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 pre-show-competitor-analysisgit 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/pre-show-competitor-analysis)<a href="https://agentmods.dev/skills/lensmorofficial/trade-show-skills/pre-show-competitor-analysis"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/pre-show-competitor-analysis/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/pre-show-competitor-analysis"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/pre-show-competitor-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00025 | $0.01477 |
| Opus 5.5 | $0.00010 | $0.00591 |
| Sonnet 5.5 | $0.00005 | $0.00295 |
| Haiku 4.5 | $0.00003 | $0.00148 |
Grade A, and why
pre-show-competitor-analysis scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Show Competitor Analysis
Analyze who is exhibiting at a target show, how they're positioning, and what it means for your strategy.
When this skill triggers:
- Read references/competitor-analysis-framework.md before starting
- This is pre-show intelligence, not real-time booth observation (use
trade-show-competitor-radarfor on-site intel) - Ask only for the missing show, segment, or offer context; do not start with a generic research questionnaire
Example Requests
- Who are my competitors at this show?
- 分析展会竞争对手
- Messekonkurrenz analysieren
- 競合他社を事前分析する
- análisis de competidores en feria
Workflow
Step 1: Determine Analysis Mode
Three modes:
-
Specific competitor deep-dive Example: "What do we know about Acme Corp's presence at MEDICA 2026?"
-
Landscape overview Example: "Who's exhibiting in surgical robotics at MEDICA?"
-
Positioning gap analysis Example: "Where's the open space in the surgical workflow market at this show?"
Step 2: Collect Target Show Data
Gather:
- Confirmed exhibitor list (if published)
- Floor plan with booth assignments
- Show segmentation (halls, pavilions, themes)
- Your company's planned booth location (if known)
Verify all data is for the correct upcoming edition.
Stop researching a missing source after two attempts and report the gap. If the exhibitor list or floor plan is unavailable, provide the supported positioning analysis with [UNK] presence fields rather than inventing booth details.
Step 3: Analyze Competitor Presence
For each relevant competitor:
Booth signals:
- Size and location (corner, island, inline)
- Hall placement (main vs. secondary)
- Proximity to entrances, competitors, or complementary vendors
Messaging signals:
- Listed product categories
- Taglines or positioning statements
- Sponsorship level (if visible)
Activity signals:
- Speaking slots or featured presentations
- Demo schedules or events
- New product launch indicators
What ships with it
3 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.
- 1mo ago Changed · +11 lines · -75 tokens per session 2029a2dacecc
- 2mo ago First seen · 170 lines · 100 tokens per session scan A c795b7dd6490
pre-show-competitor-analysis is a skill published in the GitHub repository LensmorOfficial/trade-show-skills (49 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,477 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
pre-show-competitor-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| pre-show-competitor-analysisLensmorOfficial/trade-show-skills | Skill | 49 | 1mo ago | MIT | A | 25 | Claude Code, Codex |
| mcp-host-styling-integrationa5c-ai/babysitter | Skill | 1.9k | 5d ago | MIT | A | 44 | Claude Code |
| cog-knowledge-consolidationa5c-ai/babysitter | Skill | 1.9k | 5d ago | MIT | A | 19 | Claude Code |
| formula-authoringa5c-ai/babysitter | Skill | 1.9k | 5d ago | MIT | A | 28 | Claude Code |
| quality-hooksa5c-ai/babysitter | Skill | 1.9k | 5d ago | MIT | A | 53 | Claude Code |
| ops-arLifecycle-Innovations-Limited/claude-ops | Skill | 548 | 4d ago | MIT | A | 29 | Claude Code |
| ops-marketingLifecycle-Innovations-Limited/claude-ops | Skill | 548 | 4d ago | MIT | A | 29 | Claude Code |