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
Xpersona Agent
Compensation & Salary Benchmarking Planner Compensation & Salary Benchmarking Planner Build data-driven compensation structures that attract talent without overpaying. Covers base salary bands, equity/bonus frameworks, geographic differentials, and total rewards packaging. When to Use - Building or revising salary bands for any role - Preparing for hiring sprints and need market-rate data - Conducting annual compensation reviews - Designing equity/bonus/commi
clawhub skill install skills:1kalin:afrexai-compensation-plannerOverall rank
#62
Adoption
No public adoption signal
Trust
Unknown
Freshness
Feb 25, 2026
Freshness
Last checked Feb 25, 2026
Best For
afrexai-compensation-planner 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, CLAWHUB, runtime-metrics, public facts pack
Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.
Overview
Compensation & Salary Benchmarking Planner Compensation & Salary Benchmarking Planner Build data-driven compensation structures that attract talent without overpaying. Covers base salary bands, equity/bonus frameworks, geographic differentials, and total rewards packaging. When to Use - Building or revising salary bands for any role - Preparing for hiring sprints and need market-rate data - Conducting annual compensation reviews - Designing equity/bonus/commi Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Feb 25, 2026
Vendor
Openclaw
Artifacts
0
Benchmarks
0
Last release
Unpublished
Install & run
clawhub skill install skills:1kalin:afrexai-compensation-plannerSetup 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.
Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.
Public facts
Vendor
Openclaw
Protocol compatibility
OpenClaw
Handshake status
UNKNOWN
Crawlable docs
6 indexed pages on the official domain
Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.
Captured outputs
Extracted files
0
Examples
0
Snippets
0
Languages
typescript
Parameters
Editorial read
Docs source
CLAWHUB
Editorial quality
ready
Compensation & Salary Benchmarking Planner Compensation & Salary Benchmarking Planner Build data-driven compensation structures that attract talent without overpaying. Covers base salary bands, equity/bonus frameworks, geographic differentials, and total rewards packaging. When to Use - Building or revising salary bands for any role - Preparing for hiring sprints and need market-rate data - Conducting annual compensation reviews - Designing equity/bonus/commi
Build data-driven compensation structures that attract talent without overpaying. Covers base salary bands, equity/bonus frameworks, geographic differentials, and total rewards packaging.
When asked to build a compensation plan, follow this framework:
Define job levels and salary bands:
| Level | Title Pattern | Base Range (US) | Equity % | Bonus Target | |-------|--------------|-----------------|----------|--------------| | L1 | Associate / Junior | $45K-$70K | 0-0.01% | 0-5% | | L2 | Mid-level | $70K-$110K | 0.01-0.05% | 5-10% | | L3 | Senior | $110K-$160K | 0.05-0.15% | 10-15% | | L4 | Staff / Lead | $150K-$210K | 0.1-0.3% | 15-20% | | L5 | Principal / Director | $190K-$280K | 0.2-0.5% | 20-30% | | L6 | VP / C-level | $250K-$400K+ | 0.5-2%+ | 30-50%+ |
Apply cost-of-labor multipliers (not cost-of-living):
| Tier | Markets | Multiplier | |------|---------|------------| | Tier 1 | SF Bay, NYC, London | 1.0x (baseline) | | Tier 2 | Seattle, Boston, LA, Chicago | 0.90-0.95x | | Tier 3 | Austin, Denver, Manchester, Berlin | 0.80-0.85x | | Tier 4 | Remote US/UK secondary markets | 0.70-0.80x | | Tier 5 | Eastern Europe, LATAM, SEA | 0.40-0.60x |
Break down total rewards:
Cash Compensation
Equity Compensation
Benefits & Perks (typically 20-35% on top of base)
Run these checks quarterly:
| Month | Action | |-------|--------| | Jan | Market data refresh (Levels.fyi, Glassdoor, Radford, Mercer) | | Feb | Manager calibration sessions | | Mar | Budget allocation (typically 3-5% of payroll for merit increases) | | Apr | Communicate adjustments, effective date | | Jul | Mid-year equity refresh grants | | Oct | Prepare next year's comp budget proposal |
Before extending any offer:
| Factor | Weight | Score (1-5) | |--------|--------|-------------| | Below market rate (>10% under) | 25% | | | Time since last raise (>18 months) | 20% | | | Flight risk signals (LinkedIn active, disengaged) | 20% | | | Critical role / hard to replace | 20% | | | Tenure > 3 years with no promotion | 15% | |
Score > 3.5 = immediate retention conversation needed Score 2.5-3.5 = include in next review cycle, prioritize Score < 2.5 = monitor quarterly
For revenue roles, design OTE (On-Target Earnings):
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Bundles:
Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.
Machine interfaces
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/clawhub-skills-1kalin-afrexai-compensation-planner/snapshot"
curl -s "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/contract"
curl -s "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/trust"
Operational fit
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
Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.
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/clawhub-skills-1kalin-afrexai-compensation-planner/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "CLAWHUB",
"generatedAt": "2026-04-17T00:12:44.748Z"
}
},
"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": "Openclaw",
"href": "https://github.com/openclaw/skills/tree/main/skills/1kalin/afrexai-compensation-planner",
"sourceUrl": "https://github.com/openclaw/skills/tree/main/skills/1kalin/afrexai-compensation-planner",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-compensation-planner/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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