Manchester Tonight

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds real behavioral context beyond them by disclosing the shape of the response (times, address 'if known', sources, last-checked freshness) despite there being no output schema, which is genuinely 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 verb and resource in a single dense sentence; every clause describes a returned field rather than padding. Slightly list-heavy in its tail but nothing is redundant.

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, the description carries the burden of describing returns and does so competently. It is silent only on edge cases such as an unknown venue name or result limits, which are minor for a single-parameter lookup.

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 the 'venue' parameter is already fully documented as a string with examples. The description nevertheless adds a constraint the schema lacks: the venue must be a single Manchester venue, narrowing the accepted input scope.

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 (Get) and resource (events at one Manchester venue) and enumerates the returned fields (times, address, sources, last-checked). It does not differentiate itself from siblings like seasonal_events or whats_on, whose domains it overlaps by claiming to cover 'seasonal or one-off event' too.

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 only implied: the agent can infer this is the per-venue detail lookup, but the description never says when to pick it over whats_on or search_listings, nor names any alternative or exclusion. Adequate minimum, but no routing 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 declare it is a non-read-only, open-world, idempotent, non-destructive write. The description adds genuine lifecycle context the annotations lack: the plan is persisted only to serve the link and is kept until a month after its last day, and it describes the returned preview card and message variants. It does not clarify whether repeated calls create separate links.

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?

Dense but information-bearing throughout; nearly every clause carries actionable detail (auto-fill rules, message variants, retention). The opening sentence is long and clause-heavy, so it is not maximally front-loaded, but there is little waste.

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

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

No output schema exists, and the description compensates fully by describing the return (short link, preview card, full and short message) and recommending which to offer for a group chat. Combined with the retention window and stop-resolution rules, an agent has everything needed to call and use this tool correctly.

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

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

Schema coverage is 100%, so baseline is 3, but the description adds real semantics beyond the schema: listed venues get area and page auto-filled, a stop without a time inherits the venue's start time that day, and the first stop each day is the meeting point. That is meaningful behavioral meaning layered on top of the field docs.

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: turning a planned night out into a 'Manchester Tonight plan' link with message text. It explicitly names the sibling tools used to gather stops (whats_on, search_listings), so an agent can distinguish this creation tool from the discovery 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 a clear prerequisite and alternative path ('Find the stops first with whats_on or search_listings'), which routes the agent correctly. It does not state when-not to use the tool or what happens if stops are already known, so it falls short of fully explicit 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 readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is fully covered. The description adds only that results include the day rule; it does not discuss pagination behavior or result ordering beyond what the limit parameter implies.

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 purpose and scope, followed by usage examples and return-format note. Every sentence contributes; the examples are slightly verbose but earn their place by clarifying intent.

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 read-only search with no output schema, the description notes that results carry the day rule and the schema fully documents all inputs, so an agent has enough to call it correctly. A brief note on result count or ordering would round it 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?

Schema description coverage is 100%, so each of the five parameters is already documented in detail. The description restates the searchable dimensions but adds no syntax or format detail beyond the schema, matching the baseline 3 for schema-dominant definitions.

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 all regular nights out in Manchester') plus the searchable dimensions (keyword, area, type, day). The word 'regular' implicitly separates it from seasonal_events, but no sibling is named explicitly, so it falls short of the 5-level differentiation.

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

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

Concrete example queries ('free comedy in Manchester', 'which pubs in Stockport have a quiz', 'open mics on Mondays') make the intended use cases vivid and easy to match. However, there is no explicit when-not-to-use guidance or routing to alternatives like whats_on or seasonal_events.

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 the safe read-only, idempotent, non-destructive profile, so the description's added value is its disclosure of scope ('upcoming dated events', Manchester-only) and the result contents (dates, times, prices, ticket link). With no output schema, noting what comes back is genuinely useful context. It stops short of mentioning pagination or result counts, but only counts as a minor gap.

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

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

Three tight sentences: the capability is front-loaded, the example queries sit in the middle, and the return contents close it out. Every sentence 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 one-optional-param read tool with no output schema, the description covers purpose, invocation examples, scoping, and return contents. An agent has everything needed to call it correctly and to know what the results look like.

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 100%, and the single optional 'season' parameter is fully documented in the schema, including accepted synonyms. The description adds nothing about parameter behavior, so the baseline of 3 applies.

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 (upcoming dated seasonal events in Manchester) with concrete instances such as Halloween parties, Christmas markets and panto. The scope is narrower than generic siblings like search_listings or whats_on, though no sibling is named to make the distinction explicit.

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 usage contexts with sample user questions ('Halloween in Manchester', 'Christmas markets dates', 'festive things to do in Manchester'), which tells the agent when this tool is the right pick. It does not state when NOT to use it or route to a named alternative.

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 read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds genuinely new context beyond them: the result shape (time, venue, area, notes, citable link) and the UK-time nuance, which matter because there is no output schema. It does not disclose rate limits or result ordering, which is a minor 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?

Three sentences, front-loaded with the core action and scope before the usage examples and the return-field note. The category enumeration in sentence one is long but does real work distinguishing the tool's coverage, so nothing is clearly 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?

With no output schema and no annotations covering return values, the description usefully compensates by describing the result fields and the citation link. Combined with a fully documented input schema, an agent has nearly everything needed to call and interpret the tool, missing only ordering/pagination expectations for the limit parameter.

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 100%, so area, date, type and limit are all fully documented in the schema itself (including the 4am 'tonight' rule and the seasonal-word behavior). The description adds query-phrasing examples but no parameter detail beyond what the schema already provides, so the baseline 3 applies.

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 specific verb (list) and resource (regular nights out and one-off events) plus the scope (Manchester, UK, on a given date) and enumerates the covered event categories. This is far more specific than the title alone, though it never names or contrasts the overlapping siblings search_listings or seasonal_events, so an agent cannot tell from the description alone which one to prefer.

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 user-question exemplars ("what's on tonight in Manchester", "comedy in the Northern Quarter on Saturday", "quiz in Didsbury tomorrow") that make the intended use case unambiguous. It stops short of stating when NOT to use it versus search_listings or seasonal_events, so there is no explicit exclusion or routing rule.

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