Ads Sales Proposal

Build persuasive sales proposals and close plans for ad services spanning Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Sho...

Security Scan

The skill is an instruction-only proposal generator whose requested resources, instructions, and scope align with its advertised purpose and it does not request credentials, installs, or system access.

Purpose & Capability

Name, description, and required artifacts are consistent: the skill describes building ad sales proposals across specific ad platforms and contains workflow, decision rules, and examples that match that purpose. It does not request unrelated tools, credentials, or platform access.

Instruction Scope

SKILL.md instructions focus on drafting proposal content, objection handling, and close plans. They do not instruct reading files, accessing system state, calling external endpoints, or collecting unrelated secrets. A mention of 'escalate with a structured handoff payload' appears to mean handing off to humans and there is no endpoint or transmission specified.

Install Mechanism

No install spec and no code files — instruction-only. That minimizes disk writes and external code execution risk.

Credentials

The skill declares no required environment variables, no primary credential, and no config paths. There is no disproportionate request for credentials or secrets.

Persistence & Privilege

always is false and default autonomous invocation is allowed (platform default). The skill does not request permanent presence or system-level configuration changes.

Assessment

This skill appears internally consistent and limited to producing proposal text. Before installing or using it with real client work, consider: (1) do not feed sensitive PII or client secrets into prompts unless you are comfortable with how your agent handles data; (2) review generated KPI promises and legal/policy statements — the guardrail 'never fabricate metrics' is advisory only, so validate outputs before sending to clients; (3) 'escalate with a structured handoff payload' is ambiguous—if you plan to automate handoffs, ensure no sensitive data is transmitted to external systems; and (4) keep an eye on updates to the skill and test outputs on safe examples first. No static-scan findings were available because this is an instruction-only skill.

Purpose

Core mission:

• proposal architecture, objection handling, closing path

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

• ad execution guidance tied to business outcomes
• growth decisions involving revenue, roas, cpa, or budget efficiency
• platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads
• this specific capability: proposal architecture, objection handling, closing path

High-signal keywords:

• ads, advertising, campaign, growth, revenue, profit
• roas, cpa, roi, budget, bidding, traffic, conversion, funnel
• meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

• client_request: what the client wants to achieve
• business_context: product, margin, seasonality
• offer_scope: service package or campaign scope

Optional:

• objections
• competitor_reference
• contract_constraints
• expected_start_date

Output Contract

1. Proposal Positioning
2. Scope and Deliverables
3. ROI Logic and KPI Commitment Range
4. Objection Handling Script
5. Close Plan with next steps

Workflow

1. Summarize client objective and urgency.
2. Translate objective into measurable ad outcomes.
3. Build value argument and risk controls.
4. Prepare objection responses and confidence proof.
5. Output a close-ready proposal structure.

Decision Rules

• If goal is vague, anchor on one north-star KPI first.
• If budget is low, propose phased pilot with strict milestone gates.
• If trust is low, lead with transparent assumptions and reporting cadence.

Platform Notes

Primary scope:

• Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Platform behavior guidance:

• Keep recommendations channel-aware; do not collapse all channels into one generic plan.
• For Meta and TikTok Ads, prioritize creative testing cadence.
• For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
• For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

• Never fabricate metrics or policy outcomes.
• Separate observed facts from assumptions.
• Use measurable language for each proposed action.
• Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

• If critical inputs are missing, ask for only the minimum required fields.
• If platform constraints conflict, show trade-offs and a safe default.
• If confidence is low, mark it explicitly and provide a validation checklist.
• If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Proposal Skeleton

section: Objective
section: Channel Plan
section: Budget and KPI Range
section: Risks and Mitigation
section: Next-step Commitment

Objection Response Map

objection: "CPA too high"
response: "Pilot 14 days with capped budget and clear stop-loss"

Examples

Example 1: Performance growth proposal

Input:

• Client wants lower CPA in 30 days
• Current channels: Meta + Google Ads

Output focus:

• pilot scope
• KPI promise range
• close checklist

Example 2: New product launch proposal

Input:

• Client has no baseline data
• Wants global ads rollout

Output focus:

• phased contract scope
• risk clauses
• reporting cadence

Example 3: Renewal negotiation proposal

Input:

• Existing client doubts ROI
• Needs proof before extension

Output focus:

• retrospective evidence summary
• revised operating model
• signed next-step plan

Quality Checklist

• Required sections are complete and non-empty
• Trigger keywords include at least 3 registry terms
• Input and output contracts are operationally testable
• Workflow and decision rules are capability-specific
• Platform references are explicit and concrete
• At least 3 practical examples are included