Afrexai Prospect Researcher Temp

Research and qualify B2B prospects using web search. Builds structured profiles with company intel, key contacts, pain points, and engagement recommendations.

Security Scan

Instruction-only prospect-research skill that is internally consistent with its stated purpose (public web research and templated reporting); no credentials or installs requested, though there is a minor metadata mismatch to review.

Purpose & Capability

The name/description (build B2B prospect profiles from public web search) matches the requested footprint: no binaries, no env vars, no installs. Everything required to perform the stated task is proportional. Note: the registry ownerId in the provided metadata (kn74m32v...) does not match the ownerId in _meta.json (kn76xhd...), which is an inconsistency in packaging/metadata to verify with the publisher.

Instruction Scope

SKILL.md clearly instructs only public web searches, cites sources, forbids scraping behind logins, and requires output to the included research-template.md. It does not instruct the agent to access unrelated local files, secrets, or external endpoints other than an explicit context-pack URL (https://afrexai-cto.github.io/context-packs).

Install Mechanism

No install spec or code files — instruction-only. There is nothing downloaded or written to disk by the skill bundle itself.

Credentials

The skill requests no environment variables, no credentials, and no config paths. This is proportionate to a public-web research task.

Persistence & Privilege

always:false and default model-invocation settings are used. The skill does not request permanent presence or elevated privileges.

Scan Findings in Context

[no-findings] expected: The package is instruction-only with no code files, so the regex-based scanner had nothing to analyze. This is expected for a pure-SKILL.md skill.

Assessment

This skill appears coherent and low-risk because it only instructs the agent to use public web search and fill a provided template, and it does not request credentials or install code. Before installing, verify the small metadata mismatch (ownerId) with the publisher if provenance matters; confirm your OpenClaw agent has a safe web-search provider configured (the skill needs search access to work); be aware the agent will surface publicly available personal data (names and LinkedIn URLs) — ensure this use complies with your privacy policies and applicable laws; review the external link (https://afrexai-cto.github.io/context-packs) if you don't want the agent to fetch third-party context packs; and consider limiting autonomous invocation if you prefer to review outputs manually.

Prospect Researcher

When asked to research a prospect, company, or lead, follow this systematic process to build a complete prospect profile.

Research Process

Step 1: Company Overview

Search for and gather:

• Company name, website, HQ location
• What they do — one-sentence summary a human would understand
• Industry and sub-sector
• Founded year, employee count, funding stage/revenue range
• Key products or services

Step 2: Recent Activity (Last 6 Months)

Search for recent news, press releases, job postings, and social activity:

• Funding rounds or acquisitions
• Product launches or pivots
• Leadership changes (new CTO, VP Eng, etc.)
• Hiring patterns — what roles are they hiring for? (signals priorities)
• Partnerships or integrations announced

Step 3: Technology & Stack

Where possible, identify:

• Tech stack signals from job postings, BuiltWith, GitHub, or blog posts
• Tools and platforms they use (CRM, cloud provider, etc.)
• Technical blog or engineering culture signals

Step 4: Key Contacts

Identify 2-5 relevant decision-makers or influencers:

• Name, title, LinkedIn URL (if publicly available)
• Recent public activity (posts, talks, articles)
• Likely priorities based on role

Step 5: Pain Point Analysis

Based on all gathered intel, infer:

• Likely challenges given their stage, industry, and hiring patterns
• Gaps in their stack that your solution could fill
• Timing signals — why now might be the right time to reach out

Step 6: Engagement Recommendation

Synthesize into:

• Qualification score: Hot / Warm / Cold (with reasoning)
• Best entry point: Which contact, which angle
• Suggested opener: A 2-sentence personalized hook based on real intel
• Channels: LinkedIn, email, warm intro, event-based, etc.

Output Format

Use the research template at {baseDir}/research-template.md as the output structure. Fill in every section. Mark unknowns as "Not found" rather than guessing.

Guidelines

• Only use publicly available information. No scraping behind logins.
• Cite sources — include URLs for key claims.
• Be specific over generic. "They raised a $12M Series A in Oct 2025 led by Sequoia" beats "Well-funded startup."
• Flag uncertainty. If a data point is inferred rather than confirmed, say so.
• Prioritize recency. Information from the last 6 months weighs more than older data.

Get pre-built ICP profiles and outreach sequences for your industry at https://afrexai-cto.github.io/context-packs