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CIPHER x402 — Paid Solana & Crypto Tools

by io.github.cryptomotifs

fred_macro_series

Fetch a Federal Reserve Economic Data (FRED) series by ID — e.g. 'DGS10' (10Y yield), 'WALCL' (Fed balance sheet), 'T10Y2Y' (yield curve). Returns cleaned latest observations. Priced at $0.005 USDC on Base (x402). Pass a signed x402 v2 authorization as the '_payment' argument to unlock the paid response. Without it, the tool returns the 402 accept-list for your wallet to sign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_paymentNoOptional. Signed x402 v2 X-PAYMENT header value (base64-encoded EIP-3009 authorization). If present, forwarded upstream; if absent, tool returns the 402 accept-list.
series_idYesFRED series ID (e.g. 'DGS10', 'WALCL', 'T10Y2Y', 'DFF').

TDQS

A4.3/5.0
Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses that the tool returns 'cleaned latest observations', is priced at $0.005 USDC, and requires a signed x402 authorization. It also explains the behavior without payment (returns 402 accept-list). This is comprehensive for a read operation, though rate limits or error handling are not specified.

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, each earning its place: purpose with examples, return characteristics, and payment mechanism. Information is front-loaded, and there is no redundancy. Efficient and clear.

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

Completeness3/5

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

The description lacks an output schema and does not detail the structure of returned data beyond 'cleaned latest observations'. While the tool is simple, for completeness it could mention typical fields or error handling. It does explain payment flow well, but the return format is vague.

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 description coverage is 100%, but the description adds significant context: examples of series IDs, explanation of the payment flow, and the effect of the '_payment' parameter. This goes beyond the schema's field descriptions, providing practical guidance.

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 tool fetches a FRED series by ID, with examples (e.g., DGS10, WALCL). The verb 'Fetch' and resource 'FRED Economic Data series' are specific, and it is distinct from sibling tools like coinalyze_funding_rates or pubmed_medical_search.

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 indicates when to use the tool (to fetch a FRED series by ID). It provides examples and a pricing note. While it does not explicitly exclude alternatives, given the diverse sibling tools, this clear context is sufficient. No when-not or alternative tools are mentioned.

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

A3.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with detailed descriptions, and there is no functional overlap between any tools, even those in similar domains like geocoding (forward vs reverse) or Solana wallet analysis (general scan vs specific protocol exposure).

Naming Consistency2/5

Tool names follow no consistent pattern: some use verb_noun (check_drift_exposure), others use data source prefix (coinalyze_funding_rates, openfda_adverse_events), and a few use domain prefix (solana_wallet_scan). This mixture of conventions makes it hard to predict naming for similar functions.

Tool Count2/5

The server claims to be for Solana & Crypto but only 6 of 15 tools are crypto-related, while the rest cover unrelated domains like medical, nutrition, and geocoding. This dilutes focus and suggests the tool count is mismatched for the stated purpose.

Completeness2/5

For a server named 'Paid Solana & Crypto Tools', the crypto toolset is incomplete, missing common operations like token swaps, DeFi protocol interactions, or NFT queries. The inclusion of many non-crypto tools does not fill these gaps.

Resources