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Co-Manufacturer Sourcing Brief

Brief and screen co-packers with the right capability questions and red flags.

What is the Co-Manufacturer Sourcing Brief?

The Co-Manufacturer Sourcing Brief is a free AI skill that structures the search for a co-packer or contract manufacturer for a new food or beverage product. You give it the product, target volume, and must-have capabilities; it returns the capability requirements a candidate must meet, a scored RFP question set covering equipment, food-safety certifications, and minimum order quantities, the volume and capacity fit questions to ask before a plant tour, and the red flags that predict a bad co-manufacturer relationship before you sign anything. It is built for innovation and operations teams choosing a manufacturing partner for the first time, or replacing one that has stopped fitting the brand's needs. Because every candidate is screened on the same requirements, the search stays comparable across plant visits instead of resting on whichever tour felt most impressive. Pairing it with live food and beverage demand data sanity-checks the volume forecast a sourcing decision gets built around.

Who it's for

  • Innovation and NPD teams sourcing a co-packer for a new launch
  • Founders choosing their first contract manufacturer
  • Operations and supply chain leads replacing an underperforming co-packer
  • Category teams scoping private-label manufacturing partners

What you get

  • A capability requirements checklist matched to your product
  • A scored RFP question set covering equipment, certifications and MOQs
  • Volume and capacity fit questions for the plant-tour stage
  • Red flags that predict a bad co-manufacturer relationship
  • A comparison scorecard to rank candidates consistently
  • A shortlist-to-contract next-steps checklist

How to use it

  1. 1Copy the prompt into ChatGPT, Claude or Gemini.
  2. 2Fill the bracketed inputs (product, volume, capabilities, constraints).
  3. 3Answer its clarifying questions about process and certification needs.
  4. 4Iterate: ask it to turn the RFP questions into a scorecard template.

See it in action

Example input

Product: fictional 'Marrow & Co' bone broth, needs retort or aseptic processing for a 16 oz shelf-stable carton. Target volume: 40,000 cases in year one, scaling to 150,000. Must-haves: SQF certification, organic handling, and willingness to run a 10,000-case minimum initial batch.

Example output

Co-manufacturer sourcing brief — Marrow & Co shelf-stable bone broth

Capability requirements (must-haves before a plant tour):
- Aseptic or retort processing line qualified for a protein-based liquid at your target pH and viscosity — confirm which process your recipe actually requires; they are not interchangeable and re-qualifying a recipe for a different process late costs months.
- Carton or aseptic-pouch filling compatible with a 16 oz format.
- Current SQF Level 2 or 3 certification, verified directly with SQFI, not just claimed on a sales deck.
- Certified organic handling with a segregated or validated changeover process if the line also runs conventional product.
- Willingness to run a 10,000-case minimum initial batch — many co-packers set MOQs well above this for retort lines; screen for it early to avoid wasting a plant-tour slot.

RFP question set:
1. What is your current utilization on the line that would run this product, and what lead time would our first batch need?
2. Walk us through your changeover process between conventional and organic runs — what's validated, and how is cross-contact prevented?
3. What is your typical yield loss and how is it billed?
4. Which of your current clients run a comparable viscosity and pH product, without naming names — can you describe the closest analog?
5. What does a rejected or out-of-spec batch cost us, and who owns that risk?
6. What is your true MOQ at this format, and does it flex for an initial smaller run?

Volume and capacity fit questions for the plant tour:
- Can this line's current utilization actually absorb 40,000 cases in year one without displacing an existing client — ask this directly, politely, and watch the answer's confidence.
- What capital or changeover investment, if any, would scaling to 150,000 cases require, and who funds it?
- What is the realistic lead time from PO to delivered case at each volume tier?

Red flags to screen for:
- Vague or deflected answers on current utilization — a co-packer that won't discuss capacity honestly will overpromise your lead time.
- No named QA contact separate from sales — food-safety accountability should not run through the salesperson.
- Reluctance to provide references running a similar product, not just a similar category.
- A contract that locks pricing without a raw-material index clause — leaves you exposed to the next protein price spike.
- Certifications that are expired, "in process," or unverifiable directly with the certifying body.

Comparison scorecard (score each candidate 1-5): process fit, certification status, MOQ flexibility, capacity headroom, QA transparency, reference quality, contract terms.

Next steps: shortlist to 3 candidates on the scorecard, request a paid trial run before any volume commitment, and confirm organic segregation with a site walk-through, not a phone call.

Assumption to validate: the 150,000-case year-two volume — confirm this is grounded in real demand signal before it anchors a capacity conversation with a candidate co-packer.

Want me to turn the RFP questions into a shareable scorecard spreadsheet format?

The prompt

Here's the start of the prompt. Download the free bundle for the full, ready-to-paste version — plus the installable Claude Skill and Custom-GPT instructions.

# Role
You are a senior co-manufacturing sourcing strategist who has run dozens of co-packer searches for food and beverage brands. You screen on capability and evidence, not a sales deck, and surface the questions that predict a bad relationship before a contract is signed.

# Context I'll provide
- Product: [PRODUCT — format, process requirements, key specs]
- Target volume: [VOLUME — year one and future scale]
- Must-have capabilities: [CAPABILITIES e.g. certifications, process type, organic/allergen handling]
- Market and channel: [MARKET / CHANNEL]
- Constraints: [CONSTRAINTS e.g. timeline, budget, geography, MOQ tolerance]

# Your task
1. If the process requirements, target volume, or capabilities are missing or vague, ask up to 3 clarifying questions BEFORE writing anything.

Frequently asked questions

What is a co-manufacturer in food and beverage?
A co-manufacturer, or co-packer, is a contract manufacturing partner that produces a food or beverage product on a brand's behalf — supplying the plant, equipment, and often packaging, while the brand owns the recipe and the label. Brands use co-manufacturers to launch without building a factory. This skill structures the search: what to require, what to ask, and what predicts a bad partnership.
How is this different from the Value Engineering Brief skill?
The Value Engineering Brief cuts cost on an existing formulation or pack that is already in production, usually with the current manufacturing partner. This skill is upstream of that: it sources and screens a manufacturing partner in the first place, for a new product or a switch away from an underperforming one. Use this to find the right co-packer; use the value engineering brief once you're in production and hunting margin.
Which AI models does this prompt work with?
Any capable chat model — ChatGPT, Claude, or Google Gemini — runs it as written. Because a co-packer search usually spans several weeks and multiple plant visits, many teams save it as a Custom GPT or a reusable skill so every candidate gets screened against the identical requirements and scorecard.
What should I verify before trusting a co-packer's answers?
Verify certifications directly with the certifying body rather than a sales deck, ask for references running a genuinely comparable product rather than just a comparable category, and never let a plant tour substitute for a paid trial run. The skill will not invent capacity numbers or pricing benchmarks for you — those come from the RFP responses and your own costing, not from a generic AI estimate.

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