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
CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Skill: sheet-cog Owner: nitishgargiitd Summary: CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Tags: latest:1.0.3 Version history: v1.0.3 | 2
clawhub skill install kn7a96cj9q65e0bhmzahv790en80ffqm:sheet-cogOverall rank
#62
Adoption
2.6K downloads
Trust
Unknown
Freshness
Feb 28, 2026
Freshness
Last checked Feb 28, 2026
Best For
sheet-cog 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
CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Skill: sheet-cog Owner: nitishgargiitd Summary: CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Tags: latest:1.0.3 Version history: v1.0.3 | 2 Capability contract not published. No trust telemetry is available yet. 2.6K downloads reported by the source. Last updated 4/15/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Feb 28, 2026
Vendor
Clawhub
Artifacts
0
Benchmarks
0
Last release
1.0.3
Install & run
clawhub skill install kn7a96cj9q65e0bhmzahv790en80ffqm:sheet-cogSetup 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
Clawhub
Protocol compatibility
OpenClaw
Latest release
1.0.3
Adoption signal
2.6K downloads
Handshake status
UNKNOWN
Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.
Captured outputs
Extracted files
2
Examples
4
Snippets
0
Languages
Unknown
bash
clawhub install cellcog
python
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your spreadsheet request]",
notify_session_key="agent:main:main",
task_label="spreadsheet-task",
chat_mode="agent" # Agent mode handles most spreadsheets well
)
# Daemon notifies you when complete - do NOT pollbash
clawhub install cellcog
python
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your spreadsheet request]",
notify_session_key="agent:main:main",
task_label="spreadsheet-task",
chat_mode="agent" # Agent mode handles most spreadsheets well
)
# Daemon notifies you when complete - do NOT pollSKILL.md
---
name: sheet-cog
description: "CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily."
metadata:
openclaw:
emoji: "📈"
author: CellCog
dependencies: [cellcog]
---
# Sheet Cog - Built by the Agent That Builds CellCog
**CellCog is built by its own Coding Agent. That same agent builds your spreadsheets.**
Full Python access, complex data manipulation, formulas, pivot tables, and financial models — powered by the engineering brain that develops an entire AI platform daily. Not a template filler. A programmer that understands your data and builds exactly what you need.
---
## Prerequisites
This skill requires the `cellcog` skill for SDK setup and API calls.
```bash
clawhub install cellcog
```
**Read the cellcog skill first** for SDK setup. This skill shows you what's possible.
**Quick pattern (v1.0+):**
```python
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your spreadsheet request]",
notify_session_key="agent:main:main",
task_label="spreadsheet-task",
chat_mode="agent" # Agent mode handles most spreadsheets well
)
# Daemon notifies you when complete - do NOT poll
```
---
## What Spreadsheets You Can Create
### Financial Models
Professional financial analysis and projections:
- **Startup Financial Model**: "Create a 3-year financial model for a SaaS startup including revenue projections, expenses, and cash flow"
- **DCF Model**: "Build a discounted cash flow model for valuing a company"
- **Investment Analysis**: "Create a real estate investment analysis spreadsheet with ROI calculations"
- **Revenue Model**: "Build a revenue forecasting model with multiple scenarios (base, optimistic, pessimistic)"
- **Unit Economics**: "Create a unit economics spreadsheet showing CAC, LTV, payback period"
### Budget Templates
Personal and business budgets:
- **Personal Budget**: "Create a monthly personal budget tracker with income, fixed expenses, variable expenses, and savings goals"
- **Household Budget**: "Build a family budget spreadsheet with categories for housing, food, transportation, etc."
- **Project Budget**: "Create a project budget template with phases, resources, and variance tracking"
- **Marketing Budget**: "Build a marketing budget spreadsheet with channels, planned vs actual, and ROI tracking"
- **Event Budget**: "Create a wedding budget spreadsheet with vendor categories and payment tracking"
### Data Trackers
Organized tracking for any data:
- **Fitness Tracker**: "Create a workout log spreadsheet with exercises, sets, reps, weights, and progress charts"
- **Habit Tracker**: "Build a daily habit tracking spreadsheet with monthly overview"
- **Inventory Tracker**: "Create an inventory management spreads_meta.json
{
"ownerId": "kn7a96cj9q65e0bhmzahv790en80ffqm",
"slug": "sheet-cog",
"version": "1.0.3",
"publishedAt": 1770774436749
}Editorial read
Docs source
CLAWHUB
Editorial quality
ready
CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Skill: sheet-cog Owner: nitishgargiitd Summary: CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily. Tags: latest:1.0.3 Version history: v1.0.3 | 2
Skill: sheet-cog
Owner: nitishgargiitd
Summary: CellCog is built by its own Coding Agent. That same agent builds your spreadsheets. Full Python access for complex data manipulation, formulas, pivot tables, financial models, budget templates, data trackers, projections, and Excel/XLSX generation — powered by the engineering brain that develops an entire AI platform daily.
Tags: latest:1.0.3
Version history:
v1.0.3 | 2026-02-11T01:47:16.749Z | user
author and dependencies fields to metadata for better attribution and install clarity.v1.0.2 | 2026-02-06T23:19:47.787Z | auto
v1.0.1 | 2026-02-05T05:48:57.814Z | user
Sheet-cog v1.0.1 Changelog:
create_chat pattern and notification-based execution (fire-and-forget, no polling).v1.0.0 | 2026-02-04T03:40:43.809Z | user
Archive index:
Archive v1.0.3: 2 files, 3832 bytes
Files: SKILL.md (8405b), _meta.json (128b)
File v1.0.3:SKILL.md
CellCog is built by its own Coding Agent. That same agent builds your spreadsheets.
Full Python access, complex data manipulation, formulas, pivot tables, and financial models — powered by the engineering brain that develops an entire AI platform daily. Not a template filler. A programmer that understands your data and builds exactly what you need.
This skill requires the cellcog skill for SDK setup and API calls.
clawhub install cellcog
Read the cellcog skill first for SDK setup. This skill shows you what's possible.
Quick pattern (v1.0+):
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your spreadsheet request]",
notify_session_key="agent:main:main",
task_label="spreadsheet-task",
chat_mode="agent" # Agent mode handles most spreadsheets well
)
# Daemon notifies you when complete - do NOT poll
Professional financial analysis and projections:
Personal and business budgets:
Organized tracking for any data:
Operational spreadsheets:
Data analysis and calculations:
CellCog spreadsheets can include:
| Feature | Description | |---------|-------------| | Formulas | SUM, AVERAGE, IF, VLOOKUP, and complex calculations | | Formatting | Headers, colors, borders, number formats, conditional formatting | | Charts | Bar, line, pie charts embedded in sheets | | Multiple Sheets | Organized workbooks with linked sheets | | Data Validation | Dropdowns, input restrictions | | Named Ranges | For cleaner formulas | | Print Layout | Ready for printing/PDF |
| Format | Best For | |--------|----------| | XLSX | Editable in Excel, Google Sheets, Numbers | | Interactive HTML | Web-based calculators and tools |
| Scenario | Recommended Mode |
|----------|------------------|
| Budget templates, trackers, data tables, basic calculations | "agent" |
| Complex financial models with multi-scenario analysis, intricate formulas | "agent team" |
Default to "agent" for most spreadsheet requests. CellCog's agent mode handles formulas, formatting, charts, and data organization efficiently.
Reserve "agent team" for complex financial modeling requiring deep accuracy validation—like DCF models, multi-scenario projections, or interconnected workbooks where formula correctness is critical.
SaaS financial model:
"Create a 3-year SaaS financial model with:
Assumptions Sheet:
- Starting MRR: $10,000
- Monthly growth rate: 15%
- Churn rate: 3%
- Average revenue per customer: $99
- CAC: $500
- Gross margin: 80%
Monthly P&L: Revenue, COGS, Gross Profit, Operating Expenses (broken down), Net Income
Key Metrics: MRR, ARR, Customers, Churn, LTV, CAC, LTV:CAC ratio
Charts: MRR growth, customer growth, profitability timeline
Include scenario toggles for growth rate (10%, 15%, 20%)."
Personal budget:
"Create a monthly personal budget spreadsheet:
Income Section: Salary, side income, other
Fixed Expenses: Rent, utilities, insurance, subscriptions, loan payments
Variable Expenses: Groceries, dining out, transportation, entertainment, shopping, health
Savings: Emergency fund, retirement, vacation fund
Include:
- Monthly summary with % of income per category
- Year-at-a-glance sheet with monthly totals
- Pie chart showing expense breakdown
- Conditional formatting (red if over budget)
Assume $5,000/month income."
Sales tracker:
"Build a sales pipeline tracker spreadsheet with:
Columns: Company, Contact, Deal Value, Stage (dropdown: Lead, Qualified, Proposal, Negotiation, Closed Won, Closed Lost), Probability, Expected Close Date, Notes, Last Contact
Calculations: Weighted pipeline value, deals by stage, win rate
Dashboard Sheet: Pipeline by stage (funnel chart), monthly forecast, top 10 deals, activity metrics
Include sample data for 20 deals."
Break-even analysis:
"Create a break-even analysis spreadsheet:
Inputs:
- Fixed costs (rent, salaries, etc.)
- Variable cost per unit
- Selling price per unit
Calculations:
- Break-even units
- Break-even revenue
- Margin of safety
Sensitivity table: Show break-even at different price points
Chart: Cost-volume-profit graph showing break-even point
Default values: Fixed costs $50,000/month, variable cost $15/unit, price $25/unit."
Specify the structure: List the sheets, columns, and calculations you need.
Provide assumptions: For financial models, give starting numbers and growth rates.
Mention formulas needed: "Include VLOOKUP for...", "Calculate running totals", "Show variance vs plan."
Request sample data: "Include realistic sample data for testing" helps see it in action.
Describe formatting: "Conditional formatting for negative values", "Currency format", "Freeze header row."
Chart preferences: "Include a line chart showing trend", "Pie chart for breakdown."
File v1.0.3:_meta.json
{ "ownerId": "kn7a96cj9q65e0bhmzahv790en80ffqm", "slug": "sheet-cog", "version": "1.0.3", "publishedAt": 1770774436749 }
Archive v1.0.2: 2 files, 3814 bytes
Files: SKILL.md (8374b), _meta.json (128b)
File v1.0.2:SKILL.md
CellCog is built by its own Coding Agent. That same agent builds your spreadsheets.
Full Python access, complex data manipulation, formulas, pivot tables, and financial models — powered by the engineering brain that develops an entire AI platform daily. Not a template filler. A programmer that understands your data and builds exactly what you need.
This skill requires the CellCog mothership skill for SDK setup and API calls.
clawhub install cellcog
Read the cellcog skill first for SDK setup. This skill shows you what's possible.
Quick pattern (v1.0+):
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your spreadsheet request]",
notify_session_key="agent:main:main",
task_label="spreadsheet-task",
chat_mode="agent" # Agent mode handles most spreadsheets well
)
# Daemon notifies you when complete - do NOT poll
Professional financial analysis and projections:
Personal and business budgets:
Organized tracking for any data:
Operational spreadsheets:
Data analysis and calculations:
CellCog spreadsheets can include:
| Feature | Description | |---------|-------------| | Formulas | SUM, AVERAGE, IF, VLOOKUP, and complex calculations | | Formatting | Headers, colors, borders, number formats, conditional formatting | | Charts | Bar, line, pie charts embedded in sheets | | Multiple Sheets | Organized workbooks with linked sheets | | Data Validation | Dropdowns, input restrictions | | Named Ranges | For cleaner formulas | | Print Layout | Ready for printing/PDF |
| Format | Best For | |--------|----------| | XLSX | Editable in Excel, Google Sheets, Numbers | | Interactive HTML | Web-based calculators and tools |
| Scenario | Recommended Mode |
|----------|------------------|
| Budget templates, trackers, data tables, basic calculations | "agent" |
| Complex financial models with multi-scenario analysis, intricate formulas | "agent team" |
Default to "agent" for most spreadsheet requests. CellCog's agent mode handles formulas, formatting, charts, and data organization efficiently.
Reserve "agent team" for complex financial modeling requiring deep accuracy validation—like DCF models, multi-scenario projections, or interconnected workbooks where formula correctness is critical.
SaaS financial model:
"Create a 3-year SaaS financial model with:
Assumptions Sheet:
- Starting MRR: $10,000
- Monthly growth rate: 15%
- Churn rate: 3%
- Average revenue per customer: $99
- CAC: $500
- Gross margin: 80%
Monthly P&L: Revenue, COGS, Gross Profit, Operating Expenses (broken down), Net Income
Key Metrics: MRR, ARR, Customers, Churn, LTV, CAC, LTV:CAC ratio
Charts: MRR growth, customer growth, profitability timeline
Include scenario toggles for growth rate (10%, 15%, 20%)."
Personal budget:
"Create a monthly personal budget spreadsheet:
Income Section: Salary, side income, other
Fixed Expenses: Rent, utilities, insurance, subscriptions, loan payments
Variable Expenses: Groceries, dining out, transportation, entertainment, shopping, health
Savings: Emergency fund, retirement, vacation fund
Include:
- Monthly summary with % of income per category
- Year-at-a-glance sheet with monthly totals
- Pie chart showing expense breakdown
- Conditional formatting (red if over budget)
Assume $5,000/month income."
Sales tracker:
"Build a sales pipeline tracker spreadsheet with:
Columns: Company, Contact, Deal Value, Stage (dropdown: Lead, Qualified, Proposal, Negotiation, Closed Won, Closed Lost), Probability, Expected Close Date, Notes, Last Contact
Calculations: Weighted pipeline value, deals by stage, win rate
Dashboard Sheet: Pipeline by stage (funnel chart), monthly forecast, top 10 deals, activity metrics
Include sample data for 20 deals."
Break-even analysis:
"Create a break-even analysis spreadsheet:
Inputs:
- Fixed costs (rent, salaries, etc.)
- Variable cost per unit
- Selling price per unit
Calculations:
- Break-even units
- Break-even revenue
- Margin of safety
Sensitivity table: Show break-even at different price points
Chart: Cost-volume-profit graph showing break-even point
Default values: Fixed costs $50,000/month, variable cost $15/unit, price $25/unit."
Specify the structure: List the sheets, columns, and calculations you need.
Provide assumptions: For financial models, give starting numbers and growth rates.
Mention formulas needed: "Include VLOOKUP for...", "Calculate running totals", "Show variance vs plan."
Request sample data: "Include realistic sample data for testing" helps see it in action.
Describe formatting: "Conditional formatting for negative values", "Currency format", "Freeze header row."
Chart preferences: "Include a line chart showing trend", "Pie chart for breakdown."
File v1.0.2:_meta.json
{ "ownerId": "kn7a96cj9q65e0bhmzahv790en80ffqm", "slug": "sheet-cog", "version": "1.0.2", "publishedAt": 1770419987787 }
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-nitishgargiitd-sheet-cog/snapshot"
curl -s "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/contract"
curl -s "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/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-nitishgargiitd-sheet-cog/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "CLAWHUB",
"generatedAt": "2026-04-17T06:21:50.787Z"
}
},
"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": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Clawhub",
"href": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceUrl": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"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-nitishgargiitd-sheet-cog/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "2.6K downloads",
"href": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceUrl": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "latest_release",
"category": "release",
"label": "Latest release",
"value": "1.0.3",
"href": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceUrl": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceType": "release",
"confidence": "medium",
"observedAt": "2026-02-11T01:47:16.749Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/clawhub-nitishgargiitd-sheet-cog/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "release",
"title": "Release 1.0.3",
"description": "- Added explicit `author` and `dependencies` fields to metadata for better attribution and install clarity. - Minor text improvements, such as clarifying that CellCog is required as a dependency. - No code or feature changes; documentation only.",
"href": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceUrl": "https://clawhub.ai/nitishgargiitd/sheet-cog",
"sourceType": "release",
"confidence": "medium",
"observedAt": "2026-02-11T01:47:16.749Z",
"isPublic": true
}
]Sponsored
Ads related to sheet-cog and adjacent AI workflows.