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

With no annotations, the description carries the full burden and does a fair job: it discloses the verdict values, that problems come bundled with repair actions, and that the network check (MIREA sites, internet, VPN) only runs when something is wrong. It never explicitly confirms the call is read-only/no-side-effect, which for a zero-annotation tool leaves a small safety 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?

Three short sentences, front-loaded with the core question, then the return contract, then the routing rule. Every clause carries information; nothing is restated from the schema or title.

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

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

No output schema exists, so the description must describe returns itself — and it does, listing the verdict, per-problem repair actions, the current pair, and the conditional network check. With zero parameters and no annotations, this is enough for an agent to call it correctly.

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

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

The tool takes zero parameters and the description doesn't invent any, so there is no parameter semantics to explain. Baseline 4 applies for a 0-param tool with 100% schema 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 question the tool answers ("Is the app working right now?") and enumerates what the verdict contains, so the resource and output shape are clear. It doesn't name any sibling (e.g. get_status or get_recent_problems) to draw a boundary, relying instead on a positional rule ("call this first") for differentiation.

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?

"Call this first; if ok, nothing else is needed" is an explicit, actionable routing rule that tells the agent both when to invoke and when to stop. What's missing is the reverse case — which sibling to call when the verdict is "problem" — so the guidance is one-directional rather than complete.

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

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

With no annotations, the description carries the full behavioral burden, yet it only discloses recency ('Recent') and a return exclusion ('no QR contents'). It does not clarify read-only behavior, time-window definition, permissions, pagination, or what 'pairs' structurally means.

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

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

It is a single, short sentence with no filler, and the key scope ('Recent') is front-loaded. The phrasing 'the pairs where attendance was marked' is slightly awkward but not verbose.

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

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

With no output schema and no annotations, the description should explain the shape and scope of returned data, but 'pairs' and 'events' go undefined and no time window is specified. An agent would have to call it blind to understand its output.

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

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

There are zero parameters and no parameter schema to compensate for, so the baseline of 4 applies. The description correctly does not invent parameter details.

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

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

The description identifies the resource as recent QR events and attendance-marked pairs, which hints at an attendance-history read. However, it is a noun phrase with no clear verb, and terms like 'pairs' are ambiguous — an agent cannot confidently tell what records are returned or how this differs from a generic history tool.

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

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

No indication of when to call this versus any alternative, and no prerequisites or context are given. The sibling list contains no obviously related tool, but the description still offers no usage guidance.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that only four fields are returned and implies a read-only retrieval, but it does not mention ordering, time range, pagination, authentication requirements, or error behavior. For a simple read-only log tool this is adequate but incomplete.

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 resource (warnings and errors) and then enumerates the returned fields. It is terse but not cryptic, with no wasted words.

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

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

For a zero-parameter read-only tool with no output schema, the description gives enough information to understand what is returned. The only missing piece is explicit guidance on when to prefer it over related diagnostic siblings, but the core contract is 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 takes zero parameters, so there is no parameter semantics to document; the baseline for 0 params is 4. The description does not need to compensate for any schema gaps.

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

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

The description clearly states it returns the latest warnings and errors from the app log, and enumerates the exact fields (time, level, module, event name). It is specific about the resource and content, though it does not explicitly contrast itself with diagnostic siblings like check_health or get_status.

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

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

The focus on warnings and errors implies a troubleshooting or diagnostics use case, but the description does not explicitly say when to use this tool versus alternatives such as check_health or get_status. No exclusions or prerequisites are stated.

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

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

With no annotations, the description carries full behavioral burden and does disclose the key trait: it performs no external refresh and opens nothing. However, it omits staleness/freshness guarantees, permission needs, and return format, so it is only partially transparent.

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 clause with the verb and the crucial negative constraint front-loaded, and no filler. The phrasing 'opening lectures' is slightly idiosyncratic but not wasteful.

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

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

For a zero-parameter read tool with no output schema, the description covers the essential fact that nothing external is touched, but an agent still cannot tell what the returned schedule looks like or how stale the cache may be.

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 the schema leaves nothing to explain and the baseline of 4 applies. The description adds no param detail because none is needed.

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 (Read) and resource (cached schedule), and the word 'cached' signals it is the non-refreshing variant. It does not explicitly differentiate itself from siblings like get_status or get_settings, but the resource 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 phrase 'without refreshing websites or opening lectures' implies the intended use case (fast, side-effect-free retrieval), but it never states when to prefer this over alternatives or what the alternative would be. Usage is only implied.

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

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

With no annotations, the description carries the full burden. It usefully discloses the exclusion boundary (no credentials or email codes) and that a validation schema accompanies the values, but says nothing about permissions required, whether values are defaults or overrides, or the response shape.

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

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

Two short sentences, no filler, with the core purpose front-loaded and the scope caveat immediately after. Every clause earns its place.

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

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

For a no-arg, no-output-schema getter, the description tells the agent what comes back (settings plus validation schema) and what does not (credentials, email codes). Missing only auth/permission expectations and any hint of persistence or defaults.

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

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

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; the description appropriately does not waste words inventing parameter semantics.

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

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

States a specific verb (Read) and resource (settings) plus the extra payload (validation schema). The verb 'Read' implicitly separates it from the sibling update_settings, but no sibling is named explicitly, so it stops short of full differentiation.

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 credentials or email codes' scopes what this tool is for, implying the agent must look elsewhere for secrets, but no alternative tool is named and there is no explicit when/when-not statement. Usage is inferable rather than stated.

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

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

No annotations are provided, so the description carries the full burden. It usefully discloses that no login or submission is required, implying a side-effect-free read, but says nothing about return format, caching, or failure behavior for an endpoint with no output schema.

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

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

A single compact sentence with the verb front-loaded and zero filler. It is appropriately sized for a zero-argument status 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?

For a trivial no-param, no-output-schema status endpoint, the description names both returned facts (version and scanner state) and the no-auth constraint, which is close to complete. Only the shape of the returned status values is left unspecified.

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 to disambiguate; baseline 4 applies. The description adds no parameter detail because none is needed.

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 (Read) and resource (application version and scanner state), which is clearly distinct from the settings/schedule/subject-rule siblings. It stops short of explicitly naming or contrasting with any sibling, so it lands at 4 rather than 5.

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

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

The phrase 'without logging in or submitting anything' implies this is a safe unauthenticated probe usable before authentication, but no explicit when-to-use or when-not-to-use guidance is given relative to get_settings or the other read 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 full behavioral burden. 'Read' implies a non-mutating operation and 'cached' usefully discloses that results may reflect a snapshot rather than live state, but permissions, freshness guarantees, and return shape are 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 filler; the verb and resource lead. It is efficient, though the AUTO/ASK/IGNORE vocabulary could be unpacked slightly for an unfamiliar agent.

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

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

For a zero-parameter read tool this is nearly sufficient, but with no output schema the description never explains what the returned rules look like (per-subject mapping, value semantics). It is adequate but leaves an avoidable 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?

The tool takes zero parameters, so the baseline is 4 and there are no parameter semantics for the description to elaborate on.

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 ('Read') and resource ('AUTO/ASK/IGNORE rules for subjects'), which cleanly separates it from the write-oriented sibling set_subject_rule. It does not explicitly name sibling tools, but the read verb plus the rule domain makes the purpose unambiguous.

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

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

There is no statement of when to use this tool versus get_settings, get_schedule, or set_subject_rule. The 'cached schedule' phrase hints at context but provides no explicit usage condition or exclusion.

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 disclosure burden, and it does say what the caller gets back: ready files plus in-app instructions. It doesn't discuss side effects, but a help/reference tool has little to disclose beyond its content.

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

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

Two short, front-loaded sentences with no filler. The trailing 'also shows the instructions in the app' slightly overlaps with 'with ready files' but stays within a useful length.

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

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

For a parameterless tool with no output schema, the description supplies both the content delivered and the condition for calling it. Nothing essential to invoking it correctly appears to be 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?

The schema declares zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. Omitting any parameter talk is appropriate rather than a gap.

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

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

The description states a concrete deliverable — VPN bypass guidance for two named services (MIREA and MTS Link), including ready-made config files and in-app instructions. That distinguishes it clearly from siblings like get_settings or repair, though the verb ('provides/returns') 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?

It gives an explicit trigger: 'Use when check_health says vpn_suspected,' routing the agent from a sibling tool's output directly to this one. It doesn't name a when-not condition or an alternative remedy, but for a single-purpose help tool that trigger is nearly sufficient.

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 real weight and delivers: it discloses that the operation mutates state ('Start one repair'), that it requires the in-app «Разрешить ИИ чинить приложение» permission, and that the outcome is asynchronous and must be validated via wait_and_check. It omits error/retry semantics and whether a repair can be started while another is in flight.

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

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

Three tight sentences: capability and action vocabulary first, prerequisite second, verification path last. No filler and no restatement of the tool name.

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

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

For a single-parameter tool with no annotations and no output schema, the description covers the mutation, the permission gate, the full action list, and the prescribed verification step. The one gap is return/response shape or failure behavior, which nothing else in the definition supplies.

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 'action' property has no enum, so the description is the sole source of the accepted value vocabulary — and it supplies all five literals, which is the key information an agent needs. It says nothing about invalid-action behavior or whether values are case-sensitive, keeping it from a 5.

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

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

Uses a specific verb ('Start one repair') on a specific resource and immediately enumerates the closed set of actions it accepts (retry_login, refresh_schedule, reopen_lecture, restart_browser, start_scanner). It also names the sibling wait_and_check as the follow-up step, so an agent can place it in the workflow without reading other schemas.

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?

'Start one repair from a problem's actions' frames the trigger condition, and 'Check the result with wait_and_check' routes the agent to the correct next tool. It does not state any when-not conditions (e.g. don't call if a repair is already running), so it stops short of explicit exclusions.

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

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

With no annotations at all, the description carries the full burden and does disclose an important behavioral trait: personal data is stripped and the text is sent to the developer, i.e. this transmits data outside the session. It does not say whether the submission is one-shot/irreversible or what happens to a report after it is sent.

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

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

Two sentences, front-loaded with the action and the format constraint, and the second sentence earns its place by disclosing the privacy/data-handling behavior. 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 two-parameter submission tool with no output schema and no annotations, the description covers format, language, and data handling, but leaves the 'fixed' parameter and any post-submission effect (confirmation, retry behavior) unaddressed.

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

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

Schema description coverage is 0%, so the description must compensate. It does specify the summary format well (3–6 lines, Russian, must cover what was wrong, what was done, and whether it helped), but the required 'fixed' boolean is never explained — the agent cannot tell whether it means 'the problem is resolved' or 'a change was applied'.

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+resource: it finishes a repair round by submitting a 3–6 line report on the problem, the action taken, and the outcome. This is clearly distinct from the sibling 'repair' tool, though the distinction is only implied via 'finish' rather than stated 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?

'Finish a repair round' implies this is called at the end of a repair cycle, which gives usable context. However, it never explicitly says to call 'repair' first, nor what to do if a round is abandoned, and no alternative tool is named.

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 disclose useful behavior: a permission requirement and the side effect that AUTO affects future lecture opening. It omits what ASK/IGNORE do at runtime, whether the change is reversible, and how failures surface.

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

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

Two tight sentences with zero waste, front-loading the core action and value domain before the permission constraint and the warning.

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 and no output schema, the description covers permission, side effects, and a safety warning, which is more than most. It still leaves the meaning of two of the three modes and post-invocation behavior undefined.

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

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

Schema description coverage is 0%, so the schema documents neither parameter. The description partially compensates by enumerating the mode values and noting the subject must already exist, but it never defines what ASK or IGNORE actually mean, leaving the semantics half-covered.

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 ('Set') and resource (subject rule) and enumerates the exact value domain (AUTO/ASK/IGNORE) for an existing subject. It clearly differs from the read-only sibling get_subject_rules, though it never names siblings or the broader update_settings tool 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?

Gives an explicit precondition ('only at user's request and with app-side permission') and a caution against silent changes, which is genuine when-to-use and when-not guidance. It stops short of pointing to the read sibling get_subject_rules to inspect current rules first.

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

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

With no annotations, the description carries the full behavioral burden and does well: it discloses the permission requirement, the no-unsaved-edits precondition, the need for user consent, and the fact that changes take effect in the running app. It still omits failure/partial-apply behavior and whether changes persist beyond the running session, which is a meaningful gap 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?

Four short sentences, front-loaded with the strongest constraint (only get_settings-listed keys). Each sentence carries a distinct operational fact, though 'Changes take effect in the running app' is slightly ambiguous about persistence.

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, no output schema, and an unconstrained nested object parameter, the description covers the key operational facts: source of valid settings, permission gate, UI-state precondition, user confirmation, and effect timing. Missing error/rollback semantics keep it short of complete.

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

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

Schema description coverage is 0% and the single 'settings' parameter is a free-form object with additionalProperties: true, so the schema tells the agent nothing. The description compensates partially by constraining valid keys to those returned by get_settings, but adds no expected shape, nesting, or value formats.

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

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

The description states a specific action on a specific resource (applying app settings) and explicitly ties it to the get_settings sibling, so an agent can distinguish it from the read-only getters. It never plainly says 'updates the application's settings', but the verb+resource pairing with the name is unambiguous enough.

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

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

It gives concrete preconditions (settings must come from get_settings, explicit app-side write permission, no unsaved UI edits) and a directive to confirm with the user first. The 'apply only settings listed by get_settings' phrasing also functions as an implicit exclusion for arbitrary keys, leaving little to inference.

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

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

With no annotations, the description carries the full burden. It does disclose the wait bound (up to 120 seconds) and that a repair takes roughly a minute, which is useful. But it never states whether the call blocks, whether it returns the health result or just a sleep acknowledgment, or what happens on failure, leaving the most important behavioral question unanswered.

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 duration bound and the reason for waiting are delivered immediately. The parenthetical is efficient, though the compressed phrasing contributes to the read ambiguity.

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

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

With no annotations, no output schema, and an undocumented parameter, the description needs to fully specify behavior. It omits what the tool returns and whether a separate check_health call is required, which is exactly the information an agent needs to invoke it correctly.

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

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

Only one parameter, the 'seconds' field, has 0% schema description coverage. The description partially compensates by supplying the 0–120 range, which is not documented in the schema. But it does not explain what happens above 120, negative values, or how the default of 60 interacts with the repair timing.

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 (wait, then check health) is identifiable, but it is unclear whether the tool itself performs the health check and returns results, or merely sleeps and instructs the agent to call check_health separately. That ambiguity sits at the core of the tool's purpose, so it falls short of a 4.

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 parenthetical about repair taking a minute, so an agent can infer this follows a repair. However, there is no explicit statement of when not to use it, nor any named alternative (the siblings include check_health and repair, which are clearly relevant).

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