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GrowVib: Social Media Growth

recommend_service

Read-onlyIdempotent

Choose WHICH plan option to order, once you know what to buy and for how many. Use it instead of comparing options yourself from search_catalog or get_service. Takes a service (or a platform plus a goal), a quantity, an audience and a preference. Returns one recommended option plus the cheapest, highest-tier and fastest-listed alternatives. Each pick carries the price per 1000, the total for this quantity, the quantity range it accepts, its quality tier, typed axes such as country or watch length, the listed delivery speed and start window, a sensitive flag marking a deliberate product such as a negative reaction, and short reasons written for the buyer. Branch on the typed fields; the reasons are prose in the requested locale and state only what an option gives, so their absence is never a drawback. One reason states how many independent delivery pools can serve the option, when two or more can: it is a count of the ways we can deliver it, not a promise about any one order, and a pick without it is not worse. The response also says how many options were considered, how many fit, and why the rest fell out (rejected: audience_mismatch, quantity_below_min, quantity_above_max, dominated). It carries quoted_at and catalog_version: the version fingerprints the option data the answer came from, so if you recommend, ask the user, then order, re-call and compare catalog_version to know whether the card changed in between. Prices are live at order time; placing an order re-prices from the same data get_quote does, so treat quoted_at as when this answer was computed, not as a price hold. tradeoffs compares each alternative with the lead as data (price and total deltas, quality steps, listed speed ratio, start bucket delta, max quantity delta, plus gives and costs naming the dimensions it wins and loses on; null means one side lists nothing). Use it to CHOOSE and to explain a choice as what each option gives ("$18.60 less for one tier lower and twice the listed rate"); never present a pick to the user as a percentage more expensive than another. Identify the service by service_id (from search_catalog) OR by platform + goal (the deliverable, e.g. platform "youtube" and goal "short-views" or "followers"). Read-only: it places no order. Pass the returned option_id as service_option_id to get_quote and create_paid_order (this endpoint lists it while the accountless x402 payment channel is on).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoThe deliverable metric key (followers, likes, views, short-views, members, comments, ...). Used with platform when service_id is omitted.
localeNoLanguage of the option labels and the reasons: en (default), fa, ru, uz or id. The typed fields are locale-independent, so pass the user's language freely.
audienceNo"worldwide" (default) for untargeted delivery, or "<axis>:<value>" such as "country:usa" or "emoji:❤️". The response lists the audiences the service serves.
platformNoPlatform key (telegram, instagram, tiktok, youtube, ...). Used with goal when service_id is omitted.
priorityNo"balanced" (default), "cheapest", "quality" or "fastest": which pick leads. fastest ranks on the LISTED delivery rate then start window (the listing's own claims); when no eligible option lists either it falls back to balanced.
quantityYesThe quantity the user wants to order; every pick accepts it.
service_idNoThe service id from search_catalog. Optional when platform and goal are given.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Annotations already mark the tool as readOnly and idempotent, but the description goes much further: it states 'Read-only: it places no order,' clarifies that prices are live at order time and quoted_at is not a price hold, explains the catalog_version mechanism for staleness detection, and details the semantics of the reasons field ('absence is never a drawback'). It also discloses the 'sensitive flag' behavior and the 'tradeoffs' structure. No contradictions with annotations.

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 long but front-loaded with the core purpose and differentiation. Every subsequent sentence adds critical operational detail (return fields, pricing semantics, safety caveats, parameter relationships). Despite its length, there is no redundancy; each section earns its place given the tool's complexity (7 parameters, nuanced behavioral rules).

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?

With no output schema, the description carries the full burden of explaining return values, which it does thoroughly: it lists the recommended option plus three alternatives, the fields each pick carries (price per 1000, total, quantity range, quality tier, typed axes, delivery speed, start window, sensitive flag, reasons), and the response-level fields (quoted_at, catalog_version, considered/fit/rejected counts, tradeoffs). It covers both how to use the result and how to chain it with other tools (pass option_id to get_quote/create_paid_order).

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

Parameters5/5

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

Although schema coverage is 100%, the description adds substantial meaning beyond the schema: it explains the service_id vs platform+goal tradeoff, how priority selects the lead ('fastest ranks on the LISTED delivery rate then start window'), and how audience format works. It also clarifies the relationship between quantity and picks ('every pick accepts it'). These enrich the schema's basic definitions.

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 states a specific verb and resource: 'Choose WHICH plan option to order', and immediately distinguishes it from siblings by saying 'Use it instead of comparing options yourself from search_catalog or get_service.' It also clarifies the input alternatives (service_id or platform+goal), making the tool's role unambiguous.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: 'once you know what to buy and for how many.' It explicitly contrasts with siblings and names the alternative: 'instead of comparing options yourself from search_catalog or get_service.' It also instructs how to use it for choosing and explaining, and warns against certain user presentations ('never present a pick to the user as a percentage more expensive').

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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