Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add WingedGuardian/GENesis-AGI --skill prospect-researchergit clone --depth 1 https://github.com/WingedGuardian/GENesis-AGIWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wingedguardian/genesis-agi/prospect-researcher)<a href="https://agentmods.dev/skills/wingedguardian/genesis-agi/prospect-researcher"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/prospect-researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wingedguardian/genesis-agi/prospect-researcher"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/prospect-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00101 | $0.01501 |
| Opus 5 | $0.00051 | $0.00750 |
| Sonnet 5 | $0.00020 | $0.00300 |
| Haiku 4.5 | $0.00010 | $0.00150 |
Grade A, and why
prospect-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospect Researcher
Purpose
Research a target company or person deeply enough to craft outreach that demonstrates genuine understanding — not generic "I saw your profile and thought we'd be a great fit." Produce actionable intelligence: what they care about, what problems they face, what angle gives the user the best chance of a meaningful response.
Relationship to Other Skills
This skill does the RESEARCH. Other skills use its output:
linkedin-dm-outreach— Uses findings to write personalized messageslead-generation— May trigger this for deep enrichment on hot leadslinkedin-post-writer— May inform commentary posts about the target's spaceosint— Can be invoked for deeper investigation on high-value targets
Research Process
Phase 1: Target Identification
Clarify who and what to research:
target:
type: <company | person | both>
company_name: <if known>
person_name: <if known>
person_role: <if known or "find the right person">
goal: <job_search | client_outreach | networking | partnership | interview_prep>
user_offering: |
<what the user brings to the table — skills, experience, services>
If the user says "find the right person at [company]," determine the right contact based on the user's goal:
- Job search → hiring manager for the relevant team, not HR
- Client outreach → decision-maker for the budget area
- Partnership → someone with strategic authority
- Interview prep → the interviewer(s) if known, otherwise the team lead
Phase 2: Company Intelligence
Gather structured information about the target company:
Public sources (search in this order):
- Company website — about page, careers, blog, press releases
site:linkedin.com/company/[name]— company page, employee count, posts- Recent news — funding, launches, acquisitions, leadership changes
- Job postings — what roles are they hiring for? (reveals priorities)
- Tech stack —
site:stackshare.com,site:builtwith.com, job posting requirements - Competitors — who they compete with, how they differentiate
- Industry reports or analyst coverage if available
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 194 lines · 101 tokens per session scan A 74a26f319d2b
prospect-researcher is a skill published in the GitHub repository WingedGuardian/GENesis-AGI (96 stars, last pushed yesterday), licensed MIT. It adds 101 tokens to every session and 1,501 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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