Score a specific trade show against your company's profile using the Lensmor API to get a data-backed recommendation on whether to exhibit, attend, or skip.
When this skill triggers:
event_id for the named show if not already providedtrade-show-finder for manual scoring or when Lensmor API access is unavailableBefore making any API call, verify the key is configured:
bash
[ -n "$LENSMOR_API_KEY" ] && echo "ok" || echo "missing"
If the result is missing, stop and respond:
The
LENSMOR_API_KEYenvironment variable is not set. This skill requires a Lensmor API key to generate fit scores. Contact hello@lensmor.com to purchase access, then set the key:export LENSMOR_API_KEY=your_key_here
Do not proceed to any API call until the key is confirmed present.
The fit-score endpoint requires a Lensmor event_id. If the user only has a show name, look it up first:
Endpoint: GET https://platform.lensmor.com/external/events/list?keyword={show+name}
Authentication: Authorization: Bearer $LENSMOR_API_KEY
The response is paginated under items. Pick the id or eventId that matches the show, year, and edition the user intends. Do not use query=: the current API ignores that parameter and returns an unfiltered event list.
If the user already has the event_id, skip directly to Step 3.
Endpoint: POST https://platform.lensmor.com/external/events/fit-score
Authentication: Authorization: Bearer $LENSMOR_API_KEY
Request body:
json
{
"event_id": "12740"
}
Response structure:
json
{
"event": {
"id": "12740",
"eventId": "12740",
"name": "MEDICA 2026",
"dateStart": "2026-11-16",
"dateEnd": "2026-11-19",
"city": "Düsseldorf",
"country": "Germany",
"url": "https://www.medica-tradefair.com"
},
"score": 7.8,
"recommendation": "recommended",
"breakdown": {
"profile_match": 7.8,
"matched_exhibitor_density": 4.2,
"event_scale": 1.4
}
}
Response field reference:
FieldTypeDescriptionevent.idstringLensmor event IDevent.namestringOfficial show nameevent.eventIdstringStable Lensmor event identifierevent.dateStart / event.dateEndstringShow dates in ISO formatevent.city / event.countrystringShow locationevent.urlstringEvent website URL when availablescorenumberOverall fit score on the API's 0–10 scalerecommendationstringAPI decision enum: recommended, consider, or not_recommended``breakdown.profile_matchnumberCompany-profile match on a 0–10 scalebreakdown.matched_exhibitor_densitynumberDensity derived from matched exhibitors, capped at 10breakdown.event_scalenumberScale derived from exhibitor count, capped at 10
markdown
## Event Fit Score — [Show Name]
[Show website link] | [dateStart]–[dateEnd] | [city], [country]
| Dimension | Score |
|-----------|-------|
| **Overall Fit** | **[score] / 10** |
| Profile Match | [breakdown.profile_match] |
| Matched Exhibitor Density | [breakdown.matched_exhibitor_density] |
| Event Scale | [breakdown.event_scale] |
**Decision**: [decision band — see table below]
**API Recommendation**: [exact `recommendation` enum]
**Interpretation**: [brief explanation grounded only in the returned score and three breakdown fields]
Exact-zero hard gate: If score == 0, use only this interpretation: The current API result is 0/10; this response does not identify the cause. The only permitted follow-up is independent event research with trade-show-finder. Do not mention profile validation, missing matches, database coverage, support, or possible causes anywhere in the response.
Apply this interpretation to every fit-score result:
Score RangeBandDecision7–10RecommendedStrong profile signal. Pressure-test execution cost before committing to exhibit.4–<7ConsiderMixed signal. Attend first or validate the weak dimensions before exhibiting.0–<4Not recommendedLow current API signal. Skip exhibiting unless there is a separate strategic reason.
Breakdown dimension guidance:
profile_match is the primary company-profile signalmatched_exhibitor_density reflects matched exhibitor volume, not verified buyer or attendee densityevent_scale is derived from exhibitor count and does not measure geographic fit, content fit, or expected ROIevent_scale as large or small without a defined comparison baseline. Report the value and the returned event.exhibitorCount separately when helpful.event_scale, use: "The API returned event scale [X]/10 and event exhibitor count [Y]; this response does not define a qualitative size benchmark." Never call the count registered, official, total-market, minimal, or large.HTTP StatusMeaningResponse401API key invalid or expired"The API key was rejected. Verify LENSMOR_API_KEY or contact hello@lensmor.com."404Event ID not found"Event ID [id] was not found. Use the events list endpoint to look up the correct ID."409Recommendation dependency is still processing"Lensmor recommendations are still processing. Retry after the profile recommendation job completes."429Rate limit exceeded"Rate limit reached. Wait 60 seconds and retry."502 / 5xxServer error"The Lensmor API returned a server error. Try again in a moment."
This skill calls the Lensmor API for a data-driven score on a single named event. Use trade-show-finder for:
The two skills are complementary: trade-show-finder helps you build the shortlist; trade-show-fit-score gives you a data-backed score on a specific candidate.
Score outcomeRecommended next actionScore ≥ 7Run trade-show-lead-recommender and verify that recommendation metadata is populatedScore ≥ 7, budget pendingRun trade-show-budget-plannerScore < 4Run trade-show-finder to identify alternatives using independent event researchMultiple shows to compareScore each via this skill, then rank by score field
[text](url) — never bare linksLENSMOR_API_KEYtrade-show-findertotalPages > 1 in events list lookup, confirm the correct event before scoringevent.exhibitorCount as the count in the Lensmor event record, not an official or registered-exhibitor totalBefore delivering:
event_id resolves to the correct show, year, and edition — do not use an ID from a prior yearbreakdown is missing or partial, note which dimensions were unavailablerecommendation field is empty, present the numeric score alone and apply the interpretation guideFit scores are generated by the Lensmor AI platform based on your company profile and Lensmor's trade show database. For event discovery, exhibitor intelligence, and pre-show lead generation, see Lensmor.