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 koinod/koino-skills --skill prospect-researchgit clone --depth 1 https://github.com/koinod/koino-skillsWrote 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/koinod/koino-skills/prospect-research)<a href="https://agentmods.dev/skills/koinod/koino-skills/prospect-research"><img src="https://agentmods.dev/badge/skills/koinod/koino-skills/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/koinod/koino-skills/prospect-research"><img src="https://agentmods.dev/badge/skills/koinod/koino-skills/prospect-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.01511 |
| Opus 5 | $0.00000 | $0.00756 |
| Sonnet 5 | $0.00000 | $0.00302 |
| Haiku 4.5 | $0.00000 | $0.00151 |
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 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospect Research
Research any company and generate a structured intelligence profile in 60 seconds.
name: prospect-research version: 1.0.0 description: Research any company and generate a structured intelligence profile author: KOINO Capital tags: [sales, research, prospecting]
Description
Prospect Research takes a company name and produces a full intelligence dossier — industry, team size, services, tech stack, funding, recent news, and strategic angles. Everything a seller needs before the first call, generated in under a minute.
Stop spending 20 minutes per prospect on LinkedIn and Crunchbase. This skill does the homework so you can focus on the conversation.
Activation
This skill activates when:
- The user wants to research a company before a sales call
- The user provides a company name and wants an intelligence profile
- The user asks for a prospect dossier, company research, or pre-call prep
- The user mentions "research", "profile", "look up", or "what do we know about"
Trigger phrases: "research this company", "prospect research", "look up", "company profile", "pre-call research", "tell me about [company]", "dossier on"
Instructions
When the user provides a company name (and optionally a URL, contact name, or industry hint):
Step 1: Gather Intelligence
Use web search to find:
- Company website — homepage, about page, team page, careers page, blog
- LinkedIn — company page, employee count, recent posts
- Crunchbase / PitchBook — funding, investors, revenue estimates
- News — press releases, articles, mentions from last 90 days
- Tech stack clues — job postings (what tools they hire for), BuiltWith data, integrations mentioned
- Social presence — Twitter/X, YouTube, podcast appearances
- Reviews — G2, Glassdoor, Google Reviews if B2C
Step 2: Generate the Profile
Output the following structured markdown:
# [Company Name] — Prospect Intelligence Profile
**Generated**: [date]
**Confidence Level**: [High / Medium / Low] (based on data availability)
---
## Company Overview
| Field | Detail |
|-------|--------|
| **Full Name** | [Legal name if found] |
| **Website** | [URL] |
| **Industry** | [Primary industry + sub-segment] |
| **Founded** | [Year] |
| **Headquarters** | [City, State/Country] |
| **Team Size** | [Estimate with source — LinkedIn, careers page, etc.] |
| **Revenue Estimate** | [Range if available] |
| **Funding** | [Total raised, last round, investors] |
| **Business Model** | [B2B / B2C / B2B2C, SaaS / Services / Product, etc.] |
## What They Do
[2-3 sentence plain-English summary. No jargon. What problem do they solve, for whom?]
## Products & Services
- [Product/service 1] — [one-line description]
- [Product/service 2] — [one-line description]
- [etc.]
## Tech Stack (observed or inferred)
| Category | Tools |
|----------|-------|
| **CRM** | [e.g., Salesforce, HubSpot] |
| **Marketing** | [e.g., Marketo, Mailchimp] |
| **Engineering** | [e.g., React, AWS, Python] |
| **Analytics** | [e.g., Mixpanel, GA4] |
| **Other** | [Anything notable] |
*Sources: job postings, integrations page, BuiltWith, etc.*
## Key People
| Name | Title | Notes |
|------|-------|-------|
| [Name] | [Title] | [Relevant detail — LinkedIn post, podcast appearance, quote] |
## Recent News & Activity (last 90 days)
- [Date] — [Headline + 1-sentence summary + source link]
- [Date] — [Headline + 1-sentence summary + source link]
- [Date] — [Headline + 1-sentence summary + source link]
## Strategic Angles (for outreach)
### Pain Points (likely)
1. [Inferred pain point based on industry + company stage + hiring patterns]
2. [Second pain point]
3. [Third pain point]
### Conversation Starters
- "[Reference to recent news or LinkedIn post] — how is that affecting [X]?"
- "[Industry trend] is hitting companies your size hard. How are you handling [specific aspect]?"
- "[Competitor] just [did something]. Does that change anything for your team?"
### Timing Signals
- [Are they hiring? (growth mode)]
- [Did they just raise? (spending mode)]
- [Leadership change? (new priorities)]
- [Negative reviews? (pain is public)]
## Competitive Landscape
| Competitor | How They Differ |
|------------|----------------|
| [Competitor 1] | [Key differentiator] |
| [Competitor 2] | [Key differentiator] |
## Pre-Call Checklist
- [ ] Review their LinkedIn company page
- [ ] Check the contact's recent LinkedIn posts
- [ ] Identify one specific thing to reference in opening
- [ ] Prepare 2-3 questions based on pain points above
- [ ] Have a relevant case study ready
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 · 170 lines · 0 tokens per session scan A 1cdf9ee41a7d
prospect-research is a skill published in the GitHub repository koinod/koino-skills (8 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,511 tokens. 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 2026-08-31.
Other skills, from other repositories
capabilities
Your capability catalog — read this at boot. Lists the temporal date-range skills and the external integrations (reached via the loopback broker) available to you as a spawned worker, and exactly how to call each. Read-only. Consult it whenever you're unsure what tools/integrations you have or how to invoke them.
temporal
Resolve ANY named time window — today, yesterday, thisWeek, lastWeek, last7Days, last30Days, last90Days, thisMonth, lastMonth, thisQuarter, lastQuarter, thisYear, lastYear, last12Months — or an arbitrary range (lastNdays / lastNweeks / lastNmonths) to a concrete ISO date range relative to your run time. Read-only: no…
last30Days
Resolve "last30Days" to a concrete ISO date range relative to your run time — a rolling 30-day window ending today. Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a "last 30 days" / trailing-month task…
md-audit
Read-only code quality audit — scan the current working directory for common issues (bugs, dead code, security hotspots, missing error handling) and return a prioritised findings report. No files are edited. Use when asked to "audit the code", "quick audit", "find issues", "code scan", or "what's wrong with this…
thisQuarter
Resolve "thisQuarter" to a concrete ISO date range relative to your run time — this quarter so far (quarter start → today). Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a quarter-to-date task (QTD…
md-hive-sync
Munder Difflin hive sync — runs the start-of-task hive protocol steps: reads memory.md, checks inbox/ for new messages, and reminds you to record durable facts in memory.md and write coordination files before ending. Use when asked to "sync with the hive", "check my inbox", "hive status", or "hive sync". Proactively…