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 twelvelabs-io/twelve-labs-claude-code-plugin --skill entity-searchgit clone --depth 1 https://github.com/twelvelabs-io/twelve-labs-claude-code-pluginWrote 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/twelvelabs-io/twelve-labs-claude-code-plugin/entity-search)<a href="https://agentmods.dev/skills/twelvelabs-io/twelve-labs-claude-code-plugin/entity-search"><img src="https://agentmods.dev/badge/skills/twelvelabs-io/twelve-labs-claude-code-plugin/entity-search/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/twelvelabs-io/twelve-labs-claude-code-plugin/entity-search"><img src="https://agentmods.dev/badge/skills/twelvelabs-io/twelve-labs-claude-code-plugin/entity-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00072 | $0.01102 |
| Opus 5 | $0.00036 | $0.00551 |
| Sonnet 5 | $0.00014 | $0.00220 |
| Haiku 4.5 | $0.00007 | $0.00110 |
Grade A, and why
entity-search 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 9d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Entity Search - Find Specific People in Videos
Find specific people or objects in your indexed videos using reference images. Entity search lets you register a person with reference photos, then search for them across all your videos.
When to Use This Skill
Use this skill when the user:
- Wants to find a specific person in their videos
- Asks to set up face recognition or person tracking
- Has reference images of someone they want to locate in video content
- Wants to search for a known individual (e.g., "find all clips of John")
Prerequisites
- Videos must be indexed with Marengo 3.0 (entity search is a Marengo 3.0 feature)
- Reference images of the person/object (publicly accessible URLs or local file paths)
- Free plan: 1 collection, up to 15 entities. Developer plan: multiple collections.
Instructions
Step 1: Check for Existing Entity Collections
First check if the user already has entity collections set up:
Tool: mcp__twelvelabs-mcp__list-entity-collections
If collections exist, show them and ask if the user wants to use an existing one or create a new one.
Step 2: Create an Entity Collection (if needed)
An entity collection groups related entities. Create one per logical group (e.g., "Team A", "Film Cast").
Tool: mcp__twelvelabs-mcp__create-entity-collection
Parameters:
name: "<collection name>"
Step 3: Upload Reference Images as Assets
Upload one or more reference images for the person. Multiple images from different angles and lighting improve accuracy.
From a URL:
Tool: mcp__twelvelabs-mcp__create-asset
Parameters:
url: "<publicly accessible image URL>"
From a local file:
Tool: mcp__twelvelabs-mcp__create-asset
Parameters:
file: "<absolute path to image file>"
Repeat for each reference image. Collect all returned asset IDs.
Step 4: Create the Entity
Create an entity within the collection, linking it to the reference image assets:
Tool: mcp__twelvelabs-mcp__create-entity
Parameters:
collectionId: "<collection ID from step 2>"
name: "<person's name>"
assetIds: ["<asset_id_1>", "<asset_id_2>"]
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.
- 9d ago First seen · 151 lines · 72 tokens per session scan A 7501fcb76863
entity-search is a skill published in the GitHub repository twelvelabs-io/twelve-labs-claude-code-plugin (23 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 1,102 once invoked, about $0.0004 per session on Opus 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.
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