> ## Documentation Index
> Fetch the complete documentation index at: https://docs.consensus.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Substantiate a product claim with published evidence

> Build the evidence file behind a claim before it ships — including what contradicts it.

## What you get

A claim-by-claim substantiation file: the peer-reviewed evidence supporting each claim, the evidence against it, a defensibility grade, and suggested wording the evidence actually supports.

## Who it's for

Product, brand, regulatory, and R\&D teams in consumer goods, sports and performance products, supplements, and devices — plus the consultancies who advise them.

## The prompt

```text theme={null}
You are a claims substantiation analyst. You are assembling the evidence file
behind product claims before they go to market.

Claims:
[LIST THE CLAIMS, ONE PER LINE]

Product context: [WHAT IT IS, WHO USES IT, HOW]

For each claim:

1. Split it into testable parts. "Reduces injury risk and improves comfort" is
   two claims with different evidence bases — never assess them together.
2. State each part as a proposition naming the population, the intervention or
   product attribute, the comparator, and the outcome measure.
3. Search Consensus for supporting evidence. Require human studies with a
   control condition and a realistic sample size. Note the exact population
   studied — trained athletes are not recreational users, and lab protocols are
   not real-world use.
4. Search separately for contradicting evidence, using the negative phrasing.
   Finding the contradicting paper yourself is far cheaper than a competitor
   or a regulator finding it.
5. Check whether the effect was measured directly or inferred from a surrogate.
   A claim about injury risk supported only by a biomechanical proxy is a
   different claim.

Grade each part:
  STRONG — multiple controlled human studies, consistent direction, population
    matches our users.
  QUALIFIED — evidence exists but is limited by population, sample size, design,
    or reliance on a surrogate outcome. Write the narrower claim it supports.
  UNSUPPORTED — no adequate evidence found. Say what you searched.
  CONTRADICTED — the weight of evidence points the other way. Give the citation.

For every QUALIFIED and UNSUPPORTED part, propose the wording the evidence does
support, and say what study would be needed to support the original.

Output: Claim part | Grade | Population studied | Direct or surrogate outcome |
Supporting citations | Contradicting citations | Suggested wording.
```

## The API call

Demand controlled human evidence at a realistic size:

```bash theme={null}
curl -G "https://api.consensus.app/v1/search" \
  -H "x-api-key: $CONSENSUS_API_KEY" \
  --data-urlencode "query=forefoot bending stiffness running economy oxygen cost" \
  --data-urlencode "human=true" \
  --data-urlencode "controlled=true" \
  --data-urlencode "sample_size_min=15" \
  --data-urlencode "study_types=rct,non-randomized experimental study" \
  --data-urlencode "page_size=50"
```

Then run the negative pass:

```bash theme={null}
curl -G "https://api.consensus.app/v1/search" \
  -H "x-api-key: $CONSENSUS_API_KEY" \
  --data-urlencode "query=footwear stiffness no effect running economy null finding" \
  --data-urlencode "human=true" \
  --data-urlencode "controlled=true" \
  --data-urlencode "page_size=50"
```

| Parameter         | Why it matters here                                                                    |
| ----------------- | -------------------------------------------------------------------------------------- |
| `human=true`      | Animal and in vitro evidence rarely substantiates a consumer claim                     |
| `controlled=true` | Uncontrolled studies will not survive review                                           |
| `sample_size_min` | Filters the underpowered studies that make weak claims look supported                  |
| `sjr_max`         | Restrict to higher-quartile journals when the field has a large promotional literature |
| `domain`          | Keeps technical terms in the right field                                               |

## What to check before you trust it

<Warning>
  This is an evidence file for legal, regulatory, and marketing review — not a compliance sign-off. Requirements differ by market and claim type, and a human with that jurisdiction's expertise makes the final call.
</Warning>

* **Check the population column on every row.** The most common substantiation failure is real evidence from a population that is not your customer.
* **Direct versus surrogate outcome is load-bearing.** A biomechanical proxy does not substantiate an injury-reduction claim, however strong the correlation.
* **Confirm the negative pass actually ran.** If there are no contradicting citations anywhere in the file, it was skipped — null findings exist in almost every applied field.
* **Take the suggested wording seriously.** The narrower claim is usually still a good claim, and it is the one you can defend.

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