acquisition-channel-ad…
Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.
Research and draft a competitive battle card from public evidence — every claim labeled and sourced. Use when a rep needs a field-action card, not a research report.
$ npx -y skills add deanpeters/Product-Manager-Skills --skill battle-card-builder --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/battle-card-builderContext preview
The summary Claude sees to decide when to auto-load this skill.
Research and draft a competitive battle card from public evidence — every claim labeled and sourced. Use when a rep needs a field-action card, not a research report.
name: battle-card-builder argument-hint: "[your product vs which competitor, and the deal context]" description: "Research and draft a competitive battle card from public evidence — every claim labeled and sourced. Use when a rep needs a field-action card, not a research report." intent: >- Autonomous battle card construction: given your product and one competitor, the AI does the fieldwork — pricing pages, reviews, release notes, customer stories — and produces a field-action card with a source URL and Fact/Inference/Assumption label on every claim, sized to a rep's thirty seconds. type: workflow theme: market-intelligence best_for: - "Arming sales against one competitor with claims they can actually defend" - "Turning a competitive snapshot or watch report into a field-action artifact" - "Building trap questions whose documented answers favor you" scenarios: - "We keep hitting the same rival in enterprise deals — build the battle card from public evidence" - "Our battle card is six months old and sales stopped trusting it; rebuild it with sources" estimated_time: "20-35 min per run"
Build a field-action competitive battle card from public evidence: **use or gather evidence → search plan (if gathering) → draft card with per-claim labels → appendix → next-step options.** A battle card is the artifact a rep opens mid-deal, not a research report — it must fit thirty seconds, every claim must survive being said out loud to a hostile audience, and every claim therefore carries a source URL, a date, and a Fact/Inference/Assumption label. Most battle cards in the wild are unlabeled inference; this skill exists because of what it costs a rep when one of those turns out wrong.
**Works best with:** your product and its primary differentiation, and **the one competitor** this card targets. **Also useful:** the deal context (segment, buyer, common objections or the loss reason that triggered this card), and any [`competitive-research-snapshot`](../competitive-research-snapshot/SKILL.md) or [`competitive-intel-watch`](../competitive-intel-watch/SKILL.md) output in session — the skill uses existing evidence and searches only for gaps and anything older than one quarter.
Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an appended `ARGUMENTS:` line — counts as answers already given. Use it against the question budget; don't re-ask.
**Arriving empty-handed? That works too.** The skill opens with at most 3 questions (product + competitor, segment + buyer, triggering objection) and proceeds on labeled assumptions if they go unanswered.
**Example invocation:** `Build a battle card: our workflow platform vs [Competitor A], mid-market ops buyers — triggered by three straight losses on "their integrations are deeper."`
contract — question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just Enough Mode, stable schema, 4-option Final Step.
going stale) + OSINT (review mining for objection handling) + HUMINT (win/loss ground truth when you have it) — see [`intelligence-collection-disciplines`](../intelligence-collection-disciplines/SKILL.md).
goes in the appendix; the card fits a rep's thirty seconds.
documented answer* — offense is built from citations, not bravado. "Never ask what you cannot evidence" is the section's law.
are listed explicitly — the card protects the rep from the team's own folklore.
(investigation); a facilitated workshop builds it from *your team's* evidence (win/loss knowledge, deal experience). The mode choice depends on where the evidence lives — bring rich internal win/loss knowledge to a facilitated session instead, and use this skill when the public record is the stronger source.
1. **Check session for existing evidence** — a competitive snapshot or watch report. If present, use it as the evidence base; search only for gaps and freshness (older than one quarter). 2. **Credit inline context**, then ask only the unanswered questions (max 3): 1. Your product, and the one competitor this card targets? 2. What segment and buyer do these deals involve? 3. What objection or loss reason triggered this card? If unanswered, proceed with labeled assumptions. 3. **If researching fresh, show the 3-bullet search plan** — what you'll check (pricing pages, release notes, reviews, customer stories, comparison content), source types, how facts will be separated from inference. Continue unless revised. 4. **Draft the card in the schema below exactly** — cards are diffable across runs, and the watch skill's update flags name these sections.
~~~markdown
**As-of date:** | **Deal context:** [segment, buyer]
77 battle-tested PM frameworks, ready for Claude, Codex, ChatGPT, and any agent that can read structured knowledge.
Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.
Design multi-agent AI workflows with clear boundaries, handoffs, and monitoring. Use when a complex PM task should run as parallel specialized agents instead…
Assess whether your product work is AI-first or AI-shaped. Use when evaluating AI maturity and choosing the next team capability to build.
Understand the PM-to-Director transition through altitude and horizon thinking. Use when diagnosing scope, time-horizon, or leadership-level gaps.
Map evidence-backed growth options across the Ansoff Matrix with risk-rated sequencing. Use when the question is where the next tranche of growth comes from,…
The protocol behind every investigation skill. Use when AI research must proceed without you: search-plan gate, Fact/Inference/Assumption labels, confidence…