Skip to main content
Glama

knowledge-base

by com.tunnelpowered

check_availability

Find out when a business is actually free. Worked out per call against their opening hours, their notice period, their blackout dates and what is already booked — there is no stored list of free times to be out of date. Returns known true with days, each holding slots that carry a start, an end and free. firstFree is the earliest one across the range. Pass time to ask about one exact moment instead of browsing. known false means this business has not set up a calendar and reason names the missing piece. That is "we cannot tell you", never "they are busy" — ask a person instead. A free slot is not a hold. Nothing is reserved until commit_order, and between the two calls someone else can take it. Authentication: none. This tool works with no credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoOptional. How many days to walk, 1 to 14. Defaults to 7.
fromNoOptional. First day to look at, yyyy-mm-dd in the business's own local calendar. Defaults to their today.
kindNoOptional. The `kind` field from the same search result. Defaults to "entity".
slugYesThe `slug` field from a search_businesses result.
timeNoOptional. One exact start time as HH:MM, 24-hour, on the first day of the range. The answer comes back under `asked`, and "not-a-slot-start" means their day divides differently — the free starts are listed beside it.

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the behavioral transparency burden. It discloses real-time calculation (no stale list), the meaning of `known` false ('we cannot tell you, never they are busy'), the 'not-a-slot-start' special case, the non-holding nature of a free slot, and authentication requirements ('Authentication: none'). This is exemplary.

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?

The description is appropriately sized for the tool's complexity; every sentence earns its place. It is front-loaded with the main purpose, then covers computation freshness, return shape, special cases, reservation caveat, and auth, all without repeating schema field descriptions. The structure flows logically from what → how → when → caveats.

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

Completeness5/5

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

Given no output schema and no annotations, the description provides a thorough mental model of the tool. It names the response envelope (`known`, `days`, `slots`, `firstFree`, `asked`, `reason`), explains the false/error case, and relates the tool to `commit_order`, making it complete enough for an agent to know both the call and the interpretation of results.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema for the `time` parameter, explaining its purpose ('ask about one exact moment') and its special response ('not-a-slot-start' with free starts listed beside it). It also frames the `days`/`from` browsing behavior into a coherent model of returned `slots`, which the schema alone does not convey.

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

Purpose5/5

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 ('Find out when a business is actually free') and clearly distinguishes itself from siblings by emphasizing per-call computation against live data (opening hours, notice period, blackout dates, bookings) rather than a stored list. It also clarifies the known-false semantics, making it clear this is an availability lookup, not a reservation or commitment tool.

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?

The description gives explicit guidance on when to use the `time` parameter ('exact moment instead of browsing') and warns that 'Nothing is reserved until commit_order' and 'between the two calls someone else can take it,' steering reservation tasks to a sibling tool. It also advises to ask a person when `known` is false. It stops short of naming alternative tools directly, but the context is clear.

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

All knowledge-base toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but ask_business and ask_business_freeform both serve the core function of asking a question about a listing, which could cause misselection. The detailed descriptions mitigate the overlap, but the similar intent remains a minor ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (ask_, check_, contact_, get_, search_, send_), with only ask_business_freeform adding a modifier that still fits the convention. Naming is predictable and readable.

Tool Count5/5

Nine tools is well-scoped for a knowledge base server, covering discovery (search, get), questioning (ask), asynchronous communication (contact, followup, replies, escalation), and verification. Each tool earns its place without unnecessary bloat.

Completeness5/5

The tool set provides full coverage of the domain: finding businesses, reading profiles, asking structured and freeform questions, escalating unresolved queries, opening and continuing conversations, and checking verification. Poll-based tools handle dead ends explicitly, so there are no obvious gaps.

Resources