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Cofferline

by com.cofferline

submit_feedback

Submit a feature request ($1 anti-spam fee, charged to the prepaid balance when funded). Auth required. Payment flow: call once without x_payment — a 402 reply lists the exact EIP-3009 requirements (amount, USDC asset, recipient, EIP-712 domain). Sign a transferWithAuthorization for them outside MCP (this server cannot sign), then call again with x_payment set to the base64 of {x402Version:1, scheme:'exact', network, payload:{signature, authorization}}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesthe request, 20-4000 chars
titleYesshort title, 8-120 chars
x_paymentNobase64 X-PAYMENT value from a previously answered 402 (see description)

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility and does so excellently. It discloses the fee, auth requirement, the server's inability to sign, and the exact structure of the required x_payment payload. This is exemplary transparency for a mutation tool.

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 dense but every sentence earns its place: purpose, fee, auth, and the two-step payment flow are all essential. It's somewhat long but well-structured with a colon and em dash separating the flow steps. Minor improvements could make it easier to parse.

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 description fully covers the complex payment interaction: the failure mode (402), the required signing steps, and the exact payload format. No output schema exists, but the description explains what the user will receive (402 details) and what to do next. There are no gaps in the behavioral contract.

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?

The schema already describes title, body, and x_payment with constraints. The description adds crucial semantics for x_payment by explaining it's the base64 value from the 402 response, which goes beyond the schema's simple description. Given full schema coverage, this extra detail earns above baseline.

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 'Submit a feature request', a specific verb+resource pair. The addition of the $1 anti-spam fee and the payment flow clearly distinguishes this from sibling tools like list_feedback, making the tool's unique purpose unmistakable.

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?

Provides explicit procedural guidance: first call without x_payment to receive a 402 with EIP-3009 requirements, then sign externally and retry with x_payment. This step-by-step instruction fully explains how to use the tool and what the two-phase flow entails.

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

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct resource and action. Within the prediction market domain, prepare vs create vs submit are clearly differentiated by signing model (client-signed vs server-signed). Even similar-sounding tools like check_spend and check_pm_order are unambiguously scoped to general spending vs PM orders, and their descriptions reinforce the boundary.

Naming Consistency5/5

All 47 tools follow a consistent verb_noun pattern with lowercase snake_case. Verbs like get, list, create, cancel, revoke, prepare, submit, set, remove, and poll are used uniformly. There is no mixing of styles or vague verbs like 'process' or 'run', making the surface highly predictable.

Tool Count2/5

47 tools is significantly above the 25-tool threshold for 'too many'. While the server covers a broad and complex domain (prediction markets, policy, delegations), the sheer count makes the surface heavy and potentially overwhelming. Some consolidation (e.g., merging related PM order operations) could reduce cognitive load without sacrificing functionality.

Completeness4/5

The tool set provides comprehensive lifecycle coverage across all major subdomains: authentication, policy versioning, delegation CRUD (prepare/confirm/list/get/revoke/renew), intent management, PM order flow (create/cancel/list/prepare/submit/check), credential management (store/list/revoke), balance and top-up operations, and account-level actions (export, offboard, panic). Minor omissions exist (e.g., no dedicated tool to view a single credential in detail or update an intent), but agents can work around these with existing tools.

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