Skip to main content
Glama

signals.intent_feed

Read-onlyIdempotent

Real-Time B2B Buying Intent & Web3 RFP Stream: Streams verified high-budget software and crypto buyer signals with confidence scoring and pre-drafted outreach angles. (Price: $0.995 USDC via x402 on Base/Solana)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesCategory filter for buyer intent leads.
minBudgetUsdNoMinimum stated budget threshold in USD.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesDetailed result, report, diff, or analysis output
statusYesExecution status of the micro-service (success/error)
timestampNoUnix timestamp of execution
monetizationNo

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds useful behavioral context by mentioning confidence scoring, pre-drafted outreach angles, and the $0.995 USDC price via x402, which an agent would not otherwise know. No contradiction exists between the description and annotations.

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 compact, front-loaded with the core function, and every clause adds value. The pricing parenthetical is somewhat marketing-flavored but still operationally relevant for payment-aware agents. It earns high marks without being bloated.

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?

With two parameters, an output schema, and strong annotations, the description is largely sufficient. It discloses the payment requirement, which is a notable contextual gap otherwise. It does not explain stream lifecycle, pagination, or rate limits, but those are less critical given the output schema and annotation coverage.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline applies. The description does not add any meaning beyond the schema, though the phrase 'high-budget' loosely aligns with minBudgetUsd and the enum conveys the intended category filter. The schema already carries the parameter semantics.

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 uses a specific verb ('Streams') with a clear resource ('B2B buying intent & Web3 RFP') and adds meaningful detail about confidence scoring and pre-drafted outreach angles. It could be sharper in differentiating from siblings like signals.social_momentum, but it is not tautological or vague.

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 implies usage for sales/outbound use cases by stating it streams verified high-budget buyer signals with outreach angles. However, it gives no explicit when-to-use vs. when-not-to-use guidance and does not mention alternatives such as signals.social_momentum, leaving usage context mostly inferential.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation3/5

Most tools target clearly distinct domains, but audit.smart_contract and order.commercial_audit overlap as audit offerings, and order.ast_remediation and remediate.code_patch both generate AST-based remediation patches. The pricing and commercial language help somewhat, but the boundaries are not crisp enough for reliable tool selection.

Naming Consistency4/5

The dot-separated category.snake_case pattern is consistently applied across all 12 tools, making the set easy to scan. However, the category prefixes mix nouns and verbs (analytics, audit, order, remediate, signals), and 'order' is an unclear prefix.

Tool Count4/5

Twelve tools is a reasonable size for a broad paid Web3/DeFi service suite, and each tool represents a distinct revenue-generating capability. The count feels slightly padded by overlapping audit and remediation offerings that could be consolidated.

Completeness3/5

The suite covers a wide range of Web3 tasks including audits, remediation, security checks, routing, analytics, governance simulation, and signals. However, there are no workflow-oriented tools for managing or retrieving past audit/remediation orders, and the broad scope makes the domain boundaries vague.

Resources