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@writerslogic/ai-agents-mcp

@writerslogic/ai-agents-mcp

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lead_enrichment

Scrapes a company homepage, infers its value proposition and buyer persona, and drafts a targeted B2B cold email tailored to what you sell.

Instructions

Autonomous Lead Enrichment. Scrapes a company homepage, deduces its value proposition and buyer persona, and drafts a targeted B2B cold email.

Cost: 0.50 USDC per call, paid automatically over x402 on Base when AGENT_PRIVATE_KEY is configured and the price is within MAX_USDC_PER_CALL.

Input Schema

NameRequiredDescriptionDefault
urlYesCompany homepage URL; https:// is assumed if omitted.
senderContextNoWhat you sell, used to tailor the pitch.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4/5.0
Behavior4/5

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

Adds substantial context the annotations do not carry: a hard cost of 0.50 USDC per call, automatic x402 payment on Base, a required AGENT_PRIVATE_KEY, and a MAX_USDC_PER_CALL guard. This is exactly the economic and auth behavior an agent needs before invoking a non-idempotent, open-world, paying call, though it does not say what happens when the key is absent or the cap is exceeded.

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?

Two short paragraphs, front-loaded with the capability and followed by the cost/payment constraint. The only waste is the leading 'Autonomous Lead Enrichment', which restates the annotation title without adding information.

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?

No output schema exists, and the description compensates by naming the artifacts produced (value proposition, buyer persona, cold email draft). Combined with cost, payment rail, and key requirement, an agent has enough to decide and invoke correctly.

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 both url and senderContext are already documented in the schema, including the https:// assumption. The description hints at tailoring ('targeted') which loosely relates to senderContext, but adds no format, length, or sourcing guidance beyond the schema.

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?

States specific verbs and resources: scrapes a company homepage, deduces value proposition and buyer persona, and drafts a targeted B2B cold email. The chain of work is concrete enough to separate it from adjacent siblings like company_identity (identification only) or competitor_battlecard (positioning against rivals).

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?

Usage is implied by the pipeline described (homepage URL in, cold email out), so an agent can infer this is a prospecting/outreach tool. However, there is no explicit when-to-use or when-not guidance and no sibling is named as an alternative, leaving the agent to infer selection from the name alone.

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