lead-qualify

lead-qualify is a skill for Claude Code, Codex from runxhq/runx. It costs 24 tokens per session (565 once invoked), scanned A, original, Apache-2.0.

A lead-qualification skill that compares known facts about a person or company with explicit ideal-customer criteria. It reports each criterion as met, not met, or unknown and keeps business fit separate from permission to contact.

In plain words
What is it for?
Use it to assess prospects against mandatory and optional criteria, identify missing evidence, and explain why each assessment was made.
Why use it?
It prevents weak or incomplete information from being treated as proof that a prospect is suitable. It also avoids confusing commercial fit with contact eligibility or consent.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to assess prospects against mandatory and optional criteria, identify missing evidence, and explain why each assessment was made.

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Install with agentmods
npx agentmods add skills/runxhq/runx/lead-qualify
Install

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.

Any agent
npx skills add runxhq/runx --skill lead-qualify
Clone the repo
git clone --depth 1 https://github.com/runxhq/runx

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for lead-qualify

README.md
[![agentmods](https://agentmods.dev/badge/skills/runxhq/runx/lead-qualify/github.svg)](https://agentmods.dev/skills/runxhq/runx/lead-qualify)
Your own site
<a href="https://agentmods.dev/skills/runxhq/runx/lead-qualify"><img src="https://agentmods.dev/badge/skills/runxhq/runx/lead-qualify/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.

agentmods 80×15 button for lead-qualify

Your own site · 80×15
<a href="https://agentmods.dev/skills/runxhq/runx/lead-qualify"><img src="https://agentmods.dev/badge/skills/runxhq/runx/lead-qualify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00565
Opus 5.5 $0.00010 $0.00226
Sonnet 5.5 $0.00005 $0.00113
Haiku 4.5 $0.00002 $0.00056

Measured 5d ago against content hash 498123aa1b6a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lead-qualify 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 5d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (lead-qualify.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/lead-qualify/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lead Qualify

Decide whether one lead meets the actual ICP. Use lead-enrichment for factual context; use this skill for commercial judgment; use cold-outreach for copy. Qualification neither obtains consent nor creates a provider send plan.

Procedure

  1. Supply the enrichment packet, explicit ICP criteria, and a separately sourced contact-eligibility decision. At least one criterion must be mandatory. The eligibility names the subject it decides, with the same ref and kind as the enrichment subject. Eligibility decided for any other subject requests evidence before any criterion is assessed.
  2. Keep missing and conflicting facts visible. Partial enrichment can support a criterion only through its admitted, non-conflicting facts.
  3. Assess every criterion as met, not_met or unknown. Cite exact factual field names for each supported assessment and explain its relevance.
  4. A failed mandatory criterion disqualifies the lead. An unknown mandatory criterion requests evidence. All mandatory criteria met establish fit; optional criteria explain strengths and weaknesses without overriding it.
  5. Return the fit independently from contact eligibility. A good fit with unknown or ineligible contact status remains a hold.

Never replace the supplied ICP with generic scoring. A company title is not buying authority, activity is not consent, and a matched work email is not permission to contact. Do not infer protected or sensitive personal traits.

Result and composition

lead_qualification records the exact enrichment digest, subject, criteria, assessments, contact-eligibility evidence and a bounded next action: prepare_outreach, request_evidence, resolve_contact_policy or stop. Contact eligibility appears only when it was decided for that subject; another subject's eligibility is left out, and its blocker remains. No message, CRM update, enrollment or durable suppression change occurs.

A qualified result is context for cold-outreach#prepare, not send authority. That skill requires its own exact recipient-bound eligibility/suppression input. The selected sending capability performs native approval and delivery. The calling application owns task assignment, refresh, follow-up timing and continuing work.

Read the full file on GitHub · 57 lines

Changes

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.

  1. 5d ago First seen · 57 lines · 24 tokens per session scan A 498123aa1b6a

Subscribe to this mod's changes

lead-qualify is a skill published in the GitHub repository runxhq/runx (103 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 565 once invoked, about $0.0001 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 2026-10-12.