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Buy credits

topup_credits

Prepare a top-up of the prepaid credit balance and return the hosted payment link. Nothing is charged by this call: hand payment_url to the user, the payment happens there, and they approve the amount on that page. When the user names an amount, that amount wins: pass it as amount, exactly the number they said. Amounts are always in the wallet currency of the account, which get_credits gives: if they name another currency, tell them, never convert one currency into another yourself. When they leave it to you, take one of the amounts get_credits already suggests in suggested_topups[] and pass its amount_minor: they are derived from what this account consumes, they clear the floor, and each says the runway it buys in covers_months. Name the one you picked and what it covers. Nothing to compute, and nothing to convert. Send one of the two, never both. The minimum top-up is 10.00 (1000 minor units). Once paid, the balance updates on its own and paused trackers resume.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountNoCredits to buy, in MAJOR units of the wallet currency: what a person says. 50 means 50.00, and 12.5 means 12.50. Use this one when the user names the amount, exactly as they said it. Minimum 10.00.
amount_minorNoCredits to buy, in MINOR units of the wallet currency: 5000 means 50.00. Use this one when you compute the amount from the cost grid, which is in minor units too. Minimum 1000.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations are minimal (readOnly=false, not idempotent), so the description carries the burden. It transparently discloses that nothing is charged by this call, payment happens at the hosted link where the user approves the amount, balance updates automatically after payment, and paused trackers resume. These are significant behavioral disclosures beyond what the annotations provide.

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

Conciseness4/5

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

The description is somewhat long but every sentence carries functional decision guidance. It's front-loaded with the core purpose and payment behavior first, then param selection rules, then the minimum. While dense, the content justifies its length; a rare case where verbosity serves the agent's decision-making.

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?

The tool involves money handling and has no output schema, so the description must cover return behavior (payment_url, hosted payment link) and the post-payment state changes. It covers currency handling, minimums, suggestion-sourcing, and mutual exclusivity of params. Given the stakes (financial transaction preparation), this is thorough and complete for a prepaid top-up flow.

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% with rich descriptions for both parameters (major vs minor units, examples like 50→50.00, 5000→50.00). The description adds decision guidance not in the schema: when to send which parameter, that they're mutually exclusive, and that amount should match exactly what the user said. This adds genuine routing value beyond the schema.

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 clearly states the verb (prepare top-up), the resource (prepaid credit balance), and the mechanism (returns hosted payment link). It distinguishes itself from siblings by being the only tool that handles payment/prepaid credits, and explicitly clarifies that nothing is charged by this call—a non-obvious behavioral detail that differentiates it well.

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?

Excellent guidance: explicitly states when to pass `amount` (when the user names an amount) vs `amount_minor` (when the user leaves it to you and you pick from suggested_topups from get_credits). It names the alternative source (get_credits), gives exclusions (never convert currencies, never compute, never send both), and references the sibling get_credits in a helpful way. Also states the minimum.

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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TDQS

A4/5.0
Disambiguation4/5

Each tool maps to a distinct resource and action, and the descriptions go out of their way to separate near-neighbor concepts like surfaces vs corroborations and score series vs raw responses. A few related pairs (get_results/get_responses, get_credits/get_usage, create_surface/create_corroboration) could still be confused at a glance, so it is not a perfect 5.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun snake_case pattern across all 67 tools, with clear families like create_, update_, get_, list_, archive_, restore_, and delete_. Minor quirks such as topup_credits as one word do not break the overall uniformity.

Tool Count1/5

67 tools is an extreme count for a single MCP server, even for a broad brand-monitoring domain. The surface is bloated with lifecycle variants per entity, and the sheer number makes the server hard to navigate and prompt against.

Completeness5/5

The server covers full lifecycles for projects, trackers, surfaces, corroborations, quests, logbook entries, keyword discoveries, competitor scans, link targets, sources, support, and billing. Archive/restore and soft-delete paths prevent dead ends, and nearly every obvious workflow has a corresponding tool.

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