coverage is 0%, and the description does not mention the parameters at all. 'De um serviço' hints at nome_servico, but janela_de and janela_ate defaults and accepted time formats are entirely undocumented in both schema and description.

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

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

The description states a specific verb ('Correlacionar') and three concrete resources (CPU/RAM metrics, error logs, traces) scoped to a service. An agent can understand what the tool does, though it does not explicitly distinguish itself from siblings such as grafana_investigar_servico or grafana_diagnosticar_degradacao.

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 alternatives like investigar_servico, diagnosticar_degradacao, or individual query tools. 'Simultaneamente' weakly implies cross-signal correlation, but no explicit conditions or exclusions are provided.

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 mostly fails it. "Validado" hints that the dashboard is validated before saving, but nothing explains what happens when a dashboard with the same name exists, how the overwrite flag affects existing content, or whether creation is reversible.

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?

Short and front-loaded, but it opens with a stray "5." numbering artifact that signals a truncated copy-paste, and the single sentence is under-specified rather than truly concise.

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 mutating tool with no annotations, five undocumented parameters, and a nested object payload, the description is nowhere near sufficient. The presence of an output schema only excuses return-value documentation, not the missing creation, folder-placement, and overwrite semantics.

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 five parameters, including a nested free-form dashboard object. The description mentions none of them — not pasta_id/pasta_uid (folder targeting), not sobrescrever (overwrite semantics), not mensagem_commit (version history) — and says nothing about the shape of the dashboard payload.

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 ("Criar um novo dashboard") in Grafana, which is enough for an agent to know this is a create operation. However, it gives no differentiation from siblings like grafana_duplicar_dashboard, grafana_gerar_dashboard_por_prompt, or grafana_atualizar_dashboard, and the wording "validado" is ambiguous about whether validation is performed implicitly.

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 contains no when-to-use guidance, no prerequisites (e.g. must the folder exist?), and no mention of alternatives for creating dashboards. The agent must infer everything from the name and the sibling list.

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 bears the full behavioral burden, yet it discloses almost nothing: not whether the data source becomes default, what happens on duplicate name, permission/auth requirements, or whether URL reachability is checked. "Com parâmetros validados" hints at validation but never explains it.

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 sentence, but the "23." prefix is dead weight and the trailing "com parâmetros validados" clause adds no information. The useful part (create a new Grafana data source) is front-loaded and clear.

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?

An output schema exists, so return values needn't be described, but for a mutation tool with zero annotations and six undocumented parameters—including a nested freeform object—the description is far too thin to let an agent 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% across 6 parameters, and the description compensates for none of it. Opaque parameters like tipo (which source types?), acesso (proxy default), padrao, and the freeform dados_adicionais object receive no explanation beyond what the bare property names imply.

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

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

It states a specific verb ("Criar") and resource ("fonte de dados no Grafana") that is distinguishable from the list/update/delete/excluir siblings by verb alone. However, the leading "23." is meaningless noise and "com parâmetros validados" is vague filler rather than scope detail.

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

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

There is no guidance on when to use this versus grafana_atualizar_fonte_dados or grafana_testar_fonte_dados, nor any prerequisites such as required admin permissions or whether to test the connection before saving. The only cue, "parâmetros validados," is not actionable.

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 not state that this is an irreversible state-changing write, whether notifications/on-call escalations are triggered, whether the creator becomes the incident commander, what permissions are required, or what the initial state is. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

One short sentence, front-loaded with the action, so nothing is padded. However, the leading "82." is leftover numbering noise that earns no place, and the brevity comes at the cost of under-specification rather than efficiency.

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?

An output schema exists, so return values needn't be described. But for a 4-parameter write tool with no annotations, no enum on severidade, and 0% schema description coverage, the single sentence leaves critical information an agent needs (valid severity values, default behavior, label format, side effects) undocumented.

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

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

Schema description coverage is 0% — every parameter has only a title. The description calls out severidade and descrição, covering half the parameters, but adds no meaning beyond the names: no allowed severity values, no note that severidade defaults to "major", no explanation of what rotulos (labels) accept, and it omits the required titulo entirely.

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

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

The verb+resource pair ("declarar um novo incidente operacional") is specific and clearly distinguishes this from siblings such as grafana_atualizar_incidente, grafana_obter_incidente and grafana_listar_incidentes. It also names the two main attributes contributed (severidade and descrição). The stray "82." numbering prefix is noise but does not obscure the purpose.

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

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

There is no explicit guidance on when to create a new incident versus when to update an existing one (grafana_atualizar_incidente) or add activity to it (grafana_adicionar_atividade_incidente), and no prerequisites, permissions or escalation/workflow context are stated. Usage is only implied by the verb "declarar".

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 says nothing about required permissions, behavior on duplicate title/UID collisions, whether UID is auto-generated when omitted, or whether the operation is idempotent — all critical for a mutation 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, but the leading '62.' is a leftover numbering artifact that adds noise and looks like a stray list marker rather than intentional content.

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

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

An output schema exists so return values need not be explained, but for an unannotated mutation tool the description should cover permissions, duplicate handling, and UID generation. None of that is present, leaving the definition thin against the tool's operational complexity.

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

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

Schema description coverage is 0%, so the description must compensate. It only restates that there is a title and an optional UID, adding no format rules, UID character constraints, or meaning of the default null beyond what the schema already shows.

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: creating a new Grafana folder, with the two inputs (title, optional UID) named. It is distinguishable from siblings like grafana_atualizar_pasta or grafana_excluir_pasta by the verb, though it never names them 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, prerequisites, or alternatives are given. There is no mention of how this differs from grafana_atualizar_pasta or what to do if a folder with the same title already exists, leaving the agent to infer everything 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?

With no annotations, the description carries the full behavioral burden, but only says 'parâmetros validados'. It does not disclose required permissions, whether the rule is activated immediately, side effects, or validation failure behavior—critical gaps for a mutation 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?

It is a single front-loaded sentence with no wasted explanation, though the leading '53.' is extraneous formatting noise.

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

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

This is a mutation tool with no annotations, a complex unspecified nested payload, and 0% schema description coverage. Although an output schema exists, the description is too thin to guide correct invocation of alert rule creation.

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

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

Schema coverage is 0% for the single required parameter 'regra_payload', which is an open nested object with additionalProperties true. The description mentions validated parameters but does not explain the payload structure, required fields, or expected shape, so it fails to compensate for the schema gap.

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

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

States a specific verb ('Criar') and resource ('nova regra de alerta no Grafana Alerting'), so an agent can tell it creates an alert rule. It does not explicitly differentiate itself from siblings like grafana_atualizar_regra_alerta, so it falls short of a 5.

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

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

The description gives no guidance on when to use this versus siblings such as grafana_atualizar_regra_alerta or grafana_listar_regras_alerta. The word 'nova' hints at creation-only semantics, but there are no explicit conditions 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?

No annotations are provided, so the description carries the full burden: it says nothing about whether this is read-only, which statistical method/parameters are applied, permission or rate-limit constraints, or how anomalies are reported. Only the bare intent ('find outliers') 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 front-loaded sentence with no wasted padding, but the leading enumeration artifact '40.' is noise and the brevity reflects under-specification rather than tight writing.

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?

An output schema exists so return values needn't be explained, but for a 3-parameter analytical tool with no annotations and zero parameter documentation, the description omits everything an agent needs to invoke it correctly: which query language/datasource is expected and what the time interval controls.

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. 'consulta', 'datasource_uid', and 'intervalo' (default now-12h) are left completely undefined in both schema and description, giving an agent no semantic guidance on query syntax or the meaning of the datasource identifier.

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 ('Identificar') and resource ('anomalias e desvios estatísticos atípicos (outliers) na telemetria'), so an agent understands the operation is anomaly detection over telemetry. It does not, however, distinguish it from adjacent siblings such as grafana_analisar_tendencias_metricas or grafana_diagnosticar_degradacao, which plausibly overlap.

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 this over trend analysis, period comparison, or degradation diagnosis, and no prerequisites or exclusions are stated. The agent must infer selection from the name alone.

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

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

No annotations at all, so the description carries the full behavioral burden and only partially meets it. It discloses valuable scope beyond a simple read (it evaluates health and surfaces flapping triggers), implying a read-only analytical operation, but never states that it is non-destructive or what systems it touches (rules, notification policies, contact points, silences).

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 dense sentence with no filler, and the diagnostic outcome (flapping triggers) is front-loaded. It loses a point for the stray leading "60." enumerator fragment, which is noise left over from a list.

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?

An output schema exists, so return-value explanation is not needed here, and the description does convey the analytical goal. However, for a zero-parameter diagnostic over a broad domain, it does not indicate which alerting components are examined (rules, contact points, silences, on-call) or how the health verdict is scoped, leaving the agent to discover coverage from the response.

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 and the baseline is 4. No parameter-related gap exists.

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?

Specific verb pair ("Investigar e diagnosticar") plus a specific resource ("saúde do ecossistema de alertas") and a named finding ("triggers com flapping"). This distinguishes it from the sibling listing tools (grafana_listar_regras_alerta, grafana_listar_instancias_alerta) and the report tools, though it never names those alternatives explicitly.

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

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

Usage is only implied by the word "diagnosticar" – an agent can infer this is for investigating alerting problems rather than listing or editing rules. There is no statement of when to prefer this over grafana_listar_instancias_alerta or grafana_gerar_relatorio_alertas, and no preconditions.

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 not disclose which telemetry sources are consulted, whether it is read-only, how long such a cross-signal diagnosis takes, or what confidence/reasoning the result carries beyond the mere existence of an output schema.

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

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

A single efficient sentence that front-loads the core action. The stray '49.' numbering prefix is noise, but nothing else is wasted.

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

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

The output schema covers return values, but for a complex cross-signal diagnostic tool with no annotations and two entirely undocumented parameters, the definition leaves too much for the agent to guess about inputs and 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%, yet the description adds nothing about the two required parameters. It does not clarify the expected format of nome_servico (service name, ID, qualified path) nor what granularity or phrasing sintoma_relatado should have, which is essential for a diagnosis 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?

States a specific verb+resource: diagnose the probable root cause of degradation from telemetry evidence. This clearly differs from sibling CRUD tools and from narrower diagnostics like grafana_diagnosticar_alertas or grafana_diagnosticar_fontes_dados, though the description does not explicitly name those distinctions.

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 instead of the closely overlapping siblings grafana_investigar_servico, grafana_correlacionar_logs_metricas_traces, or grafana_detectar_anomalias_metricas. The agent must infer the selection criteria from tool names alone.

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

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

No annotations are provided, so the description carries the full burden. It never says whether the diagnostic is read-only, whether it opens real network connections to every data source on each call, how long a fleet-wide sweep takes, or whether failures are aggregated. For a tool that fans out across all data sources, that omission matters.

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 the verb and Object placed early. The only waste is the stray '27.' ordinal prefix, which is serialization noise rather than 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?

An output schema exists, so return values need not be described, and with zero parameters the surface area is small. Still, with no annotations the description should have covered the read-only nature and the fleet-wide fan-out cost; as written it is adequate but leaves real gaps for a probing 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?

The schema has zero parameters, so there is nothing to disambiguate and the baseline of 4 applies. The description correctly implies no scoping inputs are accepted ('todas as fontes'), which matches the empty 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?

States a specific verb (diagnosticar) and resource (fontes de dados) with scope explicitly limited to 'todas as fontes cadastradas', which separates it from single-source siblings like grafana_testar_fonte_dados and grafana_obter_fonte_dados. It does not name those siblings, so differentiation is inferable rather than explicit.

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

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

The word 'todas' implies a bulk sweep across every registered data source versus a targeted check, which is useful implied guidance. However, there is no explicit statement of when to choose this over grafana_testar_fonte_dados or grafana_testar_conexao, nor any exclusions or prerequisites.

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 implies a write operation that creates a new dashboard while leaving the original intact, but says nothing about required permissions, whether the copy inherits folder/tags/permissions, or what happens when the target folder is not specified — all material for a mutating 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 sentence with no padding, but it opens with a stray list marker ("8.") that is an artifact of source documentation and adds noise to the front of the definition. The core content is efficiently delivered once past that.

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?

An output schema exists, so return values need no explanation, but the definition still leaves an agent without folder-targeting semantics, permission requirements, or a routing rule against sibling creation tools. For a three-parameter mutation with zero annotation coverage, that is a substantial gap.

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

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

Schema description coverage is 0% across three parameters, and the description only loosely gestures at two of them (uid_origem, novo_titulo). The third parameter, nova_pasta_id, and the meaning of its default value 0 (same folder as source? root folder?) are documented nowhere.

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 ("Duplicar um dashboard existente") plus the outcome (new title and UID), so an agent can tell this is a copy operation rather than a create-from-scratch one. It does not, however, explicitly differentiate itself from close siblings like grafana_criar_dashboard or grafana_gerar_dashboard_por_prompt, leaving that inference to the agent.

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

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

The only usage signal is implicit in the verb "duplicar"; there is no statement of when to prefer this over grafana_criar_dashboard or grafana_gerar_dashboard_por_prompt, and no prerequisites (e.g., source dashboard must exist, permission needed on the target folder). The agent must guess at 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?

With no annotations, the description carries the full burden and does deliver the two most important traits: the operation is destructive and gated by a two-step approval. It stops short of stating irreversibility, what dependent objects (alert rules, permissions, snapshots of panels) are affected, or how the approval token is obtained. Real value is added, but the behavioral picture is incomplete for a delete.

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

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

One compact sentence with the destructive warning front-loaded, no filler. The stray "7." prefix and the placement of the risk note in parentheses rather than up front cost it a point, but nothing is wasted.

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

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

For an irreversible delete with a two-step approval mechanism and an opaque token parameter, the description is too thin: it does not explain the approval flow, the consequences of deletion, or failure modes. An output schema exists so return values need no coverage, but the workflow an agent must execute to call this safely 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 and only partially does: "pelo UID" gives meaning to the uid parameter, but token_aprovacao is left entirely unexplained — the "aprovação em dois passos" phrase hints at it without saying what the token is, where it comes from, or whether it is required on the first call or a retry.

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 pair ("Excluir um dashboard") scoped by identifier ("pelo UID"), so an agent knows exactly what the tool does. It does not name or differentiate itself from siblings like grafana_excluir_pasta or grafana_remover_painel, and the leading "7." is a leftover list artifact, but the action itself is 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 parenthetical "Ação destrutiva - requer aprovação em dois passos" implies usage conditions: only call deliberately, and expect a two-step approval workflow. However, it never says when to prefer this over alternatives (e.g., moving a dashboard to a folder via grafana_mover_dashboard instead of deleting) or what preconditions outside the token must hold.

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 load and does disclose the two key behavioral facts: the operation is destructive and requires a two-step approval. It stops short of stating irreversibility, what dependencies break, permission requirements, or how the approval token is obtained/consumed, so transparency is partial.

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, so nothing is padded, but the '25.' prefix is wasted characters and the destructive warning is buried in parentheses rather than front-loaded. Structure is adequate but not optimized.

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

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

For a destructive, un-annotated tool with an unexplained approval-token parameter, the description does far too little: an agent cannot learn the irreversibility, the approval workflow steps, or which sibling tools are affected. The presence of an output schema covers return values, but the pre-call behavior gap remains large.

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

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

Schema description coverage is 0%, so the description must compensate and largely does not: 'uid' is never described as the data source identifier, and 'token_aprovacao' is only obliquely referenced by the 'aprovação em dois passos' phrase with no explanation of its format, source, or lifetime.

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 ('Excluir uma fonte de dados'), which cleanly distinguishes it from siblings like grafana_atualizar_fonte_dados, grafana_criar_fonte_dados and grafana_obter_fonte_dados. The leading sequence number '25.' is noise that adds no clarity, and no explicit sibling differentiation is written out.

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?

Gives useful invocation context ('Ação destrutiva - requer aprovação em dois passos'), which tells the agent the deletion cannot be completed in a single call. However, it never says when to prefer deletion over alternatives, nor what prerequisites or pre-checks (e.g. dashboards referencing the data source) should precede it.

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

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

With no annotations, the description must carry the behavioral burden. It usefully discloses two traits: the operation is destructive and it optionally cascades to dependent dashboards, plus that approval is required. However, it does not explain the approval mechanism (how to obtain token_aprovacao), reversibility, or required permissions, leaving significant gaps for a mutation 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 that gets to the verb quickly. However, the '64.' numbering prefix is pure waste, and the parenthetical warning is compact but vague.

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?

An output schema exists, so return values need not be explained. But for a destructive folder mutation with zero annotation coverage and 0% parameter documentation, the description should clarify the approval flow and cascade implications; it hints at both without making them actionable.

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 neither of the two parameters (uid, token_aprovacao) is explained in the description. The word 'aprovação' loosely gestures at token_aprovacao but never tells the agent how to obtain or supply it, and uid is undocumented entirely. The description does not compensate for the zero coverage.

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 ('Excluir uma pasta') and adds scope ('opcionalmente seus dashboards dependentes'). It is clearly distinguishable from grafana_excluir_dashboard by the folder resource, though it never names the sibling explicitly. The '64.' prefix is noise that detracts slightly.

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 parenthetical 'Ação destrutiva - requer aprovação' is a warning, not usage guidance. It does not say when to delete a folder versus moving/emptying it, nor how this relates to grafana_excluir_dashboard. No when-to-use or when-not conditions are provided.

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

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

With no annotations, the description does carry useful behavioral context: it declares the operation destructive and discloses a two-step approval requirement. However, it omits irreversibility, permission requirements, and what exactly is deleted beyond 'the rule', leaving meaningful gaps for a mutation tool.

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