monit.rs

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 is a state-mutating tool, yet it says nothing about side effects (does acknowledging notify on-call responders?), idempotency (what if already acknowledged?), or permissions required.

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, verb-and-resource first, then the parameter-sourcing hint. Nothing 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 a single-parameter mutation with no annotations and no output schema, the description covers the action and the parameter source but omits the behavioral context (effects, idempotency) an agent needs to invoke it confidently.

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 is 1 parameter at 0% schema coverage, so the description must compensate. It does add real value by explaining where dedup_key comes from (list_my_incidents()), but never explains what a dedup_key is or its format.

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

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

States a specific verb ('Mark') and resource ('an incident') plus the resulting state ('acknowledged'), which cleanly distinguishes it from siblings like resolve_incident and describe_incident.

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 tells the agent how to source the required dedup_key via list_my_incidents(), which is genuinely useful. However it gives no guidance on when to acknowledge versus resolve, or any prerequisites/conditions for acknowledging.

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 a genuine behavioral constraint not derivable from the schema – that exactly one credential field must be supplied and it must match channel_type – but it omits permissions, error/duplicate behavior, and side effects of this mutation.

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?

Front-loaded with the imperative, then a single mutually-exclusive rule, then a tight aligned table. Every line earns its place with 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?

With no annotations and no output schema, the description should cover return/success behavior and auth requirements, which it does not. Its coverage of the create-specific parameter rules is good, but the operational context is thin and min_severity is 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, and it does for the four interdependent credential params by mapping enum values to the correct field with examples. It adds no meaning for min_severity, which is left undocumented.

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

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

States a specific verb+resource ('Create an alert channel'), so the agent knows exactly what it does. It does not explicitly distinguish itself from the sibling list_alert_channels, but the verb alone is unambiguous against the other create_* tools.

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

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

Gives clear conditional guidance mapping each channel_type to the parameter it requires via a compact table, which is strong 'how to invoke' guidance. It stops short of stating when to prefer this over siblings or any prerequisites for calling 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 carries the full burden. It usefully discloses the tier max_endpoints cap, but says nothing about authentication, what happens when the cap is exceeded, whether the endpoint is immediately active or paused, or name-uniqueness behavior for a write 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?

Two short sentences with the purpose front-loaded and the quota constraint immediately after. Nothing is wasted or buried.

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 four undocumented parameters, the description is too thin. It should convey invocation constraints and basic parameter meaning to compensate for the structured-data gaps.

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

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

Schema description coverage is 0%, so the description must explain url, name, method, and interval_seconds, yet it mentions none of them. The schema's defaults (method=GET, interval_seconds=900) provide a little implicit meaning, but format expectations for url and uniqueness of name are 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 ("Create a new monitored endpoint"), which clearly separates it from delete_endpoint and update_endpoint_interval. It stops short of naming a sibling or clarifying scope (e.g. user vs workspace), so it is clear but not fully differentiated.

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 reference to alternatives among the many create_* and *_endpoint siblings. The only contextual hint is a quota note about the tier's max_endpoints cap.

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

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

With no annotations, the description carries the full burden, and it does disclose two meaningful traits: the page is public and its slug becomes a subdomain. It also explains a deliberate capability boundary. It omits side-effect details such as slug uniqueness/collision behavior and 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?

Two short sentences, zero filler, and the core outcome (public page at <slug>.status.monit.rs) is front-loaded before the caveat about endpoints.

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 and no annotations, so the description must cover behavior; it handles scope and the endpoint limitation but leaves parameter meaning, authentication requirements, and failure modes (e.g., duplicate slug) unaddressed for a 3-parameter mutation 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?

Schema description coverage is 0% for all three parameters. The URL template implicitly tells the agent that slug is a subdomain label, but title and description get no semantic explanation at all, so the description compensates only partially for the documentation 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?

Specific verb (create) plus resource (public status page) and even the resulting URL pattern, which tells the agent exactly what artifact it produces. It distinguishes itself from sibling list_status_pages by making clear this is the creation tool, not a read.

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?

Explicitly states the alternative path for the follow-on step — add endpoints via the dashboard or HTTP API — and explains why chat-based endpoint mapping is deliberately excluded. It does not, however, say when an agent should create a status page at all versus other workflows.

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 so richly: it discloses cascading deletions, two safety layers (exact name confirmation and per-user 5/day destructive cap), and the anti-injection rationale behind the confirmation field.

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 front-loaded with purpose and cascade effects, then uses a compact numbered list for safety constraints. Every sentence adds meaningful operational guidance, including why the confirmation requirement exists and where to go for bulk operations.

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 dangerous mutation tool with no annotations, no output schema, and a minimal two-parameter schema, the description supplies the destructive behavior, cascade consequences, confirmation mechanics, rate limit, and alternative paths. Nothing essential 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?

Although schema description coverage is 0%, the description thoroughly documents the non-obvious confirmation parameter—exact match, case-sensitive, whitespace-trimmed, and how to obtain the name via describe_endpoint(id). The endpoint_id parameter is only implied, but its meaning is standard and sufficiently clear from context.

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

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

The description names a specific verb and resource: 'Delete a monitored endpoint.' It also states the cascade scope (test_results, baselines, regressions, incidents), making the operation distinct from sibling tools like pause_endpoint or describe_endpoint.

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

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

It clearly explains when this tool is appropriate for single-endpoint deletion, and it explicitly routes legitimate bulk deletes to the HTTP API or dashboard. It does not directly compare against pause_endpoint, but the destructive nature is unambiguous.

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. It implies a read operation via 'Full detail', but says nothing about permissions, whether the endpoint must belong to the caller, error handling for unknown IDs, or rate limits. For a 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?

Two short sentences, front-loaded with the purpose and followed by the one piece of operative guidance. Nothing extraneous.

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-param lookup with no output schema and no annotations, the description covers enough to call the tool but not enough to set expectations — it does not indicate what 'full detail' contains or what happens on a bad ID. Adequate but with clear 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 coverage is 0% for the single endpoint_id parameter, and the schema gives no description. The description partially compensates by telling the agent where to obtain the ID (list_my_endpoints()), but adds no format, naming, or validity details for the value itself.

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: 'Full detail for one endpoint.' It clearly distinguishes itself from list_my_endpoints by contrasting singular vs. listing, and from create/delete/update siblings by implication. It stops short of naming a sibling alternative in an exclusionary way, but the purpose 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?

Provides a prerequisite/workflow hint — obtain the ID from list_my_endpoints() — which is genuinely useful routing. However there is no explicit when-to-use vs. when-not guidance, and no mention of error behavior for invalid or foreign IDs.

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 discloses that the response includes endpoint name and current status, and it is implicitly a read operation. However, it says nothing about permissions, whether the incident must exist, or error behavior for an unknown dedup_key.

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, front-loaded with the purpose and followed by the prerequisite and payload summary. 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 single-parameter read tool with no annotations and no output schema, the description covers purpose, prerequisite, and what is returned — enough to call it correctly. Minor gaps are the key format and error 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 coverage is 0% for the single dedup_key parameter, so the description must compensate. It usefully tells the agent where to get the key (list_my_incidents), but never describes its format or uniqueness, leaving the parameter only partially documented.

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: 'Full detail for one incident', and distinguishes itself from the sibling list_my_incidents by scoping to a single record. It also notes the payload contents (endpoint name, current status). Clear, though it could more explicitly contrast with describe_endpoint/other describe_* siblings.

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?

Explicitly routes the agent to list_my_incidents() as the way to obtain the required dedup_key, which is a genuine prerequisite. No when-not conditions or alternatives are stated, but the sourcing guidance is concrete.

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 provided, so the description must carry the full behavioral burden. It only implies a read operation and says nothing about permissions, rate limits, pagination, error conditions, or what the aggregation includes.

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; every word contributes to the purpose.

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 no annotations, no output schema, and zero parameter descriptions, the description is too sparse. It omits the read-only nature, response shape, aggregation definition, and window 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 description only names the two parameters in prose ('endpoint', 'requested window'). It does not explain the endpoint_id format or the meaning/units of each window option, leaving the schema's bare property names to carry the load.

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?

Names the resource (endpoint uptime summary) and the aggregation window, so the agent knows it retrieves an aggregate rather than raw metrics. It does not explicitly distinguish itself from siblings like monit_rs_stats or describe_endpoint, so not 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?

No guidance on when to use this versus describe_endpoint, monit_rs_stats, or other monitoring tools. No prerequisites or exclusions 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 the behavioral burden and does disclose a critical trait: it does NOT return decrypted config such as webhook URLs and PagerDuty routing keys. It also implies authentication is required ('authenticated account'). It doesn't cover rate limits or pagination, but the security-relevant omission is well surfaced.

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 action, then the critical limitation, then the alternative. Every sentence earns its place with no redundancy.

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

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

An output schema exists, so return values need not be spelled out, and the description helpfully clarifies what is omitted from the return. Auth needs are implied and the alternative path is given. Only minor operational details (pagination, ordering) are left 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?

The tool takes zero parameters, so the baseline is 4 per the rules. There is nothing further for the description to clarify about inputs.

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

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

The description opens with a specific verb and resource ('List alert channels') and scopes it to the authenticated account, distinguishing it clearly from the sibling create_alert_channel. An agent can immediately tell this is a read-only enumeration 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?

It explicitly states when not to rely on the output (when you need decrypted config) and names concrete alternatives: the dashboard or the `describe_alert_channel` HTTP API. This is exactly the when/when-not/alternative routing the dimension asks for.

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 burden and does disclose the shape of results (brief records) and that fuller fields live behind describe_endpoint. It stops short of noting pagination, ordering, or result limits, which would matter for an enumeration tool on an account with many endpoints.

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

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

Two tight sentences. The scope statement leads, and the routing hint to describe_endpoint follows immediately with zero 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?

An output schema exists, so return values need not be re-explained, and the zero-parameter schema means no argument documentation is required. Scope, enumeration intent, and the path to richer detail are all covered.

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; the 4 baseline applies. No misleading or missing parameter guidance is present.

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 (list monitored endpoints) plus a clear scope constraint (owned by the authenticated account). It also distinguishes itself from describe_endpoint, so an agent can separate it from the sibling without opening either schema.

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 explicitly says the output is suited for enumeration and names the alternative, describe_endpoint(id), for full detail. The condition selecting the alternative (need for headers, spec URL, heartbeat_token) is spelled out rather than 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?

No annotations exist, so the description carries the full burden. It usefully discloses the default status filter and that results carry a dedup_key for downstream actions, but says nothing about ordering, pagination behavior, limits, or permissions. Adequate but with clear gaps for a list tool with zero annotation coverage.

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, front-loaded with the core action and scope, then the default, then the actionable follow-on hint. No filler text.

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 documentation is unnecessary, and the description still flags the one return field an agent must act on (dedup_key). With only two optional params and a documented default, the main remaining gap is limit/pagination 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%, so the description must compensate. It explains the effective default of the status parameter ('only OPEN incidents'), but the limit parameter and the accepted status values are left entirely to the schema's enum/default. Partial compensation only.

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 ('List') plus resource ('incidents') and scope ('on the caller's account'), which separates it from describe_incident (single incident) and from the other list_* siblings by resource. The default-filter sentence adds precision about what the listing actually returns.

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?

Explicitly says it defaults to only OPEN incidents, so an agent knows the status filter must be widened to see acknowledged/resolved. It also names the follow-on tools (acknowledge_incident, resolve_incident) and the key needed to call them. It stops short of stating when to prefer describe_incident over this 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 carries the full burden and falls short. It never states ordering, whether results are paginated, how 'detected' regressions are produced, or whether any permission/scope is required beyond 'caller's account'.

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 with the resource statement front-loaded and the filter hint trailing. No filler, though the second sentence is thin enough that it could have carried more substance at the same 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?

An output schema exists, so return-value explanation is not required, and the tool is a simple two-optional-param list. Still, nothing clarifies result ordering, pagination behavior via 'limit', or what constitutes a regression, which an agent needs to call this confidently.

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

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

Schema description coverage is 0%, so the description must compensate for both parameters. It explains only endpoint_id as a filter and says nothing about 'limit' (default 20), so half the parameters remain 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?

States a specific verb ('List') and resource ('detected schema regressions') scoped to 'the caller's account', which cleanly separates it from the sibling list tools for endpoints/incidents/channels. It does not, however, distinguish itself from the detection-oriented sibling openapi_diff, leaving a small ambiguity about which tool surfaces regressions.

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 offers no when-to-use versus when-not-to-use guidance and no alternatives. 'Optionally filter by endpoint_id' describes a parameter, not an invocation context, so the agent gets no routing signal beyond 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?

No annotations are provided, so the description carries the full behavioral burden. 'List' implies a read-only operation, but nothing is said about result limits, pagination, ordering, or permission requirements, and 'limit' defaulting to 20 is never acknowledged.

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 with the resource and scope front-loaded and the optional filter second. No filler or redundancy.

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

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

An output schema exists, so return values need not be explained, and this is a simple two-parameter list tool. However, with 0% schema coverage the description should have filled the gap on limit/pagination semantics and it does not.

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

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

Schema description coverage is 0% and there are two parameters. The description covers only the severity filter semantically ('Optionally filter by severity'), while 'limit' — its default of 20 and cap behavior — is left 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?

States a specific verb (List) and resource (security findings) with an explicit scope constraint: findings on the caller's monitored endpoints. No sibling covers the same resource, so the agent can distinguish it from list_my_incidents/list_my_endpoints, though it never names a sibling explicitly.

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

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

The only guidance is 'Optionally filter by severity,' which describes an option rather than when to use this tool versus alternatives. No prerequisites, no when-not-to-use, and no reference to the many sibling list_* 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 discloses account ownership and that only public pages are returned, and 'List' implies read-only behavior, but it does not mention pagination, rate limits, or side effects beyond the implied read.

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, and no wasted words. It communicates the essential scope immediately.

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 list tool with an output schema present, the description states exactly what is listed and the ownership scope. Return-value details are appropriately left to the output schema, so nothing needed for correct invocation 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?

The tool takes zero parameters, so the baseline is 4. The empty schema and 100% schema description coverage mean the description need not compensate for missing parameter documentation.

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 ('List'), resource ('public status pages'), and ownership scope ('owned by the authenticated account'). The name and description together clearly distinguish it from sibling tools like create_status_page.

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 explicit when-to-use guidance, no prerequisites, and no named alternatives such as list_my_endpoints or create_status_page. Usage is only inferable from the verb '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 carries the burden and does well: it discloses the content source (monit.rs/llms.txt) and that the output is curated/authoritative rather than generated. It does not state that the call is read-only and side-effect free, nor anything about caching or freshness, which is a minor gap for a zero-param lookup.

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 sentences, front-loaded with the purpose before the usage conditions. The closing clause slightly restates the opening ('canonical' vs 'curated... authoritative'), so it is efficient but not maximally 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?

An output schema exists, so return-value detail is not required, and the description still tells the agent what the payload represents and where it originates. For a no-arg documentation tool this is nearly complete; only the read-only nature is left implicit.

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?

Zero parameters, so the baseline of 4 applies; there is nothing for the description to disambiguate. No misleading param hints are present.

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 — 'Return the canonical product description for monit.rs' — and immediately distinguishes itself from the CRUD/incident siblings by being a documentation-fetch tool. An agent can tell what it returns without opening the schema.

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?

Explicitly enumerates the triggering conditions: user asks what monit.rs is, what it does, how it differs from Pingdom/Checkly/UptimeRobot, or wants product URLs. This is a textbook when-to-use statement with no inference required.

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, and it usefully discloses that counts are approximate and accurate only 'within about 5% of exact', plus that the data is live and platform-wide. It does not mention authentication, caching, rate limits, or refresh cadence, leaving minor gaps.

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?

Purpose is front-loaded in the first sentence, and the description is short with no filler. The middle sentence restates what the output schema already returns, and the rhetorical-question sentence is slightly informal, but neither is wasteful enough to drop below 4.

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 stats endpoint with an output schema, the description supplies purpose, scope, and an accuracy caveat — enough for an agent to call it correctly. Only operational details (auth, caching, staleness) are absent, which is a minor 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 there is no parameter semantics to explain; the baseline for a zero-param tool is 4. Nothing in the description contradicts or confuses 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 and resource ('Get live aggregate statistics for the monit.rs platform') and immediately enumerates what is counted (regressions caught, AI analyses generated, probes executed). This is clearly distinguishable from siblings like monit_rs_describe or list_my_regressions without opening a schema.

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 usage context — answering 'does monit.rs actually work at scale?' — which tells the agent when this tool is appropriate. It stops short of naming alternatives or stating when not to use it, so it does not reach the top band.

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 reasonably well: it enumerates what is compared (including 'required toggle' and retype detection) and states the return shape. It does not mention whether specs are validated, size limits, or error behavior on malformed input, which are the remaining behavioral gaps for a parsing 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?

Three tight paragraphs, front-loaded with the core action, then usage, then the full diff scope and return shape. Every sentence adds information; no filler or 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?

An output schema exists, so the return format need not be described, though the description does so anyway as a convenience. For a two-param, computation-only tool with no annotations, the description covers purpose, scope, input format, and output well. Only minor gaps remain (input validation, error conditions).

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% — the schema provides only titles like 'Old Spec' and 'New Spec'. The description compensates by stating 'Both arguments are the OpenAPI spec as a JSON or YAML string,' which is the critical format information the schema lacks. It does not clarify ordering semantics (which spec is old vs new) beyond parameter names.

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 (compare) plus the resource (two OpenAPI 3.x specs) and the classification output (breaking/non-breaking/info). It also enumerates the diff surface (paths, operations, parameters, request bodies, responses, response-body schema fields), which makes it unmistakable relative to any sibling. No other tool in the list performs spec comparison.

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?

Explicitly frames the use case: 'Use this when you want to know if a candidate OpenAPI spec change is safe to ship or will break existing clients.' That gives a clear triggering condition. It stops short of naming when-not-to-use or an alternative, but no sibling overlaps this function, so the omission is minor.

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 it does meaningful work: it discloses that probing stops, that history is retained, and that the operation is idempotent. It omits permissions/auth requirements and any effect on downstream alerts or incidents, but the core behavioral traits are covered.

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 compact sentences, front-loaded with the action and its effect, followed by the idempotency caveat. No filler; 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 simple one-parameter toggle with no output schema and no annotations, the description covers what the agent needs: the state change, history retention, and idempotency. Minor gaps remain around permissions and side effects on related resources, but nothing blocks 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?

There is one required parameter (endpoint_id) with 0% schema description coverage, and the description never mentions it. The parameter name is largely self-explanatory, so the gap is minor, but the description adds no format, source, or constraint information beyond the 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 (pause) and resource (monitored endpoint), and clarifies the effect: stops probing but keeps history. This is enough for an agent to distinguish it from resume_endpoint, delete_endpoint, and update_endpoint_interval without opening any schema.

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 explicit when-to-use or when-not-to-use guidance and no sibling named as an alternative. The idempotency note ('no-op if already paused') implicitly tells the agent it is safe to call repeatedly, but that is inferred rather than stated as 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 must disclose behavior. It states only that the tool closes an incident, without describing permissions, idempotency, reversibility, effects on related alerts, or response 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?

Two short sentences, with the core action first and the sibling relationship second. No filler; appropriately sized for the 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 mutation tool with no annotations and no output schema, the description is too thin. It omits key context such as what closing does, what dedup_key identifies, and what the caller should expect.

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

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

Schema coverage is 0% and the sole parameter dedup_key has no description. The description does not mention dedup_key at all, so it adds no meaning beyond the schema's type string.

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

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

States a specific verb ('Close') and resource ('incident'), and references the sibling acknowledge_incident to indicate its counterpart role. This distinguishes it from generic incident operations, though it does not fully explain the state transition.

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 'Symmetric to acknowledge_incident' implies usage context: it is the counterpart action to acknowledgement, likely used when an incident is resolved. However, it gives no explicit when-to-use conditions, prerequisites, or exclusions, leaving the agent to infer.

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 burden and does disclose a real behavioral trait: the tool rejects the call when the tier's active-endpoint cap would be exceeded, plus remediation. It omits auth requirements, idempotency, and what happens if the endpoint is already active.

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, zero filler, with the primary purpose front-loaded and the failure condition plus remedy following. 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 a one-parameter state-change tool with no output schema and no annotations, the description covers purpose and the main failure mode. It could say more about auth/permissions and the success result, but the essential calling information is present.

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 never mentions endpoint_id, so it adds no meaning beyond the schema. The single parameter is self-evident, but the description does nothing to clarify its format or accepted values.

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 ('Resume a paused endpoint') and implicitly contrasts with the sibling pause_endpoint by naming the state it operates on. An agent can identify the operation without opening the schema.

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 explains the precondition for success (resuming must not exceed the tier's active-endpoint cap) and names the alternatives (upgrade or pause another endpoint). It doesn't explicitly say 'use when an endpoint is paused', but the state is stated in the first sentence.

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 disclosure burden. It usefully exposes a real behavioral constraint — the per-tier minimum interval (free=900s ... enterprise=30s) — which prevents invalid calls, but says nothing about required permissions, whether the change takes effect immediately, or whether it 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?

Two short sentences, zero padding, with the core action front-loaded and the constraint 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 two-parameter mutation tool with no annotations and no output schema, the definition covers the essential validity constraint but omits permissions/auth and any note on effect latency or what happens to existing schedules. Adequate but with clear gaps.

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

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

Schema description coverage is 0%, so the description must compensate. It does clarify that the interval is measured in seconds and enumerates tier-specific minimums, giving concrete semantics for interval_seconds; endpoint_id remains undocumented but is self-evident from its name.

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 in plain language: 'Change how often an endpoint is probed' clearly maps to updating an endpoint's probe interval, and it reads distinctly from siblings like pause_endpoint or resume_endpoint. It stops short of naming any alternative, so it earns 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?

There is no statement of when to use this tool versus alternatives (e.g. pause/resume) and no prerequisites or context. The tier minimums describe valid values rather than usage routing, so the agent must infer the invocation context entirely.

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