Results for “audit”

Fetch a published article from a URL and extract its title, headings, body content, and metadata into a markdown file the update pipeline can audit.

Prevent XSS, secure auth flows, and harden React client-side applications. Use when preventing XSS, securing auth flows, or auditing third-party dependencies in React.

Audit, write, or revise renovate.json. Use when adding Renovate, troubleshooting unexpected (or missing) update PRs, hardening against supply-chain attacks, or evolving an existing config.

Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.

Audit or refresh MarketingClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Audit a StyleSeed-based component or page for WCAG 2.2 AA issues and apply practical accessibility fixes where the code makes them safe.

Designing, optimizing, and auditing repository structure: directory design, docs/ layout (PRD, specs, ADR), test/script organization, anti-pattern detection. Use for repo layout or migration planning.

Generating, updating, auditing, and sync-repairing project-specific Claude Code skills from the repo stack and conventions. Use when authoring project-local skills (Micro or Full).

End-to-end review of agent validation system for live trader readiness. Audits gating thresholds, model health wiring, live feedback loop, notebook consistency.

Builds auditable cost-reimbursement IGCEs using BLS wages, indirect cost pools, contract-type-specific fees, GSA CALC+ positioning, and GSA Per Diem travel data.

Builds auditable milestone-based Other Transaction cost analyses using BLS wages, GSA CALC+ positioning, GSA Per Diem, materials, cost sharing, and agreement-specific fees.

Federal acquisition compliance auditor for the active Theseus workspace, backed by live FAR/DFARS text via the vendored `ecfr` MCP. USE WHEN the user asks to audit FAR/DFARS clause coverage, validate that cited clauses actually exist in eCFR (catch fabricated or typo'd numbers), check whether a cited clause has been amended since the solicitation issued, validate regulatory references (NIST SP, DAFI, MIL-STD), check that every "shall" requirement has a deliverable, find missing compliance artifacts, audit proposal_instruction ↔ evaluation_factor coverage (UCF Section L↔M or non-UCF equivalent — FAR 16 task orders, FOPRs, BPA calls, OTAs), or "are we compliant with the proposal instructions?". Cross-references the workspace's clause / regulatory_reference / requirement / deliverable / compliance_artifact entities against live eCFR and flags gaps with severity. Format-agnostic. DO NOT USE FOR drafting compliant prose (use proposal-generator) or extracting clauses (Theseus pipeline does that automatically).

Erstellt Entwürfe für Industriekunden im Energierecht: prüft Sachverhalt, Normen und Beweise und liefert Anträge mit Begründung und Anlagenlogik.

Reviews UI code for compliance with Web Interface Guidelines, checking accessibility, design, and UX best practices.

Audits top-level documentation against recent git history to detect drift, applies minimal edits, and opens a pull request.

Performs security scanning, compliance checks, deployment planning, and infrastructure setup, with optional dependency auditing and bundle size analysis.

Markdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.

Cross-stack source code asset audit — classifies every file, detects embedded third-party libraries, and delivers actionable four-level verdicts per module with interactive HTML reports.

Cross-stack source code asset audit — classifies every file, detects embedded third-party libraries, and delivers actionable four-level verdicts per module with interactive HTML reports.

Markdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.

Safety guardrails for autonomous agents. Intercepts destructive actions and vets skills, requires structured approval before irreversible operations, with CLI-backed cryptographic audit trails and policy enforcement.

Use after the user has authorized GPT Pro help; manage a prompt-plus-sources workspace, route through ChatGPT Projects when available, and audit returned reasoning.

Markdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.

Markdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.

Builds auditable firm-fixed-price IGCEs using BLS wages, layered fringe, overhead, G&A and profit, GSA CALC+ positioning, and GSA Per Diem travel data.

| Use when reviewing an incoming GitHub pull request — runs the multi-level (L1-L5) audit against the PR's real diff range, posts findings as one batched review (inline, summary, or local-only), offers the standard fix chain on NEEDS_FIX, and optionally merges. The maintainer-side counterpart to /hyperflow:issue. Trigger with /hyperflow:pr, "review PR #N", "review this pull request <url>", "audit the PR", "check this contribution".

Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.

Systematic methodology for auditing the Hermes Skills Hub (and external sources) to identify gaps, overlaps, redundancies, and conflicts when building a skill library for any project. Covers browsing, targeted searching, cross-referencing with web/GitHub, comparing candidates against existing inventory, verifying install safety, and planning installation order. Use when starting a new project and assembling tools, or when evaluating whether to add external skills beyond what's currently installed.

Scaffolds fullstack projects (Next.js, FastAPI, MERN, Django) and analyzes code quality with security and complexity scoring.

Fork, sanitize, and package private projects for safe public release through a three-stage pipeline.

Discover, compare, audit, repair, adapt, craft, run, debrief, and publish repeatable AI-agent loops for engineering workflows.

Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization.

Audit GitHub Actions workflow efficiency and recommend fixes to reduce CI minutes and costs.

Find similar vulnerabilities and bugs across codebases using pattern-based analysis after identifying an initial issue.

Provides a structured approach to designing, implementing, and troubleshooting AWS security configurations with best practices and verification checklists.

Audit and redesign AI-generated feedback for pedagogical quality, timing, and learning impact. Use when building or reviewing automated feedback in digital learning tools.