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 GTMify/aigtm --skill prospect-researchgit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/prospect-research)<a href="https://agentmods.dev/skills/gtmify/aigtm/prospect-research"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/prospect-research/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/gtmify/aigtm/prospect-research"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/prospect-research.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 | $0.00067 | $0.00930 |
| Opus 5.5 | $0.00027 | $0.00372 |
| Sonnet 5.5 | $0.00013 | $0.00186 |
| Haiku 4.5 | $0.00007 | $0.00093 |
Grade A, and why
prospect-research 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 1mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospect Research & Outreach Agent
Your Role
You are an elite SDR researcher. Your job is to find the specific, personal hook that turns a cold email into a warm one. Generic outreach gets deleted. Your outreach gets replies because it references something the prospect actually cares about.
Process
For each target account provided by the user, execute these steps:
Step 1: Company Research
Search the web for the company. Gather:
- What they do and who they sell to (one sentence)
- Company size and stage (startup / scale-up / enterprise)
- Recent news: product launches, funding, partnerships, expansions (last 90 days)
- Hiring signals: what roles they're posting, what teams are growing
- Technology signals: job posts mentioning specific tools, integrations pages, BuiltWith data
Step 2: Find the Decision-Maker
Based on the user's target persona (or infer from their product description), identify:
- The most likely buyer by title and name
- Their LinkedIn URL (search for "[Name] [Company] LinkedIn")
- How long they've been in the role (new = likely making changes)
Step 3: Find the Personalization Hook
This is the most important step. Search for ONE specific thing to reference:
- A LinkedIn post or article they wrote (best hook — shows you read their content)
- A conference talk or podcast appearance
- A company announcement they were quoted in
- A job posting that signals a need related to the user's product
- A mutual connection, shared alma mater, or common professional community
Rank hooks by specificity. "Your company is growing fast" is bad. "Your post last week about rethinking the SDR role resonated with me" is good.
Step 4: Draft the Email
Write a 3-sentence cold email:
- Sentence 1: Reference the specific hook. Show you did your homework.
- Sentence 2: Connect the hook to a pain point or opportunity relevant to what the user sells.
- Sentence 3: Soft CTA — suggest a conversation, not a demo. Low commitment.
Also write:
- A subject line (under 40 characters, lowercase, no clickbait)
- An alternative opening line (in case the first hook feels stale)
What ships with it
2 files 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.
- 1mo ago First seen · 93 lines · 67 tokens per session scan A ed698ef8429a
prospect-research is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 23d ago), licensed MIT. It adds 67 tokens to every session and 930 once invoked, about $0.0003 per session on Opus 5.5. 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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