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public_data_feed

Public attestation data feed JSON records ($0.0001 USDC)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

C2.1/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It usefully discloses the output format (JSON records), access scope (public), and an important side effect (a $0.0001 USDC fee). It does not, however, describe whether records are singular or paginated, any rate limits, or whether any mutation is involved.

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

Conciseness2/5

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

The text is extremely short, but brevity here is under-specification rather than conciseness. It fails to front-load an action or parameter information, and the only sentence does not provide enough operational content to earn its place.

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

Completeness2/5

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

For a one-parameter tool with no output schema, the description still needs to explain what filename means and what the returned JSON looks like. It supplies cost and format but omits the parameter semantics, so the agent cannot reliably invoke it.

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

Parameters1/5

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

The only parameter, filename, has a bare string type with 0% schema description coverage, and the description never mentions it. The agent is given no information about what filenames are expected, where they come from, or what the parameter controls.

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

Purpose3/5

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

The description identifies the resource as a public attestation data feed returning JSON records and notes a cost, which is more specific than the bare tool name. However, it is a noun phrase with no explicit verb (e.g., fetch/list/get), and it does not clarify how this differs from the sibling data_feeds tool.

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

Usage Guidelines1/5

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

There is no guidance about when to use this tool, what inputs are valid, or when to prefer siblings like data_feeds or extract_json. The word 'Public' hints at access scope but provides no actionable usage context.

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

C2.7/5.0
Disambiguation3/5

The tools are largely distinct, but web_scraper and browser_scraper overlap on web page scraping, and data_feeds and public_data_feed are hard to distinguish without more detail. A few descriptions do help separate output formats, but an agent could still misfire.

Naming Consistency3/5

All names use snake_case and are descriptive, but the naming pattern is mixed: deploy_contract and render_screenshot are verb-first, while smart_contract_verifier, base_analytics, and data_feeds are noun phrases. This prevents a predictable verb_noun convention.

Tool Count4/5

Twelve tools is a reasonable count and each has a defined paid purpose. However, the set spans scraping, data feeds, DeFi yields, and smart-contract deployment, so it feels slightly broad for a single server.

Completeness3/5

Core operations exist for scraping, extraction, deployment, verification, and data feeds, but the surface is incomplete for lifecycle workflows: contracts can be deployed but not called/managed, and data feeds cannot be listed or refreshed. The gaps are noticeable but not fatal for independent one-off API calls.

Resources