Security

Use to check that required disclosures, consents and notices were actually given in support conversations — the right wording, at the right point, through a channel the customer could act on. Trigger for "did we give the required disclosure", "are we capturing consent properly", "recording notification audit", "check our mandatory notices", disclosure compliance, or a complaint that a customer was not told something.

Use to find where support routing is failing — misrouted contacts, reassignment chains, unassigned work, and queues nobody owns. Trigger for "why do tickets bounce between teams", "are we routing correctly", "tickets sitting unassigned", "how many tickets get reassigned", ticket ping-pong, or reviewing routing rules and queue design.

Use to push call recordings into Rulebase over the REST API when the phone system has no native connection, in reviewed batches with a dry-run plan, resume and audit log. Trigger for "upload calls to Rulebase", "import call recordings", "backfill our call history into Rulebase", "get XCally calls into Rulebase", "Rulebase isn't seeing our calls", or bulk-ingesting audio for QA evaluation.

Use to design or audit the support contribution to a customer health score, so the score predicts something instead of averaging weakly-related signals into a colour. Trigger for "build a customer health score", "add support signal to health scoring", "our health scores don't predict churn", red/amber/green account scoring, or a health score nobody trusts.

Use to sign off a QA period for audit or governance — stating what is being attested to, on what evidence, and with which limitations. Trigger for "sign off the QA period", "attest to our quality results", "monthly QA governance pack", "certify the quality figures", or being asked to confirm quality was assured for a period.

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.

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 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.

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 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 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.

Systematic Obsidian vault audit and normalization — structure, frontmatter, wikilinks, broken links, Git hygiene.

Bagman

Anti-AI-slop design skill for greenfield pages, audits, redesigns, and design extraction from URLs or screenshots. Use when the user asks to build a new app or landing page, wants to redesign something, invokes Hallmark by name, or uses audit/redesign/study.

VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check

Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detection-only mode that flags patterns without rewriting.

End-to-end statistical writing assistant for LaTeX - draft title/abstract/keywords, expand outlines into sections, audit manuscripts, write reviewer reports and response letters, and scaffold book manuscripts.

Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.

Hardens code against vulnerabilities by applying threat modeling, OWASP Top 10 prevention patterns, and secure coding practices for web applications.

Manage environment variables and secrets securely in Claude Code sessions, ensuring sensitive values are never exposed in logs, diffs, or context.

Design secure, scalable Firebase backends with Firestore, Auth, Functions, and Storage, following best practices for security rules, data modeling, and real-time listeners.

Discovers, classifies, protects, and governs API keys, tokens, secrets, and credentials across all providers with enterprise-grade security auditing and governance.

Verifies that fix commits properly address security audit findings without introducing new bugs or vulnerabilities.

Routes user requests to specialist skills for AEM 6.5 LTS Dispatcher configuration, troubleshooting, performance tuning, security hardening, and lifecycle orchestration.

Reviews local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist and attack surface mapping.

Conducts systematic security code reviews to identify exploitable vulnerabilities, reporting only high-confidence findings after researching the codebase.

Audit Django code for validated performance issues including N+1 queries, unbounded querysets, missing indexes, and write loops.

Creates CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers for any repository.

Enforces output quality, intellectual honesty, and continuous improvement across security analysis agents with anti-rationalization guards, self-critique loops, retry protocols, and quality gates.

Configure and manage GitHub secret scanning, push protection, custom patterns, and alert remediation.

Create agent user identities in Microsoft Entra ID to enable AI agents to act as digital workers with user capabilities in Microsoft 365.

Verify supply chain integrity for AI agent plugins, tools, and dependencies by generating SHA-256 manifests, detecting tampered files, auditing dependency pinning, and enforcing promotion gates.

Audit MCP server configurations for security issues including secrets exposure, shell injection, unpinned dependencies, and unapproved servers.

Finds the minimal Azure role that meets desired permissions and generates CLI commands or Bicep code to assign it.