Crawler Summary
Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- name: lora-captioner description: Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- LoRA Captioner Overview Create high-detail, tag-style captions for image datasets used in AI/LoRA training. Always plan first, always ask for the trigger word, then caption each image and s Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/15/2026.
Freshness
Last checked 4/15/2026
Best For
lora-captioner is best for general automation workflows where OpenClaw compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack
Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- name: lora-captioner description: Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- LoRA Captioner Overview Create high-detail, tag-style captions for image datasets used in AI/LoRA training. Always plan first, always ask for the trigger word, then caption each image and s
Public facts
5
Change events
1
Artifacts
0
Freshness
Apr 15, 2026
Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/15/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Apr 15, 2026
Vendor
Sienadrayy
Artifacts
0
Benchmarks
0
Last release
Unpublished
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/15/2026.
Setup snapshot
git clone https://github.com/sienadrayy/lora-captioner-skill.gitSetup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor
Sienadrayy
Protocol compatibility
OpenClaw
Adoption signal
1 GitHub stars
Handshake status
UNKNOWN
Crawlable docs
6 indexed pages on the official domain
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
0
Snippets
0
Languages
typescript
Parameters
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB OPENCLEW
Editorial quality
ready
Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- name: lora-captioner description: Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders. --- LoRA Captioner Overview Create high-detail, tag-style captions for image datasets used in AI/LoRA training. Always plan first, always ask for the trigger word, then caption each image and s
name: lora-captioner
description: Plan-first workflow for creating detailed image captions for AI/LoRA training datasets, including per-image .txt files, trigger-word inclusion, and batch processing of local image folders.
Create high-detail, tag-style captions for image datasets used in AI/LoRA training. Always plan first, always ask for the trigger word, then caption each image and save a matching .txt file.
Plan first
State a brief plan before writing any files.
Confirm the target folder and image extensions.
Collect required inputs
Ask for the trigger word (do not assume or hardcode it).
Ask for overwrite policy: overwrite existing .txt, skip if exists, or write .new.txt.
Ask for caption style if not provided: high-detail comma tags (default).
Enumerate images
List image files in the target folder (.png, .jpg, .jpeg, .webp, .bmp).
Sort by filename for deterministic order.
Caption in a continuous batch
Process images sequentially without pausing unless the user requests checkpoints.
For each image, view it and generate a caption that includes the trigger word naturally.
Write the caption to a .txt file with the same base name as the image.
Report summary
Use comma-separated tags. Include these when visible:
Subject and trigger word (must appear in every caption)
Pose and body orientation
Expression and gaze
Outfit and accessories
Hair style and color
Makeup (if visible)
Lighting (soft, harsh, natural, studio, etc.)
Camera angle and framing (close-up, medium, side profile, etc.)
Background/setting
Mood or vibe (only if clearly conveyed)
Avoid guessing details not visible. Keep captions concise but rich.
Save captions as UTF-8 text in image_base_name.txt.
Follow the user’s overwrite policy.
Keep one caption per file, single line.
triggerword, close-up portrait, direct eye contact, soft smile, wavy brown hair, minimal makeup, black sleeveless top, soft natural light, plain light background
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/snapshot"
curl -s "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/contract"
curl -s "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/trust"
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.
Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.
Rank
70
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Traction
No public download signal
Freshness
Updated 2d ago
Rank
70
AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs
Traction
No public download signal
Freshness
Updated 5d ago
Rank
70
Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!
Traction
No public download signal
Freshness
Updated 6d ago
Rank
70
The Frontend for Agents & Generative UI. React + Angular
Traction
No public download signal
Freshness
Updated 23d ago
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_OPENCLEW",
"generatedAt": "2026-04-16T23:37:09.671Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}Facts JSON
[
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
},
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Sienadrayy",
"href": "https://github.com/sienadrayy/lora-captioner-skill",
"sourceUrl": "https://github.com/sienadrayy/lora-captioner-skill",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T02:12:38.292Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-15T02:12:38.292Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "1 GitHub stars",
"href": "https://github.com/sienadrayy/lora-captioner-skill",
"sourceUrl": "https://github.com/sienadrayy/lora-captioner-skill",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T02:12:38.292Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/sienadrayy-lora-captioner-skill/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub · GitHub",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
}
]Sponsored
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