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 opusforge/gorilla-mcp --skill gorilla-lead-findergit clone --depth 1 https://github.com/opusforge/gorilla-mcpWrote 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/opusforge/gorilla-mcp/gorilla-lead-finder)<a href="https://agentmods.dev/skills/opusforge/gorilla-mcp/gorilla-lead-finder"><img src="https://agentmods.dev/badge/skills/opusforge/gorilla-mcp/gorilla-lead-finder/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/opusforge/gorilla-mcp/gorilla-lead-finder"><img src="https://agentmods.dev/badge/skills/opusforge/gorilla-mcp/gorilla-lead-finder.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 | $0.00066 | $0.01386 |
| Opus 5 | $0.00033 | $0.00693 |
| Sonnet 5 | $0.00013 | $0.00277 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
gorilla-lead-finder 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 9d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gorilla Lead Finder
This skill helps solo founders find their first paying users by surfacing real social posts where people are actively describing the problem the founder's SaaS solves. The skill drives Gorilla's MCP server, which searches five platforms in parallel, scores every post by buying intent, and drafts outreach messages tuned to each platform's tone.
When to Use This Skill
- You just shipped a SaaS product and need your first 10 paying users.
- You want to validate an idea before building, by finding people already asking for what you'd build.
- You need to know which social platform your customers actually live on, before committing to a channel.
- You want ranked outreach targets with personalised drafts ready to send.
- You are doing competitive research and want intent signals on a competitor's audience.
What This Skill Does
- Sharpens the idea: Asks the founder five clarifying questions about their ICP, audience pain, and the alternatives users currently rely on.
- Searches five platforms at once: Pulls recent posts from Reddit, X, YouTube, LinkedIn, and Bluesky where people describe the relevant problem. LinkedIn is a paid-plan source; the free tier covers the other four.
- Scores by buying intent: Returns each lead with an intent score from 0 to 1. HIGH (≥0.7), MED (0.4 to 0.69), LOW (<0.4).
- Buckets by category: ACTIVE_SEARCH, PAIN_OR_FRUSTRATION, SWITCHING, COMPARISON, FEATURE_GAP, COMPETITOR, TUTORIAL, DISCUSSION. Each bucket gets a different outreach register.
- Drafts platform-tuned outreach: For each lead the founder picks, generates a Reddit-paragraph, X-reply, YouTube-comment, LinkedIn reply, or Bluesky reply that follows that platform's conventions.
- Plans the funnel: Returns a Week-1 outreach cadence (sends per day per channel, follow-up windows, action register per category bucket).
How to Use
Setup
The skill calls the Gorilla MCP server. Install it once:
npx -y @usegorilla/mcp
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.
- 9d ago First seen · 118 lines · 66 tokens per session scan A 7b616c04700b
gorilla-lead-finder is a skill published in the GitHub repository opusforge/gorilla-mcp (3 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 1,386 once invoked, about $0.0003 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 2026-08-31.
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