Results for “refund-policy”

Comprehensive retail customer returns specialist for processing returns, exchanges, and refunds across in-store, online, and omnichannel retail — handling policy enforcement, fraud prevention, customer retention, vendor returns, and returns analytics to maximize recovery while preserving customer loyalty

Use to audit whether similar customers with similar failures received similar redress, and to find variation that could not be defended. Trigger for "are our refunds consistent", "do we compensate similar cases the same way", "audit our goodwill decisions", redress fairness review, customers who escalate getting more, or a complaint that someone else was treated better.

The relevant axis is not "how do we deploy" but "how fast and how cheaply can we

Review governed memory proposals, policy tags, tombstones, and effective memory.

`analysis-agent`/`task-agent`/`review-agent`: use for release identity, compatibility, exposure, stop, rollback, or recovery; skip pipeline-only and no-release work.

Re-onboard a churned customer with the same care they got the first time. Reads why they left and whether they left the door open, picks the ones worth winning back, and builds a warm re-onboarding sequence, not a "we miss you" discount blast. Built for any post-sale or growth team, customizable to your product and win-back window. Trigger on "win back churned customers", "re-engage a lost account", "build a win-back sequence", "which churned customers should we chase", "boomerang play", "re-onboard a customer who left", or any win-back question.

Strategic decision retrospective — review research decisions against actual outcomes, update confidence levels

Write user-facing copy following Sentry's brand guidelines, covering Plain Speech and Sentry Voice tones for UI text, documentation, and marketing content.

Rolls back Open-workspace phase or plan commits using a phase manifest with dependency checks and a confirmation gate, preserving history via git revert.

Review protected asset policy and risky local data surfaces.

Provides evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflows for sales snapshots, pricing comparisons, duplicate-charge diagnosis, or code-backed billing reality.

Design or revise a company's commercial policy governing discounts, approver thresholds, exception flows, and deal frameworks using data-backed matrices and linting tools.

Reduces churn through cancel flows, dunning, and win-back. Use when the user requests 'churn', 'cancel flow', 'dunning', 'win-back', 'failed payment', 'retention rate', or 'save offer'.

Food order (Foodora via ordercli)

Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).

Shop catalog search, checkout, order tracking, returns.

Reduce churn with cancellation flows, save offers, and win-back campaigns.

Use when responding to a Revise & Resubmit decision from AER, AER:Insights, or an AEJ, and a point-by-point response letter plus aligned manuscript revisions are needed. Handles triage, the concede / clarify / push-back decision, and the response-letter format that editors actually read.

Research a customer question across docs, changelogs, and past tickets, then answer with source attribution, a confidence rating, and honest gaps.

Turn owner feedback about agent behavior into concrete system changes. Use when the owner says something is off, wants the assistant to improve how it operates, asks for a reflection, or wants a durable fix instead of a one-off apology.

Referral and partnership marketing strategist. Use when the user requests 'referral program', 'affiliate', 'partner program', 'refer-a-friend', 'word-of-mouth', or 'commission structure'.

Imported skill faq_database from openai

Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences.

Error Recovery Playbook

The single most useful question before analysing anything is: *what does it cost

Recover a PR whose head SHA disagrees with its branch ref (webhook desync). Force-push and close+reopen rarely fix it — recreate the PR.

Integrate PayPal payment processing with support for express checkout, subscriptions, and refund management. Use when implementing PayPal payments, processing online transactions, or building e-commerce checkout flows.

Provides safe, reversible database schema change patterns for PostgreSQL, MySQL, and common ORMs, with guidance on zero-downtime deployments, rollbacks, and migration tooling.

Integrate an exact reviewed PR under repository policy, choose truthful history semantics, and verify cleanup

Operate customer billing workflows such as subscriptions, refunds, churn triage, billing-portal recovery, and plan analysis using connected billing tools like Stripe.

Turn interactive commit reviews back on for the current herdr workspace.

Use to design or audit a QA dispute and appeal workflow with timeboxes, adjudication standards, and second-level consistency so appeals improve trust instead of rewriting scores without rules. Trigger for "QA appeal process", "agents disputing scores", "who adjudicates QA disputes", "overturn rate too high", second-level review standards, or calibration erosion from ad-hoc score changes.

Refine a ticket interactively until it is ready for planning.

Run a structured churn-save play for an at-risk account to diagnose root cause and reverse the decision.

Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility. Use PROACTIVELY for legacy system updates, framework migrations, or technical debt reduction.