Rulebase Skills

Use to audit QA coverage and scorecard health in a Rulebase workspace via the Rulebase MCP server. Trigger for "audit our QA coverage", "which agents or channels aren't being evaluated", "are our QA scores meaningful", "is our scorecard working", QA blind spots, score distribution or ceiling effects, and checking whether QA scores relate to SLA or complaint outcomes.

Use to compare a support data retention policy against what is actually still stored, and find both over-retention and premature deletion. Trigger for "are we deleting support data on time", "retention audit", "how long do we keep transcripts", "we still have data from 2018", conflicting retention obligations, or preparing for a data protection review.

Use to fulfil a subject access request from support data — finding everything about the person, and deciding what must be redacted before disclosure. Trigger for "handle this SAR", "subject access request", "customer wants all their data", DSAR fulfilment from support systems, "a customer asked for their call recordings", or an employee requesting their own QA records.

Use to assemble a fair, evidence-backed coaching pack for a support agent's one-to-one from QA evaluations and conversation history. Trigger for "prepare a coaching session for X", "what areas does X need to improve", "areas of markdown for this agent", "what coaching opportunities stand out", "build a coaching agenda from these tickets", or preparing a weekly or monthly agent review.

Use to measure whether a support bot, AI agent, or self-service channel actually reduces contact volume, and to audit a vendor's containment or deflection number. Trigger for "what's our real deflection rate", "is the bot working", "our containment rate is 70% but tickets haven't dropped", automation ROI, self-service savings, AI agent resolution rate, or designing a holdout test for a support bot.

Use to analyse why support contacts escalate, how long escalations take, and which escalation paths are broken or missing. Trigger for "why are escalations increasing", "how long do escalations take", "which issues get escalated most", tier 2 volume, back-office handoffs, escalations with no defined path, or designing an escalation process.

Use to distil a CX dashboard into the three numbers a board or exec actually needs — volume/demand health, quality/outcome, and cost/efficiency — with commentary that drives decisions instead of forty tiles nobody acts on. Trigger for "board pack", "exec summary for support", "what should leadership see", "too many metrics on the dashboard", "three KPIs for the board", quarterly business review CX section, or when a leadership deck is mostly charts with no story.

Use to recover a day in real time when volume, handle time or availability diverge from plan — reforecasting decisions, break moves, overtime, callbacks and skill flex without burning tomorrow. Trigger for "intraday management", "real-time reforecast", "we are underwater at 11am", move breaks or lunches, call people back in, flex agents between queues, ride out the spike, or when the WFM plan is wrong before close of business.

Use to assign ownership, set review cadence, and deprecate support content without breaking self-service or AI grounding. Trigger for "who owns this article", "our KB is out of date", orphan articles, annual review calendar nobody follows, deprecating help content, knowledge governance, or preventing stale articles from quietly harming customers.

Use to write CX commentary that makes a number decision-ready — what moved, why (decomposed), so what, do what — separating noise from signal and stating confidence honestly. Trigger for "write the commentary", "explain this trend", "what should we say about the drop", weekly or monthly narrative, board pack prose, "why did QA fall", metric movement write-up, or when a report has charts but no story.

Use to export CSAT or satisfaction survey responses from a support platform into one canonical shape. Trigger for "export our CSAT data", "pull satisfaction ratings", "get survey responses out of Zendesk/Freshdesk/Gorgias/HubSpot", joining CSAT to tickets, or when a conversation export left the csat field null.

Use to analyse the help-centre funnel from search through article view to contact, find actionable drop-off, and align KB content to contact drivers. Trigger for "self-service funnel", "contact after viewing an article", "why doesn't the help centre deflect", KB deflection rate, search-to-contact conversion, or article effectiveness.

Use to analyse billing and pricing complaints, separating genuine pricing objections from billing defects and unclear communication. Trigger for "customers complaining about price", "billing complaint analysis", "why do customers dispute their invoice", "is our pricing a problem", unexpected-charge complaints, or a pricing decision that needs evidence from support.

Design a refund, credit, and goodwill framework that separates owed redress from discretionary gestures, sets agent authority based on actual distributions, and enables consistent, auditable outcomes without escalating every request.

Use to design the process that gets a revenue signal out of support and to the account owner without turning agents into sellers or degrading support quality. Trigger for "route upsell leads from support to sales", "support-sourced pipeline process", "should agents flag opportunities", designing a CS-to-sales handoff, or a handoff programme where agents have stopped flagging.

Use to monitor support conversations for conduct risk — pressure, mis-selling, unfair outcomes, obstruction and misleading statements — as distinct from whether the answer matched policy. Trigger for "monitor for mis-selling", "conduct risk in our support conversations", "are agents pressuring customers", "customers being obstructed from cancelling", conduct surveillance, or a conduct finding raised by second line.

Use to identify signals of customer vulnerability in support conversations and audit whether they were recognised and acted on. Trigger for "identify vulnerable customers", "did we spot the vulnerability signals", "customers in financial difficulty", bereavement or health disclosures in support, vulnerable customer handling audits, or designing vulnerability recognition for a support team.

Analyzes chat and call abandonment, queue patience, and what a high FCR may be hiding when abandoned contacts never become tickets.

Use to audit whether customer support is reachable for people with access needs — channels, hours, authentication barriers, CAPTCHA, voice-only paths, and alternate formats. Trigger for "support accessibility audit", "can customers with disabilities reach us", CAPTCHA on contact form, voice-only support, alternate format requests, or accessibility checklist for CX.

Use to design overnight and follow-the-sun support — coverage models, handoff quality and measuring what is lost between shifts. Trigger for "after-hours coverage", "follow the sun", overnight support design, night shift vs defer async, handoff packet, shift handover quality, global coverage gaps, or when customers reopen tickets after every handoff.

Use to analyse average handle time, resolution time or time-in-queue without being misled by the skew, and to find where time actually goes. Trigger for "why is our AHT increasing", "our call handling times are up", "which contact reasons take longest", "how long do tickets take", handle time by agent or team, or an AHT target being set.

Use to audit a help centre or knowledge base against the conversations customers actually have, finding coverage gaps, stale articles and unused content. Trigger for "what should we write help articles about", "audit our knowledge base", KB coverage gaps, self-service deflection content, or preparing a knowledge base to ground an AI support agent.

Use to compare BPO sites, vendors or partner teams fairly, adjusting for the work mix each is given before concluding anything about performance. Trigger for "compare our BPO sites", "which vendor is performing best", "site A scores lower than site B", outsourcer QBR packs, partner MI reporting, or setting contractual quality targets with a vendor.

Use to clean up sprawling helpdesk tags, categories and custom fields so reporting built on them means something. Trigger for "our tags are a mess", "consolidate our ticket categories", "why don't our tag reports add up", duplicate or near-duplicate tags, tags nobody uses, agents tagging inconsistently, or before building reporting on top of tags.

Use to keep localised help centre content current when the source language changes, detect stale translations, and prevent silent lag between markets. Trigger for "translations are out of date", localisation workflow, source of truth language, help centre i18n, translation drift after policy update, or non-English customers seeing old policy.

Use to audit a customer-facing support bot or AI agent for harm rather than for volume — manipulation and prompt-injection attempts, customers stranded without a human, fabricated answers, and unsafe commitments or disclosures. Trigger for "are people trying to jailbreak our bot", "show me attempts to manipulate the assistant", "is our bot giving wrong answers", "customers stuck with the bot and never got a human", or reviewing an AI agent before or after launch.

Use to design or audit the executive escalation path for a major account — intake, ownership, communication cadence and follow-through — so escalations are resolved rather than merely attended. Trigger for "design our escalation process for key accounts", "an executive escalation went badly", "customer went to our CEO", red account war rooms, or escalations that get attention and then quietly stall.

Use to design or audit complaint identification and classification in customer support, especially in regulated sectors. Trigger for "are we identifying complaints correctly", "complaint detection", regulatory complaint definition, FCA or CFPB complaint handling, vulnerable customer identification, root cause categorisation for complaints, or building an AI classifier for complaints.

Use to find personal data support collects and stores that nothing actually uses, and to stop collecting it. Trigger for "do we collect too much data", "which fields do we actually use", data minimisation review, "why do we ask customers for this", reducing breach exposure, or a form that grew a field every quarter.

Use to measure which help articles actually resolve contacts versus merely being read, including contact-after-view and assisted resolution. Trigger for "are our help articles working", article view counts misleading, deflection measurement, contact after reading an article, self-service success metrics, KB ROI, or stopping AI agents from optimising for page views.

Use to compare CX performance to a published or vendor benchmark without fooling yourself — scope mismatch, survivor bias, and definition mismatch usually make external benchmarks incomparable, and internal baselines often beat them. Trigger for "how do we compare to industry", "is our CSAT good", benchmark slide for the board, vendor benchmark report, "are we above average", outsourcing RFP benchmarks, or when someone cites a round-number industry standard.

Use to merge overlapping help articles without breaking search, bookmarks, or AI grounding — choosing a canonical page, setting redirects, and measuring post-merge impact. Trigger for "we have duplicate KB articles", consolidate help centre content, merge knowledge base articles, KB deduplication, article redirects, canonical help article, or overlapping docs confusing customers and search.

Use to draw a defensible sample of support conversations for QA review, an audit or a manual analysis, so the results generalise to the population rather than to whatever was easy to pull. Trigger for "which tickets should we review", "how do we pick a sample", "is our QA sampling representative", stratified or risk-based sampling, review coverage design, or a finding based on a handful of hand-picked tickets.

Use to turn an ad-hoc CX reporting request into a versioned spec that can be re-run each period and actually compared across periods. Trigger for weekly or monthly QA and support reports, "same report but for last week", "generate the weekly digest", "supervisor report for each team", a report request pasted as a long prompt for the second or third time, or when two runs of the same report disagree.

Use to build and maintain a reusable bank of QA criteria as observable decision rules shared across scorecards. Trigger for "criterion library", "standardise our QA criteria", "write better rubric items", "was professional is too vague", versioning criteria across teams, or turning adjectives into pass/fail decision rules with examples.

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.

Use to staff and schedule QA reviewers for sustainable throughput without grading quality collapsing — fatigue, drift, and false precision from treating reviewers like production agents. Trigger for "how many QA reviewers do we need", reviewer capacity planning, grader fatigue, throughput per reviewer, calibration after long shifts, or scores drifting over the course of a day.

Use to review how call recordings are notified, stored, accessed, redacted and deleted, including the parts that differ from text conversations. Trigger for "review our call recording practices", "do we need to tell customers we're recording", "who can listen to our calls", recording retention, card details spoken on a call, or a request for a customer's own recording.

Use to assemble evidence that customers are getting good outcomes from support, at the level a board or regulator expects, rather than reporting activity metrics. Trigger for "evidence our customers get good outcomes", "consumer duty evidence from support", "board report on customer outcomes", outcomes-based regulatory reporting, or a request to show harm is not occurring.

Use to find where support agents cross from information into regulated advice or a personal recommendation, and to design the boundary so they can still be helpful. Trigger for "are agents giving advice", "where's the line between information and advice", "should agents recommend a product", guidance versus advice boundary, agents answering "what would you do", or a complaint that an agent recommended something.