Product context
Build or refresh a compact, evidence-backed product context before marketing, positioning, SEO, analytics, sales-enablement, or launch work. Use when an agent needs to understand the product, audience, proof, conversion goal, terminology, and claim boundaries without inventing commercial facts.From its SKILL.md
npx -y skills add markoblogo/abvx-agent-skills --skill product-contextAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 14 stars14 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its file declares
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The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
2.5 KB, 435 tokens by cl100k_base, as published. Nobody here has run it
Product Context
Create a small, durable context artifact that lets later product work start from evidence instead of generic positioning.
Use When
- entering marketing, content, SEO, analytics, sales, or launch work in a repo;
- the product, audience, conversion action, or proof boundary is unclear;
- existing public copy and internal product behavior have drifted.
Workflow
- Read existing product docs, public copy, analytics contracts, and relevant implementation surfaces.
- Separate confirmed facts from assumptions, placeholders, and claims needing owner confirmation.
- Draft or update
docs/product-context.mdunless the repo already defines a better canonical path. - Keep only: product and audience, jobs and conversion action, terminology, proof and known limits, approved voice, prohibited claims, source surfaces, and last-reviewed date.
- Ask for confirmation where positioning, ICP, pricing, competitor claims, or proof cannot be established from the repo.
- Link future work to the context; do not treat it as permission to publish, spend, contact people, or change product behavior.
Guardrails
- Never invent customer quotes, metrics, market position, availability, pricing, partner status, or legal/compliance claims.
- Keep personal data and private sales evidence out of a committed context file.
- Treat a product context as a reviewable input, not a source of truth over code, current policy, or human direction.
- Preserve domain-specific safety language such as financial, booking, or approval boundaries.
Output Shape
Use these headings where applicable: Product, Audience and jobs, Conversion action, Proof and limits, Language, Claim boundaries, Source surfaces, Maintenance.
Pair With
evidence-ledger-researchfor external facts;social-publishing-gatebefore distribution;bounded-growth-loopbefore recurring optimization;loop-readiness-reviewbefore scheduling any loop.
Provenance
Adapted from the shared-context architecture in coreyhaines31/marketingskills, narrowed to evidence-backed, product-neutral context with explicit claim boundaries.
What ships with it: 2 files
1.6 KB alongside SKILL.md
agents/
- openai.yaml222 B
- SKILL_CARD.md1.4 KB