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open_interest

Requires a ChainHelix API key as bearer token, or 2 cents per call paid over Binance b402 in USDT, USDC, USD1 or U on BNB Smart Chain, or over x402 in USDC on the Base network. Open interest per chain: latest value, the value at the start of the window, change in percent, high and low inside the window and a sampled series. window in hours, default 24, max 720. Omit chain for all nine

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNo
windowNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations available, the description carries the transparency burden and handles it well: it discloses the required ChainHelix API key/bearer or per-call fee, describes the output data shape in detail, and explains default window and chains. It could add response format or rate-limit details, but no contradictory or unclear safety behavior exists.

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

Conciseness3/5

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

Every sentence carries relevant information, but the long billing phrase at the start delays the core purpose and the output details are densely packed into comma-separated clauses. The description is compact, but not as front-loaded or scannable as it should be.

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

Completeness4/5

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

For a simple, non-destructive fetch tool with no output schema, the description covers the most important required details: auth/payment, output fields, chain selection, and window defaults. The main missing piece is the definition of 'sampled series' frequency and the exact response format, but the tool remains callably complete.

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 input schema only lists chain and window without descriptions, so the description adds significant meaning: it specifies window units, default, maximum, and the behavior of omitting chain. The chain enum values themselves are still left to the schema, but the description compensates for the main conceptual gaps.

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

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool as open interest per chain and enumerates the exact returned fields: latest value, start-of-window value, change percent, high, low, and a sampled series. It lacks a strong verb like 'returns' or 'gets,' and it does not explicitly contrast with sibling tools, but the resource and output are unambiguous.

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

Usage Guidelines3/5

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

The description gives operational guidance such as 'window in hours, default 24, max 720' and 'Omit chain for all nine,' plus an explicit authentication or payment requirement. However, it does not say when to prefer or avoid this tool versus related sibling metrics tools, so the usage context is mostly implied rather than stated.

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

C2.9/5.0
Disambiguation2/5

Several tools occupy nearly the same territory: market_state, situation_report, and deep_report all present overlapping per-chain market analysis at different comprehensiveness levels. attest_spec and proof_spec are also near-identical, and attest_status, attestation_stats, and list_attestations use similar attestation vocabulary. Most data tools have unique jobs, but the overlapping report and verification tiers create real misselection risk.

Naming Consistency3/5

The server consistently uses snake_case but mixes noun-style data endpoints like prices and wall_map with command-style actions like attest, buy_key, and verify_reveal. Report names are also uneven: market_state, situation_report, and deep_report signal only vague depth differences. The set is readable but does not follow a single predictable convention.

Tool Count2/5

With 29 tools, this exceeds the heavy threshold and spans roughly four distinct functional areas: market data, attestation, key management, and webhooks. Each tool may earn its place individually, but the overall menu is too large for one MCP server; splitting it into data and attestation/administration servers would be clearer.

Completeness4/5

The attestation lifecycle is well covered with creation, status, listing, reveals, stats, and independent verification, and the key purchase and webhook workflows are also complete. The main gaps are historical-depth data, explicit key revocation, and a direct hire action despite hireable agents being listed, but agents can generally work around these. Core workflows do not dead-end.

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