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 CALLE-AI/awesome-phone-call-agents --skill ocmanjos-lead-qualifiergit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote 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/calle-ai/awesome-phone-call-agents/ocmanjos-lead-qualifier)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/ocmanjos-lead-qualifier"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/ocmanjos-lead-qualifier/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/calle-ai/awesome-phone-call-agents/ocmanjos-lead-qualifier"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/ocmanjos-lead-qualifier.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 | $0.00040 | $0.00763 |
| Opus 5.5 | $0.00016 | $0.00305 |
| Sonnet 5.5 | $0.00008 | $0.00153 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
ocmanjos-lead-qualifier 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
O.C. Manjos Lead Qualifier
Scores inbound product enquiries (captured via a WhatsApp sales AI into Supabase) against category, price, and recency rules, then places a CALL-E outbound call to qualifying leads to confirm interest and capture delivery or pickup preference.
Use it for
- Following up on high-value product enquiries that went unanswered on WhatsApp within 72 hours
- Confirming customer interest and delivery preference via voice instead of relying on repeat text follow-ups
- Demonstrating a real small-business use case for CALL-E: filtering noisy, free-text enquiry data down to genuinely qualifying leads before spending a call
Do not use it to
- Call numbers not sourced from an explicit customer enquiry
- Call leads marked as already purchased, a known competitor, or opted out
- Guess phone numbers, prices, or product categories - the skill only prices and calls what matches configured rules and real price-sheet data
Setup
- A Supabase table with enquiry records (product_asked, created_at, whatsapp_responded, known_competitor, already_purchased, opted_out)
- A product price sheet (.xlsx) with description, unit price, and sell price columns
- .env with SUPABASE_URL and SUPABASE_ANON_KEY (never commit this file)
- CALL-E CLI authenticated (calle auth login)
How it works
- Pull recent enquiries from Supabase
- Extract a product keyword and variant (e.g. size/phase) from free-text product_asked
- Look up the real sell price from the price sheet, matched by token, not exact phrase
- Score against category/price/recency/disqualifier rules
-
- For qualifying leads, the operator manually runs CALL-E's plan_call via the CLI, reviews the confirm_summary, then runs run_call. This script identifies who to call; it does not itself invoke CALL-E.
Qualification rule (example, tune to your own product line)
IF (category = "Distribution Board" AND value >= 35000) OR (category = "Box/Conduit" AND value >= 2500) OR (category = "Solar/Flood Light" AND value >= 34000) AND enquiry_age <= 72h AND no_whatsapp_response = true AND NOT (known_competitor OR already_purchased OR opted_out) THEN CALL
What ships with it
5 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 · 54 lines · 40 tokens per session scan A e9c1646e2cb0
ocmanjos-lead-qualifier is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 763 once invoked, about $0.0002 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 2026-09-15.
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