UK Business Calendar MCP

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

With no annotations, the description must carry behavioral disclosure: it usefully states that calendar-day results are rolled to the next working day and mentions a statutory 30-day default. It says nothing about how `from` defaults when omitted, whether paid subscription (access_token) is mandatory, or what the result looks like.

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 operation and immediately followed by the rolling/default nuance. The 'PRO.' marker is noise but costs almost nothing.

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

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

For a 5-parameter tool with no annotations and no output schema, the description covers the core calculation rule but leaves the auth requirement, `from` default, and return shape unaddressed, forcing the agent to infer from the schema fragment.

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 only 40% (`days`, `from`, `working` have no schema descriptions). The description partially compensates by contrasting working days vs calendar days (mapping to `working`) and naming a 30-day default, but never explains `from`'s format/default or whether negative `days` are allowed.

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?

Clear verb+resource: add N working or calendar days to a date to produce an invoice/contract due date. It is distinguishable from siblings like working_days (which presumably counts) and tax_deadlines, though the description never names an alternative 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 'Invoice/contract due date' framing implies the use case, and 'Includes Late Payment Act 30-day default' hints at a legal-basis scenario, but there is no explicit when-to-use / when-not guidance or routing to working_days for pure day counting.

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 adds useful behavior context: it is a paid PRO tool costing $0.01, searches Wikipedia, and returns up to 10 articles with snippets plus summaries for the top 3. However, it does not explicitly state authentication requirements, rate limits, error behavior, or whether results are paginated.

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

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

The description is a single tightly written sentence that front-loads cost and purpose, then states the result shape. Every phrase carries useful information 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?

For a simple search tool with no output schema and no annotations, the description covers the source, result count, snippets, and top-3 summaries. It is still thin on parameter semantics and authentication behavior, especially given only 33% schema description coverage.

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 only 33%, so the description must compensate for undocumented parameters. The description does not explain the required 'query' parameter or the 'max' parameter, aside from loosely implying a cap of 10 articles. The access_token parameter is documented in the schema, but the other two are not.

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

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

The description states a specific verb and resource: Wikipedia search for background facts. It also clarifies the return shape: up to 10 matching articles with snippets and summaries for the top 3. It distinguishes this from news-oriented siblings by emphasizing Wikipedia background facts, though it does not explicitly name a sibling alternative.

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 'Wikipedia search for background facts' and the PRO cost note, but there is no explicit when-to-use, when-not-to-use, or alternative-tool guidance. An agent can infer this is for background factual research rather than current news, but the definition does not route among siblings.

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

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

With no annotations, the description carries the full burden, and it does disclose one genuinely useful behavioral rule: payday is suggested as the last working day or the 25th rolled back. It still omits whether the operation is read-only, how region affects bank-holiday results, and what failure looks like without a valid subscriber token. Partial disclosure of behavior beyond the schema.

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

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

A single compact sentence that front-loads the month scope and enumerates outputs efficiently. The only wasted token is the unexplained 'PRO.' marker, which costs clarity rather than 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?

There is no output schema, so the description must convey return values; it names the categories but leaves 'deadlines' ambiguous (tax? user-supplied? statutory?) and says nothing about the shape of payday suggestions or holiday output. For a compound, three-parameter tool with no annotations, this is adequate but thin.

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 100%, so month format, the region enum values, and the access_token source are all documented in the schema. The description adds nothing about any of the three parameters — no mention of region affecting holidays or of the token's role. Baseline 3 is appropriate since the schema does the work.

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 lists the concrete outputs (working days count, bank holidays, payday suggestions, deadlines) for a given month, which gives a reasonably clear sense of the resource. However, it never states a verb or that this is an aggregate/month-summary tool, and it does not distinguish itself from siblings like working_days, next_bank_holidays, or tax_deadlines that appear to overlap. The cryptic 'PRO.' prefix adds no clarity.

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

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

There is no guidance on when to pick this tool over working_days, next_bank_holidays, tax_deadlines, or due_date, which cover adjacent ground. The 'PRO' marker hints at a subscription gate but is never explained, and there is no mention of when the access_token is required or what happens without 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, and it does disclose two valuable traits: this is a paid PRO call ($0.01) and it fans out across three named sources. It does not state rate limits, whether the token is mandatory on every call, or how results are combined or ordered across sources.

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

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

A single dense sentence with zero filler: cost is front-loaded, then the capability, then the source breakdown. Every clause carries information an agent needs.

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

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

With no output schema and no annotations, listing the three constituent sources does most of the work of explaining what comes back. The remaining gaps are the undocumented 'days' parameter and the auth flow, which are moderate rather than blocking given the token param's own schema description.

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 only 25% (only access_token is documented), so the description must compensate. It does clarify query as 'a company or topic' and uk_only as 'UK outlets only', but 'days' is never explained — whether it is a lookback window, and in what unit — leaving a required-looking semantic gap.

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

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

States a specific verb and resource ('One-call briefing on a company or topic') and enumerates exactly what the briefing contains: GDELT news, Hacker News discussion, Wikipedia background. That aggregate-output framing implicitly separates it from the single-source siblings (news_search, news_quick, tech_news_search), but no sibling is named 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?

'One-call briefing' implies the aggregate use case versus a plain search, and 'optionally UK outlets only' hints at the geographic variant. However, there is no explicit when-to-use, no guidance on choosing this over news_search/news_quick/tech_news_search, and no mention of prerequisites such as requiring a subscriber token.

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 well: it discloses that it is free, needs no key, returns top Wikipedia matches with summaries, and limits HN stories to the last 30 days. It does not explicitly state read-only behavior or result limits beyond 'top,' but 'lookup' strongly implies a safe read 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?

A single compact sentence with the most important qualifiers front-loaded: FREE, no key, sources, and recency. Every element 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?

For a simple one-parameter lookup tool with no annotations or output schema, the description is mostly complete: it covers pricing, auth, data sources, recency, and return content. It could be fuller by specifying expected result counts or clarifying the exact output shape, but it is sufficient for correct invocation.

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

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

Schema coverage is 0% and there is one required parameter. The description adds some meaning by saying the query is 'for a topic,' which tells the agent what to supply, but it does not provide format examples or clarify whether the topic should be a keyword, phrase, or entity 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?

The description gives a specific verb and resource: quick news and facts lookup for a topic, using Wikipedia and Hacker News. It distinguishes itself somewhat through 'quick' and named sources, but does not explicitly contrast with siblings like news_search or facts_search.

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 implies usage through 'quick' and 'top matches,' suggesting a shallow lookup versus deeper searches, but it never states when to use this instead of news_search, facts_search, or news_briefing. The 30-day recency window is useful context, though not a usage rule.

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 discloses unusually useful traits: a per-call cost of $0.01, the upstream source (GDELT DOC 2.0), language breadth (65+ languages), the result fields, and bounds/defaults on the main knobs (days 1-90 default 7, max <=50). It omits rate limits, ranking/ordering behavior and what happens on empty results.

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 blocks, cost and capability front-loaded, then a tight options list with defaults and bounds inline. No sentence is filler and the numeric constraints are attached directly to their parameter names.

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 6-parameter search tool with no output schema and no annotations, the description explicitly enumerates the returned fields, which removes the need for an output schema. It stops short of covering authentication mechanics (only in the schema) and error/empty-result behavior.

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

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

Schema description coverage is only 17% (access_token alone), so the description must compensate and largely does: it constrains days to 1-90 with default 7, caps max at 50, gives a lang example ('english'), and explains uk_only by implication. The required 'query' parameter's semantics (topic matching behavior, free-text vs phrase) are left thin.

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 ('Search worldwide online news... for a topic') plus the data provider (GDELT DOC 2.0) and the exact fields returned (headline, URL, outlet domain, time seen, source country). It never names or contrasts against the four news-related siblings (news_quick, news_briefing, tech_news_search), so a 4 rather than a 5.

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

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

The 'PRO ($0.01)' prefix hints that this is a paid variant an agent might trade off against a cheaper sibling, which implies context for when to pick it. But there is no explicit when-to-use/when-not-to-use statement and no named alternative among news_quick, news_briefing or tech_news_search, so usage is only implied.

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

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

No annotations are supplied, so the description carries the full burden. It does disclose cost ("FREE") and the shape of the result (next 3 holidays plus today's working-day status), but says nothing about auth, rate limits, or how the holiday data is returned. For a simple read-only lookup that is a moderate but not severe gap.

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

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

One short sentence, front-loaded with the cost signal and then the payload. Nothing is padded, though "FREE." as a fragment is slightly cryptic without explanation.

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?

A simple single-parameter read tool with no output schema; the description states what it returns and that the region defaults. An agent has enough to call it correctly, with only minor gaps around return format.

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 100% and the region parameter already enumerates england/wales/scotland/northern-ireland with a stated default. The description only implies the region via "for a nation," adding little beyond the schema. Baseline 3 is appropriate.

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 resource and scope: the next 3 UK bank holidays for a chosen nation, plus a working-day flag. An agent knows exactly what data comes back. It does not explicitly distinguish itself from the sibling working_days, which likely overlaps on the working-day portion.

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 content (UK bank holidays by region, working-day check), but there is no explicit when-to-use or when-not-to-use guidance. The sibling working_days tool plausibly covers related ground and the description never routes the agent between them.

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 the paid 'PRO' context and the scope of deadlines returned, but it does not clarify whether the operation is read-only, how authentication/access tokens are required, whether results are paginated, date inclusivity, or the response shape. This is thin for a 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?

The description is a single, front-loaded sentence with no wasted text, and the key purpose and optional extension are stated up front. The leading 'PRO.' is terse and somewhat cryptic, which slightly reduces clarity, but overall it is appropriately sized.

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 three-parameter read-style deadline tool with no output schema and no annotations, the description covers the core purpose and the company_year_end extension adequately. It remains incomplete regarding authentication requirements, return format and whether months defaults or constraints exist, so it is minimally viable rather than fully complete.

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

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

The description adds meaning beyond the schema for two parameters: 'months' is explained as the next N months, and company_year_end is tied to Corporation Tax, CT600 and accounts dates. The access_token parameter is already documented in the schema, and overall the description compensates reasonably well for the 67% schema coverage, though it does not explain constraints on the months value.

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

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

The description clearly identifies the resource and scope: upcoming HMRC and Companies House deadlines for the next N months, plus Corporation Tax, CT600 and accounts dates when company_year_end is supplied. It is specific enough for an agent to understand the tool's purpose, though it does not explicitly distinguish itself from siblings such as due_date or month_planner.

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 implies when to use the tool by framing it around upcoming HMRC and Companies House deadlines, and it notes that adding company_year_end expands results to Corporation Tax, CT600 and accounts dates. However, it does not explicitly state when to choose this over alternatives like due_date or month_planner, nor does it describe any exclusions.

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

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

With no annotations, the description carries the behavioral burden. It does disclose important traits such as the $0.01 cost, Algolia data source, returned fields, default 30-day window, and max result cap of 30. It does not explicitly mention auth requirements or rate limits in the description, though the access_token parameter is documented in the 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?

The description is compact and front-loaded with the cost and core action. Every phrase adds useful information: data source, search target, return fields, and option constraints.

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 six-parameter search tool with no annotations and no output schema, the description provides enough detail to invoke it correctly: purpose, cost, returned fields, defaults, sort options, and result cap. It falls short of full completeness by omitting explicit sibling routing and auth/quota behavior from the description itself.

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 only 17%, so the description must compensate, and it largely does. It explains that query is the search subject, days defaults to 30, sort accepts 'relevance' or 'recent', and max is capped at 30; min_points is implied and access_token is covered only by 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?

The description uses a specific verb and resource: search Hacker News stories via Algolia for a company, product, or topic. It also distinguishes the scope from generic news search by naming Hacker News and Algolia.

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 implies the tool is for finding Hacker News coverage of a company, product, or topic, which gives useful context. However, it does not explicitly compare against siblings like news_search, news_quick, or news_briefing, nor does it state when not to use this tool.

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

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

With no annotations, the description carries the full burden; it does disclose the core behavioral rule (excludes weekends and nation-specific bank holidays), which is valuable. It omits auth/premium behavior implied by 'PRO' and the access_token parameter, error behavior for unsupported regions, and whether the count is inclusive of 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?

A single tight sentence with the resource and rule front-loaded and no filler. The leading 'PRO' token is unexplained jargon that consumes attention without conveying actionable meaning.

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

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

For a simple two-required-parameter calculation tool with no output schema and no annotations, the description covers the what but not the return type, date format, or subscription requirement. It is minimally viable but leaves gaps an agent must guess at before calling.

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 50% – region and access_token are documented in the schema, while 'from' and 'to' have no description at all. The prose implies 'for the nation' maps to the region parameter and that the range is date-based, but it never gives a date format, leaving a real ambiguity the schema does not resolve.

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 ('Count UK working days between two dates') plus the exclusion rule, which makes it clearly distinct from siblings like next_bank_holidays or due_date. It does not explicitly name the sibling it replaces, so a 5 is not warranted.

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 choose this over next_bank_holidays, due_date, or month_planner, and no prerequisites or exclusions are given. The only usage signal is an unexplained 'PRO' tag, which does not tell an agent whether the tool requires a subscription to call.

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