Broker Recognize
Product photo recognition for C2C resale. Use when user uploads a product photo and wants AI to identify the item for resale listing. Extracts brand, product name, model, category, condition grade (A-E), material, color, size, notable features, and visible flaws. Also usable standalone via /broker-recognize. Trigger phrases: "what is this", "identify this", "analyze this item", photo upload for r…
Install
$ agentstack add skill-madguyevans-creator-resale-agent-skill-hub-broker-recognize ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-madguyevans-creator-resale-agent-skill-hub-broker-recognize) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
broker-recognize: Photo → Product Info
Extracts structured product information from user-uploaded photos for C2C resale listing purposes.
Prerequisite: ANTHROPICAPIKEY
This skill uses the Anthropic API (Claude Vision) for image analysis. Your current LLM model may not support multimodal vision, so the skill calls the Vision API directly.
export ANTHROPIC_API_KEY="sk-ant-..."If the key is missing, the skill will output an error instructing the user to set it.
Workflow
- User provides 1-3 photos of the item
- Analyze using vision: brand, product name, model, category, condition (A-E), material, color, size, features, flaws, estimated original retail
- Present structured card to user for confirmation/correction
- Save product info to conversation context for next skill in pipeline
Condition Grade Scale
| Grade | Label | Criteria | |-------|-------|----------| | A | Like New | No visible wear, original packaging if applicable | | B | Excellent | Minor signs of use, no significant flaws | | C | Good | Visible wear, minor flaws, fully functional | | D | Fair | Noticeable wear/flaws, may need minor repair | | E | For Parts | Significant damage, sold as-is |
Key Rule
Be honest about flaws. Transparency is the foundation of C2C trust. A lost honest sale is better than a return from undisclosed flaws.
Script
scripts/recognize.py provides the structured prompt template and output schema.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: madguyevans-creator
- Source: madguyevans-creator/resale-agent-skill-hub
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.