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SKILL verified MIT Self-run

Icp Reality Check

skill-mardab96-b2b-lead-generation-claude-skills-icp-reality-check · by mardab96

Compares your stated ICP against actual closed-won and closed-lost customers. Use when you are about to write new targeting or messaging, or when the customers you actually close look nothing like the ICP on the slide.

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Install

$ agentstack add skill-mardab96-b2b-lead-generation-claude-skills-icp-reality-check

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Icp Reality Check

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 icp reality check.
  • 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. Write the stated ICP as a short profile: company type, buyer role, pain, budget, urgency and exclusion rules.
  2. Build a comparison table for closed-won, closed-lost, disqualified and no-show leads by source, company size, role, industry, use case and deal value.
  3. Identify ICP drift: segments that produce cheap leads but weak SQL/opportunity/closed-won rates.
  4. Find ICP blind spots: segments with low lead volume but high sales acceptance or deal value.
  5. Separate targeting problems from offer, page, qualification and follow-up problems before recommending a change.
  6. Return an ICP action: keep, narrow, split into segments, exclude, or collect more data.

Diagnostic rubric

Use this table when the user provides CRM or sales outcome data:

| Segment | Lead volume | SQL rate | Opportunity rate | Closed-won rate | Rejection pattern | ICP verdict | |---|---:|---:|---:|---:|---|---| | Company size / role / industry / use case | Count and source mix | Percent or missing-data marker | Percent or missing-data marker | Percent or missing-data marker | Sales reason, no-show pattern or lost reason | Keep / narrow / split / exclude / collect more data |

Then summarize:

  • ICP drift: segments that create leads but weak pipeline.
  • ICP blind spot: segments with low volume but strong downstream quality.
  • ICP change: the one targeting or qualification change worth testing first.

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.

Output format

| Finding | Evidence | Lead quality impact | Recommended action | Confidence | |---|---|---|---|---| | Specific diagnostic claim | Data, screenshot, report, note or missing-data marker | Business or signal consequence | Smallest useful next step and owner | High / Medium / Low |

End with:

  • Decision: fix / test / monitor / ask for data / do not act yet
  • Approval needed: yes/no and what would change if approved
  • Missing data: only the inputs that would materially change the recommendation

Practical example

User: "Here are CRM stages, source data and sales notes for icp reality check. What should we change before the next campaign move?"

Assistant should: put the stated ICP next to closed-won and closed-lost reality, name where they diverge, and stop at a corrected ICP the owner can sign off.

Guardrails

  • Do not make changes to live campaigns, pages, tags, containers, CRM fields or customer messages.
  • Do not claim performance impact without evidence.
  • Mark missing data clearly.
  • Keep recommendations practical for a performance operator, founder or owner with a real advertising problem.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.