Agent skill

Sales Operations

Sales operations across CRM, analytics, territory planning, and compensation.

Install Sales Operations

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sales-success/sales-operations .claude/skills/sales-operations && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .claude/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/sales-success/sales-operations .agents/skills/sales-operations && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .agents/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/sales-success/sales-operations .cursor/skills/sales-operations && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .cursor/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/borghei/Claude-Skills.git --path sales-success/sales-operations

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/sales-success/sales-operations .gemini/skills/sales-operations && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .gemini/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/sales-success/sales-operations .github/skills/sales-operations && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .github/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add borghei/Claude-Skills --skill sales-operations -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install borghei/Claude-Skills sales-operations --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/sales-success/sales-operations .opencode/skills/sales-operations && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "sales-operations" agent skill from https://github.com/borghei/Claude-Skills/tree/main/sales-success/sales-operations into .opencode/skills/sales-operations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sales-operations", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: sales-operations
GitHub stars: 886
Token cost: ~3.7k tokens
SKILL.md length: 1,343 words
Files: 4 (incl. scripts)
Skills in repo: 354
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Sales operations across CRM, analytics, territory planning, and compensation.

Works in 7 steps: Assess current state -- Audit CRM data… → Analyze pipeline health -- Calculate… → Design or refine territories -- Balance… → …
Building pipeline reports
SKILL.md covers Clarify First, Workflow, Sales Metrics Framework and Account Scoring, plus 11 more sections
Runs Python scripts from its folder; calls python

What it does

Sales Operations is an agent skill from borghei/Claude-Skills. Sales operations across CRM, analytics, territory planning, and compensation. Use when building pipeline reports, designing territories, setting quotas, creating comp plans, or auditing CRM data quality.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/forecast_analyzer.py`, `scripts/quota_calculator.py` and `scripts/territory_planner.py`).

It sits in Data & Analytics, covering Data cleaning. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

Building pipeline reports
Designing territories
Creating comp plans
Auditing CRM data quality

Example prompts

“Use the sales-operations skill to sale operations across CRM, analytics, territory planning, and compensation”
“/sales-operations”

Requirements

Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

Assess current state -- Audit CRM data quality, pipeline coverage, and rep performance baselines. Validate that required fields are…
Analyze pipeline health -- Calculate coverage ratios, stage conversion rates, velocity metrics, and deal aging. Flag bottlenecks where…
Design or refine territories -- Balance territories by opportunity potential, workload, and geographic/industry alignment. Score accounts…
Model quotas -- Run top-down (revenue target / capacity) and bottom-up (account potential analysis) models. Reconcile and risk-adjust.
Architect compensation -- Structure OTE splits, commission tiers, accelerators, and SPIFs aligned to company stage and selling motion.
Build forecast -- Categorize deals by confidence tier, apply probability weights, and surface the gap-to-quota with required win rates.
Validate and iterate -- Cross-check outputs against historical actuals. Confirm territory balance, quota fairness, and forecast accuracy…

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sales Operations loads about 3.7k tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 1,343 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~55
When it runs · the whole SKILL.md, loaded when a task matches: ~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 1,343 words, ~3,660 tokens.

Download SKILL.mdSave it as .claude/skills/sales-operations/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: sales-operations
description: Sales operations across CRM, analytics, territory planning, and compensation. Use when building pipeline reports, designing territories, setting quotas, creating comp plans, or auditing CRM data quality.
license: MIT + Commons Clause
metadata.version: 1.0.0
metadata.author: borghei
metadata.category: sales-success
metadata.updated: 2026-03-31
metadata.tags: sales-ops, crm, analytics, territory, compensation

Sales Operations

The agent operates as an expert sales operations professional, delivering revenue infrastructure through analytics, territory design, quota modeling, compensation architecture, and process optimization.

Clarify First

Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

Which deliverable — pipeline report, territory design, quota model, comp plan, or forecast (selects the script and the input data)
Revenue target + rep capacity — the company number and ramped headcount (drives top-down quota and coverage math)
Selling motion + company stage — new-business vs. expansion mix, segment, and growth rate (shapes comp splits, accelerators, and territory balance)
Historical actuals — prior win rates, stage conversion, and cycle times (calibrate forecast weights and quota risk-adjustment)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflow

Assess current state -- Audit CRM data quality, pipeline coverage, and rep performance baselines. Validate that required fields are populated and stage dates are current.
Analyze pipeline health -- Calculate coverage ratios, stage conversion rates, velocity metrics, and deal aging. Flag bottlenecks where conversion drops below historical norms.
Design or refine territories -- Balance territories by opportunity potential, workload, and geographic/industry alignment. Score accounts to inform assignment.
Model quotas -- Run top-down (revenue target / capacity) and bottom-up (account potential analysis) models. Reconcile and risk-adjust.
Architect compensation -- Structure OTE splits, commission tiers, accelerators, and SPIFs aligned to company stage and selling motion.
Build forecast -- Categorize deals by confidence tier, apply probability weights, and surface the gap-to-quota with required win rates.
Validate and iterate -- Cross-check outputs against historical actuals. Confirm territory balance, quota fairness, and forecast accuracy before publishing.

Sales Metrics Framework

Activity Metrics:

Metric	Formula	Target
Calls/Day	Total calls / Days	50+
Meetings/Week	Total meetings / Weeks	15+
Proposals/Month	Total proposals / Months	8+

Pipeline Metrics:

Metric	Formula	Target
Pipeline Coverage	Pipeline / Quota	3x+
Pipeline Velocity	Won Deals / Avg Cycle Time	--
Stage Conversion	Stage N+1 / Stage N	Varies

Outcome Metrics:

Metric	Formula	Target
Win Rate	Won / (Won + Lost)	25%+
Average Deal Size	Revenue / Deals	Context-dependent
Sales Cycle	Avg days to close	<60
Quota Attainment	Actual / Quota	100%+

Account Scoring

python

def score_account(account):
    """Score accounts for territory assignment and prioritization."""
    score = 0

    # Company size (0-30 points)
    if account['employees'] > 5000:
        score += 30
    elif account['employees'] > 1000:
        score += 20
    elif account['employees'] > 200:
        score += 10

    # Industry fit (0-25 points)
    if account['industry'] in ['Technology', 'Finance']:
        score += 25
    elif account['industry'] in ['Healthcare', 'Manufacturing']:
        score += 15

    # Engagement (0-25 points)
    if account['website_visits'] > 10:
        score += 15
    if account['content_downloads'] > 0:
        score += 10

    # Intent signals (0-20 points)
    if account['intent_score'] > 80:
        score += 20
    elif account['intent_score'] > 50:
        score += 10

    return score  # Max 100; 70+ = Tier 1, 40-69 = Tier 2, <40 = Tier 3

Territory Design

The agent balances territories across three dimensions:

Balance -- Similar opportunity potential, comparable workload, fair distribution across reps.
Coverage -- Geographic proximity, industry alignment, existing account relationships.
Growth -- Room for expansion, career progression paths, untapped market potential.

Example: Territory Allocation Table

Territory	Rep	Accounts	ARR Potential	Quota	Coverage
West Enterprise	Rep A	45	$3.0M	$2.7M	111%
East Mid-Market	Rep B	62	$2.8M	$2.4M	117%
Central (Ramping)	Rep C	38	$2.5M	$1.2M	208%

Quota Setting

Top-Down Model

Company Revenue Target: $50M
  Growth Rate: 30%
  Team Capacity: 20 reps
  Average Quota: $2.5M
  Adjustments: +/-20% based on territory potential

Bottom-Up Model

Account Potential Analysis:
  Existing accounts: $30M
  Pipeline value: $15M
  New logo potential: $10M
  Total: $55M
  Risk adjustment: -10%
  Final: $49.5M

The agent reconciles both models and flags divergence exceeding 10%.

Compensation Architecture

TOTAL ON-TARGET EARNINGS (OTE)
  Base Salary: 50-60%
  Variable: 40-50%
    Commission: 80% of variable
      New Business: 60%
      Expansion: 40%
    Bonus: 20% of variable
      Quarterly accelerators
      SPIFs

COMMISSION RATE TIERS
  0-50% quota:   0.5x rate
  50-100% quota:  1.0x rate
  100-150% quota: 1.5x rate
  150%+ quota:    2.0x rate

Forecasting

Forecast Categories

Category	Definition	Weighting
Closed	Signed contract	100%
Commit	Verbal commit, high confidence	90%
Best Case	Strong opportunity, likely to close	50%
Pipeline	Active opportunity	20%
Upside	Early stage	5%

Example: Weighted Forecast Output

Q4 Forecast - Week 8
  Quota: $10M

  Category       Deals    Amount     Weighted
  Closed         12       $2.4M      $2.4M
  Commit         8        $1.8M      $1.6M
  Best Case      15       $3.2M      $1.6M
  Pipeline       22       $4.5M      $0.9M

  Forecast (Closed + Commit): $4.0M
  Upside (with Best Case): $5.6M
  Gap to Quota: $6.0M
  Required Win Rate on Pipeline: 35%

CRM Data Quality Checklist

The agent validates these fields during every pipeline review:

Required fields populated on all open opportunities
Stage dates updated within the last 7 days
Close dates set to realistic future dates (no past-due)
Deal amounts reflect current pricing discussions
Contact roles assigned with at least one economic buyer
Next steps documented with specific actions and dates

Process Optimization

Sales Process Audit Framework

STAGE ANALYSIS
  Average time in stage -> identify stalls
  Conversion rate per stage -> find drop-off points
  Drop-off reasons -> categorize and address

ACTIVITY ANALYSIS
  Activities per stage -> benchmark against top performers
  Activity-to-outcome ratio -> measure efficiency
  Time allocation -> optimize selling vs. admin time

TOOL UTILIZATION
  CRM adoption rate -> target 95%+ daily login
  Feature usage -> identify underused capabilities
  Data quality score -> track completeness over time
  Automation opportunities -> reduce manual entry

Scripts

bash

# Territory planner
python scripts/territory_planner.py --accounts accounts.csv --reps 10

# Quota calculator
python scripts/quota_calculator.py --data team.csv --quarter Q4-2026

# Forecast analyzer
python scripts/forecast_analyzer.py --data forecast_history.csv --quarters 4

Troubleshooting

Problem	Root Cause	Resolution
Forecast accuracy below 70%	Inconsistent stage definitions; reps over-committing; lack of weighted methodology	Enforce strict stage entry/exit criteria. Apply probability weights by category (Commit 90%, Best Case 50%, Pipeline 20%). Review commit deals individually in weekly forecast calls. Compare rolling 4-quarter actuals to calibrate weights.
Territory imbalance causing rep attrition	Uneven account distribution; potential-to-quota mismatch exceeding 20%	Re-score accounts quarterly using the scoring model. Target less than 15% variance in potential-to-quota ratio across territories. Review territory balance monthly in high-growth periods.
CRM data quality below 80% completeness	Insufficient enforcement; no automated validation; rep adoption gaps	Implement required field validation at stage transitions. Run weekly data quality reports. Tie CRM hygiene to variable compensation (5-10% of bonus). Target 95%+ daily login rate.
Quota attainment below 60% team-wide	Quotas set too aggressively; insufficient pipeline; ramp time underestimated	Reconcile top-down and bottom-up models. Flag divergence exceeding 10%. Risk-adjust for ramp (ramping reps at 50-75% quota). Ensure 3-4x pipeline coverage at quarter start.
Comp plan driving wrong behaviors	Misaligned incentives; rewarding volume over quality; no accelerators	Audit comp plans against strategic objectives. Ensure accelerators kick in at 100% attainment. Weight new business vs. expansion per GTM strategy. Add SPIFs for strategic priorities.
Pipeline coverage drops mid-quarter	Insufficient lead flow; deals pushed or lost faster than replaced	Alert AEs when individual coverage drops below 2.5x. Coordinate with Marketing on lead generation campaigns. Implement minimum weekly prospecting activity requirements.
Stage conversion rates declining	Process bottleneck; missing enablement; competitive pressure	Identify the specific stage with the highest drop-off. Compare top performer conversion rates to team average. Deploy targeted training on the bottleneck stage. Review competitive win/loss data for that stage.

Show full SKILL.md (512 more words)Show less

Success Criteria

Metric	Target	Measurement Method
Forecast accuracy	Within 10% of actual quarterly	Abs(Weighted Forecast - Actual) / Actual
Pipeline coverage ratio	3-4x quota at quarter start	Total pipeline value / Team quota
CRM data completeness	95%+ required fields populated	Weekly automated data quality audit
Territory balance	Less than 15% variance in potential-to-quota	Standard deviation of potential-to-quota ratio across territories
Quota attainment distribution	60%+ of reps at or above quota	Reps at 100%+ / Total ramped reps
Stage conversion rates	Improving or stable QoQ	Stage N+1 entries / Stage N entries per period
Sales cycle length	Trending downward or stable	Average days from opportunity creation to close
Ramp time to productivity	Under 6 months for new hires	Months until new rep reaches 75% of quota run rate
Process adoption	90%+ compliance with defined process	Audit score from monthly process compliance review

Scope & Limitations

In Scope:

CRM administration, data quality management, and process enforcement
Pipeline analytics: coverage ratios, stage conversion, velocity metrics, deal aging
Territory design, account scoring, and balanced assignment optimization
Quota modeling: top-down, bottom-up, and reconciliation approaches
Compensation architecture: OTE splits, commission tiers, accelerators, SPIFs
Forecast methodology: weighted pipeline, category-based, rolling forecasts
Sales process audit: stage analysis, activity benchmarking, tool utilization
Reporting infrastructure and dashboard design

Out of Scope:

Individual deal strategy, qualification, and closing (see account-executive)
Technical demos, RFP responses, and POC management (see sales-engineer)
Post-sale customer management and retention (see customer-success-manager)
Enterprise solution architecture and integration design (see solutions-architect)
Marketing attribution modeling and campaign ROI (see marketing/campaign-analytics)
Financial modeling beyond sales compensation (see finance)

Limitations:

Territory optimization uses heuristic scoring, not mathematical optimization solvers; results are directional, not globally optimal
Quota models require accurate historical data; garbage in, garbage out
Forecast accuracy benchmarks assume consistent CRM hygiene; accuracy degrades with poor data quality
Scripts process CSV/JSON exports only; no direct CRM API connectivity
Compensation modeling does not account for tax implications or local labor law constraints

Integration Points

Integration	Direction	Purpose	Handoff Artifact
Account Executive	Ops -> AE	Territory assignments, quota targets, pipeline reports, forecast templates	Territory map, quota letter, pipeline dashboard, forecast submission form
Sales Engineer	Ops -> SE	Activity tracking, demo conversion metrics, technical win/loss data	SE activity reports, technical evaluation pipeline
Customer Success Manager	Ops -> CSM	Renewal pipeline tracking, expansion revenue attribution, churn reporting	Renewal forecast rollup, NRR reports, churn analysis
Marketing	Bidirectional	Lead attribution, MQL-to-SQL conversion, campaign ROI, pipeline sourcing	Attribution reports, lead routing rules, campaign pipeline reports
Finance	Ops -> Finance	Revenue forecasting, commission calculations, quota-to-capacity planning	Forecast submissions, commission statements, headcount models
Revenue Operations	Bidirectional	Cross-functional GTM metrics, funnel analytics, ARR reporting	Unified revenue dashboard, GTM efficiency metrics
HR	Ops -> HR	Headcount planning, ramp modeling, performance data for reviews	Ramp timelines, quota attainment reports, territory capacity models

Workflow Handoff Protocol:

Sales Ops publishes territory assignments and quota letters at least 2 weeks before quarter start
Sales Ops delivers weekly pipeline report to sales leadership every Monday by 10 AM
Sales Ops collects forecast submissions from AEs every Friday and publishes rolled-up forecast by Monday
Sales Ops runs monthly territory health review and flags imbalances exceeding 15% variance

Files

SKILL.md and 3 other files (scripts) in sales-success/sales-operations of borghei/Claude-Skills.

SKILL.md
scripts/forecast_analyzer.py
scripts/quota_calculator.py
scripts/territory_planner.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Sales Operations next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Pandas ProJeffallan/claude-skills	12k	1 repos	~1.5k	Automated safety check: Pass	MIT	5 days ago

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Questions about Sales Operations

What does Sales Operations do?

Sales operations across CRM, analytics, territory planning, and compensation. Sales Operations is an agent skill from borghei/Claude-Skills. Sales operations across CRM, analytics, territory planning, and compensation.

When should I use Sales Operations?

Sales Operations fits situations like: building pipeline reports; designing territories; creating comp plans; auditing CRM data quality.

How do I install Sales Operations in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill sales-operations -a claude-code`. Or copy the skill folder (sales-success/sales-operations in borghei/Claude-Skills) into .claude/skills/sales-operations in your project. Claude Code loads it when a task matches its description.

How do I install Sales Operations in Codex?

Run `npx skills add borghei/Claude-Skills --skill sales-operations -a codex`. Or copy the skill folder (sales-success/sales-operations in borghei/Claude-Skills) into .agents/skills/sales-operations in your project. Codex loads it when a task matches its description.

Can I use Sales Operations in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill sales-operations -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sales-operations, .gemini/skills/sales-operations, .github/skills/sales-operations and .opencode/skills/sales-operations in your project.

What does Sales Operations need to run?

Going by SKILL.md and its folder, Sales Operations needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Sales Operations access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Sales Operations safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Sales Operations use?

Sales Operations is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sales Operations use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Sales Operations?

Skills that share tags, products or a category with Sales Operations: Clean Data (explorium-ai/gtm-skills, 175 stars), Question2report (refraction-ray/xalpha, 2.7k stars), Dingo Verify (MigoXLab/dingo, 757 stars) and Data Validation (platonai/Browser4, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sales Operations?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 886 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Sales Operations

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Sales Operations

Clarify First

Workflow

Sales Metrics Framework

Account Scoring

Territory Design

Example: Territory Allocation Table

Quota Setting

Top-Down Model

Bottom-Up Model

Compensation Architecture

Forecasting

Forecast Categories

Example: Weighted Forecast Output

CRM Data Quality Checklist

Process Optimization

Sales Process Audit Framework

Scripts

Troubleshooting

Success Criteria

Scope & Limitations

Integration Points

Files

Compare with similar skills

Similar skills

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Related

Questions about Sales Operations