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Manchester Tonight

Search Manchester Tonight listings

search_listings
Read-onlyIdempotent

Search all regular nights out in Manchester by keyword, area, type and day of the week. Use for questions like "free comedy in Manchester", "which pubs in Stockport have a quiz" or "open mics on Mondays". Results include the day rule (e.g. "Every Tuesday", "1st Thursday of the month").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dayNoOptional day of the week, e.g. monday.
areaNoOptional area: city-centre, northern-quarter, south-manchester, didsbury, west-didsbury, chorlton, stockport, salford, further-out, or a neighbourhood name such as Ancoats, Castlefield, Levenshulme or Heaton Moor.
typeNoOptional type: pub-quizzes, comedy-nights, open-mics, live-music, club-nights, drag or happy-hours. Plain words like "quiz" or "comedy" work too.
limitNoMaximum results (default 40).
queryNoOptional keywords matched against venue, area, type and notes, e.g. "free", "jazz", "SpeedQuizzing".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered, and the description goes beyond them by disclosing what comes back ('Results include the day rule, e.g. Every Tuesday, 1st Thursday of the month'), which is genuinely new information with no output schema to carry it. It still says nothing about match strictness (fuzzy vs exact keyword matching) or result ordering.

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

Conciseness5/5

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

Three sentences: capability first, then concrete example questions, then the notable return field. Nothing is repeated and nothing is padding.

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

Completeness4/5

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

With no output schema, the description accepts the burden of hinting at the return shape and does so via the day-rule sentence, and its usage examples cover the main intent classes. Minor gaps remain around result ordering and matching behavior, but an agent has enough to call this correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter including day, area, type, limit and query is already documented in the schema with examples and enumerations. The description's recital of 'keyword, area, type and day of the week' adds no format or matching semantics beyond that, so the baseline 3 applies.

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

Purpose4/5

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 filter dimensions, which is unambiguous. It implicitly separates itself from seasonal_events and whats_on via the word 'regular' (recurring nights vs one-off events), but never names those siblings explicitly, so an agent must infer the boundary.

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

Usage Guidelines4/5

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') give the agent clear situational context for when to reach for this tool. It stops short of saying when NOT to use it or pointing to whats_on / seasonal_events for one-off events, so the routing guidance is implied rather than explicit.

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

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