Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LensmorOfficial/trade-show-skills --skill trade-show-fit-scoregit clone --depth 1 https://github.com/LensmorOfficial/trade-show-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lensmorofficial/trade-show-skills/trade-show-fit-score)<a href="https://agentmods.dev/skills/lensmorofficial/trade-show-skills/trade-show-fit-score"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/trade-show-fit-score/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lensmorofficial/trade-show-skills/trade-show-fit-score"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/trade-show-fit-score.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 183 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.02610 |
| Opus 5 | $0.00061 | $0.01305 |
| Sonnet 5 | $0.00024 | $0.00522 |
| Haiku 4.5 | $0.00012 | $0.00261 |
Grade A, and why
trade-show-fit-score scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
3. Never expose endpoint paths, raw curl commands, or internal token values in the response How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lensmor Event Fit Score
Score a specific trade show against your company's profile using the Lensmor API to get a data-backed recommendation on whether to exhibit, attend, or skip.
When this skill triggers:
- Run the API key check (Step 1) before any API call
- Resolve the
event_idfor the named show if not already provided - Call the fit-score endpoint and return a structured score card with decision band
- Pair with
trade-show-finderfor manual scoring or when Lensmor API access is unavailable
Use Cases
- Exhibit vs. skip decision: Get a quantified answer before committing budget
- Annual planning triage: Run multiple shows through fit-score to rank investment priorities
- Internal justification: Produce a data-backed score card to share with leadership
Workflow
Step 1: API Key Check
Before making any API call, verify the key is configured:
[ -n "$LENSMOR_API_KEY" ] && echo "ok" || echo "missing"
If the result is missing, stop and respond:
The
LENSMOR_API_KEYenvironment variable is not set. This skill requires a Lensmor API key to generate fit scores. Contact [email protected] 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
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 210 lines · 122 tokens per session scan A 47907fba39b9
trade-show-fit-score is a skill published in the GitHub repository LensmorOfficial/trade-show-skills (48 stars, last pushed 1mo ago), licensed MIT. It adds 122 tokens to every session and 2,610 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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