UK Data: Is it down? Service status

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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: live incident reports from the official Statuspage, coverage of web/API/model availability, and a 1-credit cost.

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 purpose and source, with cost appended at the end. No redundant wording.

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

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

For a zero-parameter status tool with rich annotations and no output schema, the description supplies enough: what is checked, the source, coverage, and cost. No critical invocation detail 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?

There are no input parameters, so parameter semantics are not applicable and the baseline is 4. The description does not need to compensate for schema gaps.

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

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

States a specific verb ('Check') and resource ('Claude or the Anthropic API') with clear scope around downtime and performance issues. The provider-specific naming distinguishes it from sibling status tools such as openai_status and github_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?

Clearly indicates when to use it: checking Claude/Anthropic downtime or performance issues. It does not explicitly name alternatives or exclusions, but the provider-specific scope makes the relevant sibling choice obvious.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description adds value beyond that: the data comes from Atlassian's official status page and includes official incident updates plus component-level health, and it discloses a cost of 1 credit, which is operationally useful.

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 purpose, then scope, then return content, then cost. Two clauses ('project management tools, issue tracking, and developer workflows') are largely redundant expansions of 'Jira' and could be trimmed without losing routing value.

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

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

For a parameterless, read-only status reader with no output schema, the description covers source, subject matter, and what kind of data comes back (incident updates, component health). Refresh cadence or whether it returns an overall up/down flag is unstated, but nothing essential to a correct call 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?

Zero parameters, so baseline 4 applies; there is nothing for the description to clarify about inputs and it doesn't waste words pretending otherwise.

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 ('monitor'/'check') and resource ('status of Jira Software and related Atlassian cloud services'), which distinguishes it from the many sibling status tools (github_status, cloudflare_status, slack_status) by naming the vendor and product family. It doesn't explicitly say 'for Atlassian products only' but the naming makes the routing clear 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 a use context ('check for outages affecting project management tools, issue tracking, and developer workflows') but no explicit when-to-use/when-not guidance or named alternatives. An agent must infer it should pick this over github_status or zoom_status purely from the product 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?

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds two genuinely useful details beyond them: the data provenance ('straight from Cloudflare's official status page') and a cost of 1 credit. It does not disclose the return shape, whether data is cached or truly real-time, or what an empty/all-operational response looks like — meaningful gaps given there is 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?

Front-loaded with the core scope and broken into short, scannable sentences; nothing is buried. The 'Essential for web administrators' sentence is somewhat promotional, and the parenthetical credit note sits awkwardly at the end rather than up front, but overall the text earns most of its space.

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, zero-output-schema tool, the description does a fair job enumerating what kinds of signals are covered (network, DNS, edge, dashboard, Workers, Pages). However, with no output schema the description carries the full burden of indicating what a response looks like, and it never says whether the result is a component list, an incident feed, or an overall indicator — an agent must call it blind to find out.

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 is 4. The description correctly does not invent or imply any 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?

States a specific verb+resource: monitoring Cloudflare's global network, DNS, and edge computing status, with named sub-scopes (routing issues, dashboard availability, Workers, Pages). The tool name and the Cloudflare-specific framing make it distinguishable from the many sibling *_status tools, though the description never explicitly says 'use this for Cloudflare, not github_status/slack_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?

Provides clear usage context by naming the scenario: 'web administrators troubleshooting site accessibility or CDN performance.' That is enough to know when to reach for it. It stops short of explicit alternatives — with roughly fifteen sibling status tools in the list, a sentence like 'for GitHub/AWS outages use X instead' would have earned a 5.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so safety is covered. The description adds genuinely non-structured information: the data comes 'directly from the official DigitalOcean status page' (confirming the open-world external source) and that each call costs 1 credit, which matters for invocation budgeting. It does not describe freshness/latency or rate limits, keeping it out of 5 territory.

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 what is checked, then the source, then audience. The 'useful for developers...' sentence is the weakest and borders on filler, but the cost note earns its place. No redundancy or padding beyond that.

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

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

For a zero-parameter, read-only status tool with no output schema, the description covers the substantive question of what the response concerns (per-service and regional status, API availability, database health). The remaining gap is that it never says what the response shape is (overall indicator vs. component list), which is the one thing an agent cannot infer without an output schema.

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

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

The tool takes zero parameters, so the baseline is 4 and there is nothing for the description to disambiguate. It correctly avoids inventing parameter-like options such as region filters that the schema does not support.

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

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

The description gives a specific verb ('Check the status') and an enumerated resource set (droplets, networking, storage, regional outages, API availability, managed database health) tied to the DigitalOcean vendor. An agent can distinguish it from github_status or cloudflare_status purely from the name plus this text. It stops short of a 5 only because sibling differentiation is implicit in the vendor name rather than stated.

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 offers audience framing ('useful for developers managing cloud infrastructure and troubleshooting connectivity'), which implies when to reach for it. There is no explicit when-not guidance, no mention of the other ~10 status siblings, and no statement of prerequisites, so usage is implied rather than directed.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds genuinely useful context the annotations lack — data originates from Discord's official status dashboard and each call costs 1 credit. It does not say what is actually returned (overall indicator vs. incident list vs. component uptime), and no output schema exists to fill that 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?

The purpose and component scope are front-loaded in the first sentence, and the cost note is a useful trailing signal. The middle sentence partly restates the first ("monitor real-time connectivity... API performance") in more promotional phrasing, which is mild padding.

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 status lookup, the description covers what is checked, the source of truth, the motivating scenario, and the cost. The one real omission is the response shape — component-level statuses versus incident summaries — since no output schema exists to convey it.

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

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

The tool takes zero parameters, which is the baseline-4 case. There is nothing for the description to disambiguate, and it correctly implies a single no-argument call.

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?

"Check the operational status of Discord's API, Gateway, and Media Proxy" names a specific verb and resource and scopes it to named Discord components. Against the many sibling status tools (slack_status, github_status, cloudflare_status), the Discord scope makes the target unambiguous 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 gives a concrete usage trigger: developers seeing "stuck on connecting" or message delivery failures. However, it never names an alternative or states exclusions (e.g., use slack_status/github_status for other services), so routing guidance is contextual rather than explicit.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds meaningful context beyond them: data comes from GitHub's official status page, it is real-time, and the call costs 1 credit. It stops short of describing the response shape or freshness/rate limits.

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 compact sentences, front-loaded with what is checked, followed by data source and use case. The credit-cost note is short and useful; minor redundancy between "current operational status" and "real-time updates" is the only soft spot.

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-parameter, read-only lookup with annotations covering safety and no output schema, the description gives enough: what services, where the data comes from, what it reports, and the cost. Only a brief note on return structure would make it fully self-contained.

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

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

The tool takes zero parameters, which is the baseline for a 4. Nothing in the schema needs additional explanation, and the description correctly implies no inputs are required.

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 a specific verb and resource ("Check the current operational status of GitHub services") and enumerates the covered components (Actions, Pages, API), so the agent knows exactly what is returned. It does not explicitly differentiate itself from the many other *_status siblings (cloudflare_status, openai_status, slack_status), though the GitHub-specific naming makes the distinction obvious.

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

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

"Useful for developers troubleshooting deployment failures or connectivity issues" supplies a concrete triggering scenario. There are no explicit exclusions or references to alternative tools, but for a zero-parameter status lookup the context is 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?

Annotations already declare readOnly, idempotent, non-destructive behavior, so the description need not restate safety. It adds valuable context beyond annotations: the data comes from OpenAI's official status page, it is real-time, and each call costs 1 credit — the cost note is especially useful for an agent deciding whether to re-poll.

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 core action and followed by data scope, use cases, and cost. Slight redundancy between the first two sentences ('status of...' and 'Monitor real-time availability...'), but nothing wasteful enough to penalize heavily.

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

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

For a parameterless, read-only lookup with annotations covering the behavioral profile, the description supplies what is needed: what services are covered, where the data originates, when to call it, and the credit cost. The absence of an output schema means a hint about what is returned (availability states, incidents) would be a marginal improvement.

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, which is the baseline 4. There is nothing parameter-related to explain, and the description correctly does not invent input options.

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 ('Check') and resource (status of ChatGPT, OpenAI API, Labs), and names the exact scope of what is monitored. Among many sibling status tools (anthropic_claude_status, github_status, cloudflare_status), the OpenAI service naming makes the target 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?

Gives concrete trigger conditions: slow responses, login failures, API errors. It does not name an alternative tool or state when not to use it, but the conditions are specific enough to select the tool confidently.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), so the description only needs to add non-obvious context — and it does: the official-status-page provenance and the '1 credit' cost, which matters for an agent budgeting calls. It does not describe the shape of the status payload, which is the main remaining 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?

Front-loaded with what is checked, then why it matters, then provenance and cost. Four sentences is slightly more than strictly needed — the 'Critical for merchants...' sentence overlaps with the first — but nothing is 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 zero-parameter read tool with no output schema, the description tells the agent what domains are covered (storefront, admin, checkout, payments, API, apps) so the return values are predictable. Only the status vocabulary (e.g., operational/degraded/outage per component) 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?

The tool takes zero parameters, so the schema imposes nothing to explain and the baseline is 4. The description correctly describes a no-argument global check rather than implying any filtering options.

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

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

Specific verb + resource: 'Check the status of Shopify storefronts, admin, and checkout', with the monitored surfaces (payment processing, API endpoints, third-party apps) enumerated. The vendor-specific name plus the explicit component list makes it unmistakable against the many other *_status 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?

'Critical for merchants investigating store downtime or checkout disruptions' gives a concrete triggering scenario, and 'directly from Shopify's official status page' clarifies the source of truth. It stops short of stating exclusions (e.g., that it does not diagnose your own store's configuration or orders), so it is clear context rather than full when/when-not 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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new context: the data comes from the official Slack Status API (authoritative source, live network dependency) and that it returns active incidents as well as current status. It omits return shape and severity vocabulary, which keeps it below a 5.

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 purpose before the mechanism and cost. Slight redundancy between 'Verify if Slack is experiencing connectivity issues' and 'fetches the current status and active incidents', but no filler otherwise.

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 probe with full annotation coverage, this is nearly complete: source, scope, and cost are all stated. The only gap is a hint about what the response contains structurally (e.g., status indicator plus incident list), which matters slightly since there is no output schema.

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

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline for a no-param tool is 4. The description correctly implies no input is needed by framing the call as a direct fetch.

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 ('fetches the current status and active incidents') scoped to Slack, and explicitly lists the covered surfaces (messaging, calls, file uploads). Against siblings like discord_status or cloudflare_status, the Slack scope is unambiguous from the name and first sentence.

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 opening sentence implies the use case ('verify if Slack is experiencing connectivity issues'), which is enough to know when to call it. However, there is no explicit guidance on when not to use it or which sibling status tool to pick when the user's question is ambiguous, and no mention of how often to re-poll during an incident.

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

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

Annotations already establish readOnly, idempotent, non-destructive, open-world behavior, so the bar is lower. The description still adds real value: the upstream data source (official Zoom Statuspage API), that updates are real-time, that it covers disruptions and scheduled maintenance, and the 1-credit cost. It stops short of describing the response shape (overall indicator vs per-component breakdown).

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, followed by source and coverage detail. Slightly padded – the third sentence about 'audio, video, and screen sharing' restates the component-coverage idea already conveyed, and the parenthetical credit note is tacked on – but nothing is genuinely misleading or 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-only status check with no output schema, the description covers what the tool does, where the data comes from, and its granularity. A brief note on the shape of the returned status (overall vs per-component) would have made it fully self-sufficient, but the remaining gap is minor.

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 schema is empty, so the baseline of 4 applies. There is no parameter behavior the description could usefully clarify, and it correctly implies a single unparameterized call returns all status data.

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 ('Verify') and a specific resource ('operational status of Zoom Meetings, Phone, and Video Webinars'), and names the components covered. Against the many sibling status tools (slack_status, github_status, atlassian_status), the provider is unambiguous from the name and description alone.

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 phrase 'Verify the operational status' – an agent knows this is a health-check tool. However, there is no explicit statement of when to prefer it over alternatives (e.g. general news search for outage reports) or any preconditions. Adequate but leaves routing to inference.

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