lead-magnet-offer-fit

lead-magnet-offer-fit is a skill for Claude Code, Codex from mardab96/b2b-lead-generation-claude-skills. It costs 55 tokens per session (781 once invoked), scanned A, original, MIT.

A review of a B2B lead magnet, a free resource offered in exchange for contact details. It checks whether the resource fits the buyer's stage, addresses a relevant problem, attracts suitable prospects, and supports follow-up.

In plain words
What is it for?
Use it when planning or reviewing a guide, checklist, report, or similar offer, using campaign, form, CRM, and sales data.
Why use it?
It helps explain why many people download a resource but few move toward a sales conversation or purchase.

Skill for Claude CodeCodex

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

Good fit Use it when planning or reviewing a guide, checklist, report, or similar offer, using campaign, form, CRM, and sales data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit
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 mardab96/b2b-lead-generation-claude-skills --skill lead-magnet-offer-fit
Clone the repo
git clone --depth 1 https://github.com/mardab96/b2b-lead-generation-claude-skills

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-magnet-offer-fit

README.md
[![agentmods](https://agentmods.dev/badge/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit/github.svg)](https://agentmods.dev/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit)
Your own site
<a href="https://agentmods.dev/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit"><img src="https://agentmods.dev/badge/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit/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-magnet-offer-fit

Your own site · 80×15
<a href="https://agentmods.dev/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit"><img src="https://agentmods.dev/badge/skills/mardab96/b2b-lead-generation-claude-skills/lead-magnet-offer-fit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 781 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 $0.00055 $0.00781
Opus 5.5 $0.00022 $0.00312
Sonnet 5.5 $0.00011 $0.00156
Haiku 4.5 $0.00006 $0.00078

Measured 2mo ago against content hash 76b6312f5128, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lead-magnet-offer-fit 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 2mo 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.

lead-magnet-offer-fit/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lead Magnet Offer Fit

Use the shared quality bar in ../references/output-standard.md and ../references/skill-design-principles.md when those files are available.

Use this skill when

  • the user shares lead source, CRM stage, sales note, form, landing page or campaign data tied to lead magnet offer fit.
  • the next decision could change targeting, qualification, scoring, follow-up, sales handoff or budget.
  • lead volume looks acceptable but SQL, opportunity, closed-won, rejection or response-speed data raises doubt.

Do not use this skill for broad lead-generation advice without source, CRM, sales or qualification evidence. Use it when a real B2B lead quality decision is on the table.

Required input

  • business model, ICP, offer, ACV or deal value range, sales cycle and main conversion goal.
  • ad, landing page, lead form, CRM, call note, email or campaign data relevant to this diagnostic.
  • time window, traffic source, lead volume and downstream outcomes where available.
  • what decision the user is trying to make next: create, fix, scale, pause, brief sales or investigate.
  • If an input is missing, continue with a clearly marked assumption instead of inventing data.

Analysis workflow

  1. Classify the asset by buyer stage: problem-aware, solution-aware, vendor-aware or implementation-ready.
  2. Compare the promised outcome with ICP pain intensity, buying urgency and the next commercial step.
  3. Check whether the asset attracts budget owners, operators, researchers, students or low-intent downloaders.
  4. Review the asset title, landing page, form, thank-you step and follow-up for one coherent promise.
  5. Score qualification strength using specificity, business pain, implementation effort, proof and follow-up relevance.
  6. Recommend keep, sharpen, reposition, gate differently, pair with a stronger CTA or retire.

Decision rules

  • If the data does not connect to revenue, pipeline, qualified leads or conversion quality, label the recommendation as a hypothesis.
  • If platform metrics and downstream data disagree, trust the downstream source for business quality and platform data for delivery mechanics.
  • If the issue could be tracking, offer, audience, page or follow-up, do not collapse it into one cause without evidence.
  • Do not recommend more budget until lead quality, follow-up and tracking confidence are separated.

Read the full file on GitHub · 66 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. 2mo ago First seen · 66 lines · 55 tokens per session scan A 76b6312f5128

Subscribe to this mod's changes

lead-magnet-offer-fit is a skill published in the GitHub repository mardab96/b2b-lead-generation-claude-skills (6 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 781 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 2026-08-31.

Related

lead-magnet-offer-fit compared with skills from other repositories

lead-magnet-offer-fit next to 6 skills from other repositories
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lead-magnet-offer-fitmardab96/b2b-lead-generation-claude-skillsSkill63mo agoMITA55Claude Code, Codex
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