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 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.