trade-show-fit-score

trade-show-fit-score is a skill for Claude Code from LensmorOfficial/trade-show-skills. It costs 122 tokens per session (2,610 once invoked), scanned A, original, MIT.

A tool that scores a trade show against your company's profile and recommends exhibiting, attending, or skipping it.

In plain words
What is it for?
Use it to evaluate one show or rank several shows for annual investment planning. It can also provide evidence for a go-or-no-go discussion with leadership.
Why use it?
It helps you judge whether an event is worth the budget before committing. It also gives you a structured score card to support planning and internal decisions.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: built for openclaw.

Good fit Use it to evaluate one show or rank several shows for annual investment planning. It can also provide evidence for a go-or-no-go discussion with leadership.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lensmorofficial/trade-show-skills/trade-show-fit-score
Install

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.

Any agent
npx skills add LensmorOfficial/trade-show-skills --skill trade-show-fit-score
Clone the repo
git clone --depth 1 https://github.com/LensmorOfficial/trade-show-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for trade-show-fit-score

README.md
[![agentmods](https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/trade-show-fit-score/github.svg)](https://agentmods.dev/skills/lensmorofficial/trade-show-skills/trade-show-fit-score)
Your own site
<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.

agentmods 80×15 button for trade-show-fit-score

Your own site · 80×15
<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>
Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,610 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 12d ago against content hash 47907fba39b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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
trade-show-fit-score/SKILL.md · 210 lines

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_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 [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

Read the full file on GitHub · 210 lines

Files

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.

Changes

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.

  1. 12d ago First seen · 210 lines · 122 tokens per session scan A 47907fba39b9

Subscribe to this mod's changes

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.