Lensmor Event Fit Score

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:

• Run the API key check (Step 1) before any API call
• Resolve the event_id for the named show if not already provided
• Call the fit-score endpoint and return a structured score card with decision band
• Pair with trade-show-finder for manual scoring or when Lensmor API access is unavailable

Use Cases

• Exhibit vs. skip decision: Get a quantified answer before committing budget
• Annual planning triage: Run multiple shows through fit-score to rank investment priorities
• Internal justification: Produce a data-backed score card to share with leadership

Workflow

Step 1: API Key Check

Before making any API call, verify the key is configured:

[ -n "$LENSMOR_API_KEY" ] && echo "ok" || echo "missing"

If the result is missing, stop and respond:

The LENSMOR_API_KEY environment 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.

Step 2: Resolve the Event ID

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.

Step 3: Call the Fit-Score Endpoint

Endpoint: POST https://platform.lensmor.com/external/events/fit-score

Authentication: Authorization: Bearer $LENSMOR_API_KEY

Request body:

{
  "event_id": "12740"
}

Step 4: Interpret the Response

Response structure:

{
  "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:

Step 5: Format the Output

## 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.

Score Interpretation Guide

Apply this interpretation to every fit-score result:

Breakdown dimension guidance:

• profile_match is the primary company-profile signal
• matched_exhibitor_density reflects matched exhibitor volume, not verified buyer or attendee density
• event_scale is derived from exhibitor count and does not measure geographic fit, content fit, or expected ROI
• Do not invent dimensions that are not returned by the API
• A zero score does not prove that the user's Lensmor profile is missing or incomplete. It can also mean that no recommendation match was returned. Do not diagnose the cause unless the API returns an explicit error or status.
• For an exact zero, the interpretation must be limited to: "The current API result is 0/10; this response does not identify the cause." Do not add possible causes, profile-review advice, coverage speculation, or a support-contact recommendation.
• Do not label event_scale as large or small without a defined comparison baseline. Report the value and the returned event.exhibitorCount separately when helpful.
• If explaining 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.

Error Handling

Relationship to trade-show-finder

This skill calls the Lensmor API for a data-driven score on a single named event. Use trade-show-finder for:

• Manual scoring and comparison across multiple shows when you do not have API access
• Annual planning and shortlist discovery driven by web research
• Scoring shows not yet in the Lensmor database

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.

Follow-up Routing

Output Rules

1. All URLs formatted as [text](url) — never bare links
2. Never output the value of LENSMOR_API_KEY
3. Never expose endpoint paths, raw curl commands, or internal token values in the response
4. Employee counts above 1,000 shown as "1.2K"; above 1,000,000 as "1.2M"
5. Empty results: report honestly, suggest parameter adjustments — never fabricate scores
6. End every response with 1–3 contextual follow-up suggestions; for an exact-zero result, the only permitted suggestion is independent event research with trade-show-finder
7. Scores and breakdown values must come directly from the API — do not infer or estimate missing dimensions
8. When totalPages > 1 in events list lookup, confirm the correct event before scoring
9. If API key is missing, direct user to hello@lensmor.com — do not just say "please configure"
10. Treat the score as 0–10 and preserve the exact recommendation enum; never convert it to 0–100 unless the user explicitly requests a labeled conversion
11. Never infer missing profile configuration, absent coverage, or a support requirement from a zero score alone
12. Treat event.exhibitorCount as the count in the Lensmor event record, not an official or registered-exhibitor total
13. If the exact score is zero, do not suggest profile changes, coverage checks, or support escalation unless the API returns a specific error or status that supports that advice

Quality Checks

Before delivering:

• Confirm event_id resolves to the correct show, year, and edition — do not use an ID from a prior year
• Do not infer or fabricate dimension scores; use only what the API returns
• If breakdown is missing or partial, note which dimensions were unavailable
• If recommendation field is empty, present the numeric score alone and apply the interpretation guide
• If the result is zero, state only that the current API result is zero and that the cause is not identified by this response

Fit 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.