account-executive

account-executive is a skill for Claude Code from aAAaqwq/AGI-Super-Team. It costs 48 tokens per session (2,926 once invoked), scanned A, original, MIT.

A sales-workflow agent for managing opportunities from qualification and customer discovery through demonstrations, proposals, negotiation, and closing.

In plain words
What is it for?
Use it to score leads, run MEDDIC discovery, plan accounts, prepare value-based demos and proposals, handle objections, negotiate, and track deals toward a close.
Why use it?
It gives sales work a structured process for checking whether an opportunity is suitable, understanding the buyer's needs, and forecasting its progress.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/forecast.py --pipeline pipeline.csv --quarter Q4.

Part of the agi-super-team plugin — 194 skills, 1 agent shipped together

Good fit Use it to score leads, run MEDDIC discovery, plan accounts, prepare value-based demos and proposals, handle objections, negotiate, and track deals toward a close.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team
agentmods
npx agentmods add skills/aaaaqwq/agi-super-team/account-executive

Made for: Claude Code.

Or install agi-super-team, the plugin that ships this one along with the rest of its 194 skills, 1 agent.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for account-executive

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
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Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,926 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 125
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.02926
Opus 5 $0.00024 $0.01463
Sonnet 5 $0.00010 $0.00585
Haiku 4.5 $0.00005 $0.00293

Measured 11d ago against content hash f44f4ecbb1aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

account-executive scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/deal_scorer.py, scripts/pipeline_analyzer.py, scripts/win_loss_analyzer.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/account-executive/SKILL.md · 262 lines

How it starts

The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Account Executive

The agent operates as an expert account executive, driving revenue through disciplined pipeline management, structured discovery, value-based selling, strategic negotiation, and accurate forecasting.

Workflow

  1. Qualify the opportunity -- Score the lead against ICP criteria and MEDDIC dimensions. Confirm budget, authority, need, and timeline before advancing. Validate: qualification score reaches 18+ out of 30.
  2. Run discovery -- Execute MEDDIC framework to map Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, and Champion. Document findings in the discovery template. Validate: all six MEDDIC fields populated.
  3. Deliver demo / evaluation -- Present solution mapped to the prospect's specific pain points and use cases. Engage all stakeholders identified during discovery. Validate: technical fit confirmed and champion provides positive feedback.
  4. Build and deliver proposal -- Construct pricing aligned to the prospect's budget and value expectations. Include ROI justification. Validate: proposal accepted or objections documented for negotiation.
  5. Negotiate and close -- Apply trade-based negotiation (never give without getting). Handle objections using the response framework. Validate: contract signed and payment terms confirmed.
  6. Hand off to Customer Success -- Transfer account context including success criteria, stakeholder map, and implementation expectations. Validate: CS acknowledges receipt and kickoff is scheduled.
  7. Update forecast -- Categorize deal accurately by confidence tier. Maintain pipeline hygiene weekly. Validate: all open opportunities have current close dates and documented next steps.

Sales Stages

Stage Probability Entry Criteria Exit Criteria
Prospect 10% Lead meets ICP Meeting scheduled
Discovery 20% Meeting held MEDDIC qualified
Demo/Evaluation 40% Technical fit confirmed Demo delivered, stakeholders engaged
Proposal 60% Budget approved Proposal accepted
Negotiation 80% Terms discussed Contract agreed
Closed Won 100% Signed Payment terms confirmed, CS handoff

Read the full file on GitHub · 262 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 262 lines · 48 tokens per session scan A f44f4ecbb1aa

Subscribe to this mod's changes

account-executive is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 2,926 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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