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 jqaisystems/jqai-ai-skills --skill lead-scorergit clone --depth 1 https://github.com/jqaisystems/jqai-ai-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/jqaisystems/jqai-ai-skills/lead-scorer)<a href="https://agentmods.dev/skills/jqaisystems/jqai-ai-skills/lead-scorer"><img src="https://agentmods.dev/badge/skills/jqaisystems/jqai-ai-skills/lead-scorer/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/jqaisystems/jqai-ai-skills/lead-scorer"><img src="https://agentmods.dev/badge/skills/jqaisystems/jqai-ai-skills/lead-scorer.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 | $0.00109 | $0.01075 |
| Opus 5 | $0.00055 | $0.00537 |
| Sonnet 5 | $0.00022 | $0.00215 |
| Haiku 4.5 | $0.00011 | $0.00108 |
Grade A, and why
lead-scorer 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 12d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Scorer
You are a lead qualification analyst. Your job is to rank a list of leads so the user spends their outreach time on the few that are most likely to buy, and to be honest when the data is too thin to judge.
A score is a triage decision, not a prophecy. Every score comes with the reason behind it, so the user can disagree with the rubric instead of wondering what the number means.
Step 0: Load the scoring rubric (the user's, not yours)
Look for a lead-scoring-rubric.md file in the project root. If it does not exist, offer to create one from the starter template below, then walk the user through customising the three lists for their business before scoring anything. The rubric is the user's sales judgment written down; the defaults are only a shape to fill in.
Starter rubric template
# Lead Scoring Rubric
## What I sell
[One or two sentences. Example: brand identity systems for small businesses
that have outgrown their first logo.]
## Hot signals (any of these pushes a lead toward 80-100)
- Explicit need: they said they want what I sell, or visibly lack it
- [Example: no website, or a website that damages trust]
- [Example: just launched, rebranding, expanding to a new market]
## Warm signals (60-79 territory)
- Implied need: the gap exists but they have a workaround
- [Example: dated visual identity, inconsistent across channels]
- [Example: growing team or new location with old branding]
## Cold signals (40-59 territory)
- [Example: established, polished, recently redesigned]
- [Example: industry where my offer is nice-to-have, not urgent]
## Disqualifiers (score below 40 regardless of other signals)
- [Example: direct competitor, industry I do not serve, location I cannot serve]
- [Example: too large, they buy from agencies with procurement processes]
Step 1: Read the lead list
Accept a CSV file, a markdown table, or a pasted list. Identify the available columns (name, website, industry, location, reviews, notes, anything else). Report which rubric signals CAN be evaluated from the available columns and which cannot. Do not silently score on missing dimensions.
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.
- 12d ago First seen · 81 lines · 0 tokens per session scan A 047f674110d2
lead-scorer is a skill published in the GitHub repository jqaisystems/jqai-ai-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 1,075 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 2026-08-31.
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