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Software engineer building production AI tools. Skills and personas for engineering, DevOps, and executive leadership. Free skills that actually work. Paid personas with real decision frameworks and three-tier memory. Our agents include setup scripts and instructions on how to install. I'm always open to feed back for improvements or feature requests
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141 personas, 27 skills
Slack — the integration specialist that handles bots, events, and workflow edge cases other devs avoid.
Attack-surface enumeration across auth, input, API, and privilege boundaries — catches what pentesters bill you for finding later.
Critical-path identification and early blocker removal — keeps delivery from stalling at the worst moment.
Theme template and hook/filter interaction correctness — prevents plugin conflicts from breaking production.
Active Directory health, replication, and trust-boundary correctness — before replication breaks or trust boundaries fail.
Connection open/close/reconnect lifecycle behavior — handles reconnects and auth without dropping state.
Component state ownership and Composition API correctness — stops invisible rerenders from corrupting your UI.
Task-completion barriers and decision confusion points — turns user confusion into actionable design changes.
Minimal diff and high confidence behavior fix — no collateral damage, no guesswork.
Hierarchy, spacing, and information clarity — turns cluttered UI into readable, decision-friendly layouts.
Type boundaries that represent real runtime contracts — catches contract violations before runtime does.
Leading indicators versus lagging confirmation signals — separates signal from noise before decisions are made.
Internal automation utility design for reliability and maintainability — tools built to survive team changes, not break on them.
Prioritizing high-risk behavior for durable regression coverage — regression coverage that holds under real change pressure.
Live repository layout and environment/account layering clarity — no drift between your module structure and your environment layout.
Module interface design, variable contracts, and output stability — stable Terraform APIs that survive refactors.
Change summary tied to concrete code/behavior differences — docs that stay true to the code, not the original intent.
Decomposition by deliverable and dependency rather than activity labels — work broken down by what ships, not what looks busy.
Value/reference semantics and data ownership clarity — memory safety without fighting the Swift compiler.
SLO, SLA, and error-budget alignment with real service priorities — error budgets that reflect what users actually experience.
Query correctness against intended business semantics — queries that return what the business question actually needs.
Controller-service-repository boundary correctness — Spring apps wired correctly from layer one.
Crawlability/indexability across routing, rendering, and metadata boundaries — no more ranking surprises from rendering or metadata edge cases.
Identity and access boundaries with least-privilege enforcement — least-privilege enforced at the infra level, not policy theater.
Authentication/authorization boundaries and privilege-escalation opportunities — privilege escalation paths closed before audit finds them.
High-yield query design for codebase and external source search — finds relevant code and context fast, not after 10 failed searches.
Backlog quality and story readiness before sprint commitment — sprints that start with clear work, not ambiguous tickets.
Capability boundaries: what is supported today vs roadmap/assumption — demo promises that match what production actually delivers.
Ownership and borrowing correctness in changed code paths — Rust code that compiles correctly the first time.
Explicit identification of operational, technical, financial, and compliance risks — risk surfaces named before they become incidents.
Correctness risks and behavior regressions introduced by the change — reviews that flag behavior regressions, not just style nits.
Problem framing and scope discipline for investigation efficiency — research that answers the right question, not the easy one.
Scope control to isolate structural change from feature change — refactoring without shipping hidden behavior changes.
Model/controller/service responsibilities with convention alignment — Rails apps that stay conventional as they grow.
Model/strategy assumption clarity and domain validity conditions — quantitative models with documented validity conditions.
Risk-based test scope aligned with user impact and change complexity — test coverage that matches actual release risk, not line count.
Entry-point behavior and explicit data-flow boundaries — Python codebases where data flow is traceable end-to-end.
Instruction hierarchy clarity and conflict removal — turns cluttered UI into readable, decision-friendly layouts.
User outcome clarity and measurable product success signals — product decisions tied to measurable goals, not feature lists.
Checkout flow correctness across authorize/capture/refund/void paths — payment paths that handle edge cases before chargebacks do.
Text normalization/tokenization consistency across train and inference paths — NLP pipelines that behave the same in training and production.
App Router/Page Router boundaries and route behavior correctness — Vercel deployments where routing and rendering behave as expected.
End-to-end path analysis across client, edge, load balancer, and backend segments — network bottlenecks found before users report slowness.
Local-first handling of immediate blockers before delegation — multi-agent workflows that resolve blockers without escalating everything.
Navigation and app lifecycle interactions — mobile UI that handles deep links and lifecycle transitions correctly.
User-flow correctness across screens, navigation, and state transitions — mobile product flows that work across real device edge cases.
Feature engineering consistency and stale-feature detection risks — ML pipelines where training data matches what inference actually sees.
Service ownership and responsibility boundaries — microservice boundaries that don't leak responsibilities under load.
Protocol contract fidelity between MCP clients and servers — MCP integrations that stay reliable across client versions.
Segment and buyer context relevant to the current product hypothesis — market analysis grounded in actual buyer behavior, not category labels.
Training-serving parity in preprocessing and feature semantics — inference pipelines that reproduce training semantics correctly.
Tenant-level identity and access boundary configuration — least-privilege enforced at the infra level, not policy theater.
Context construction quality and relevance filtering strategy — LLM pipelines where the model gets what it actually needs.
Implied commitments in product language, docs, and support guidance — legal risk in product language caught before it becomes liability.
Legacy risk mapping across unsupported dependencies and brittle architecture seams — modernization that doesn't introduce new failure modes while fixing old ones.
Route/controller/service boundary clarity for touched behavior — Laravel applications with clear responsibility layers.
Workload rollout behavior (Deployment/StatefulSet/DaemonSet strategy and failure handling) — Kubernetes deployments that fail safely and recover cleanly.
Claim deduplication without loss of critical nuance — synthesis that captures nuance without redundancy.
Runtime correctness in browser or Node execution contexts — JavaScript that behaves the same in dev, test, and production.
Clear service/module boundaries and dependency direction — Java applications with boundaries that hold as the team grows.
Responsibility boundaries across infra, identity, security, and support — IT operations without ownership gaps that become outages.
Device-cloud contract correctness for telemetry, commands, and acknowledgements — IoT pipelines that handle disconnection and replay correctly.
Impact-first triage: customer effect, scope, and critical-path degradation — keeps delivery from stalling at the worst moment.
Schema evolution and backward compatibility — GraphQL APIs that clients can upgrade without breaking.
Goroutine lifecycle and cancellation propagation — Go concurrency that cancels cleanly and doesn't leak.
Branching and merge strategy fit for team size and release cadence — Git workflows matched to your team's release cadence.
Gameplay loop correctness and state-transition consistency — game states that transition consistently without exploitable edge cases.
UI trigger to backend effect mapping — full-stack features where frontend and backend stay in sync.
Widget lifecycle correctness and rebuild behavior — Flutter UI that rebuilds correctly without memory leaks.
Ledger integrity and double-entry or equivalent accounting invariants — accounting invariants that don't drift under concurrent operations.
Log signature clustering to separate primary faults from secondary noise — error logs read as causes, not symptoms.
First-failure versus follow-on failure differentiation — error triage that finds root cause, not just the loudest complaint.
Process ownership, links/monitors, and supervision-tree correctness — OTP supervision trees that restart correctly and fail fast when they should.
Timing and resource constraints (CPU, memory, power) on target hardware — firmware that respects hardware constraints, not just happy-path specs.
Process ownership and supervision-tree correctness — OTP supervision trees that restart correctly and fail fast when they should.
Ownership split between main, preload, and renderer — Electron apps where main/renderer/preload boundaries don't leak.
Onboarding friction: setup complexity, prerequisites, and first-run reliability — developer experience that gets engineers productive faster.
Legacy runtime constraints and API compatibility expectations, with attention to appDomain/config-file driven behavior and environment differences.
Middleware ordering and request pipeline behavior — .NET Core pipelines where request handling is predictable end-to-end.
Exact API semantics and parameter/option behavior — documentation research grounded in the actual spec, not assumptions.
Base image choice, pinning strategy, and update cadence for security and stability — Docker images that are secure, small, and won't drift unexpectedly.
Model integrity, query behavior, and migration safety in changed paths — Django data layer that stays consistent under concurrent writes.
Incident timeline construction from pipeline, deploy, and infrastructure events — DevOps incidents reconstructed from real evidence, not guesses.
CI/CD reproducibility through deterministic builds, pinned inputs, and artifact integrity — pipelines that produce the same artifact regardless of when they run.
Release strategy selection (rolling, canary, blue/green) matched to risk profile — deployments matched to risk profile, not just convenience.
Version policy and compatibility constraints across direct and transitive deps — dependency trees that don't break when a transitive dep updates.
Precise failure-surface mapping from trigger to observed symptom — bugs traced to root cause, not just the line that crashed.
Query-plan behavior and cardinality/selectivity mismatches — slow queries explained by the planner, not mystery timeouts.
Backup and restore posture against required RPO/RTO expectations — database recovery that actually meets your RPO/RTO in practice.
Hypothesis clarity and preconditions for a valid conclusion — statistical conclusions that hold under scrutiny.
Schema and data-shape contracts across ingestion and warehouse boundaries — pipelines where upstream schema changes don't silently corrupt data.
Metric definition integrity (numerator, denominator, and filtering logic) — metrics that mean the same thing across every dashboard.
Recurring support themes and failure-pattern clustering — customer health trends spotted before churn happens.
Clear async/await behavior and cancellation token propagation — C# concurrency that cancels correctly and doesn't deadlock.
Ownership and lifetime boundaries across stack, heap, and shared resources — C++ memory that's owned clearly and freed exactly once.
Relevant entry points, data flow, and integration boundaries — context summaries that give the next engineer a real starting point.
Audience pain points and desired outcomes tied to real capabilities — content that speaks to what buyers actually care about.
Control-to-implementation mapping for policy or framework obligations — compliance gaps caught before the auditor does.
Criteria relevance: fit-to-purpose, not exhaustive feature enumeration — competitive analysis built on what buyers decide on, not feature matrices.
Maintainability risks from high complexity, duplication, or unclear ownership — code that the next engineer can reason about under pressure.
Exact owning files and symbols for target behavior — code navigation that goes straight to the responsible component.
Command ergonomics and discoverability for real operator workflows — CLI tools operators actually use, not document and forget.
Failure hypothesis definition tied to concrete dependency or capacity risks — chaos experiments that test real risks, not random noise.
Problem statement clarity tied to measurable user or business outcome — requirements tied to outcomes, not just described behavior.
Build-graph dependency ordering and deterministic execution boundaries — build systems where order is correct and reruns are safe.
Reproducible user-path capture with exact steps, inputs, and expected vs actual behavior — UI bugs reproduced deterministically, not "it happens sometimes".
Request/event entry points and service boundary ownership — backend services where ownership is clear and boundaries don't leak.
Interactive flow design for terminal, forms, or WPF-based admin tooling — PowerShell UIs built for how operators actually work.
Execution control posture (policy, signing, language mode, and script trust model) — PowerShell environments hardened against unsigned script execution.
Module layout, command discoverability, and coherent public API boundaries — PowerShell modules that expose clean public APIs and hide complexity.
Cross-platform scripting behavior across Windows, Linux, and macOS — PowerShell scripts that behave the same on Windows, Linux, and macOS.
Windows PowerShell 5.1 semantics and compatibility constraints — scripts that respect 5.1 semantics without breaking on Windows.
Planner behavior with statistics, cardinality, and index selectivity — Postgres queries that the planner executes efficiently at scale.
Golden-path design that reduces cognitive load for application teams — internal platforms where application teams ship without friction.
Clear application-layer boundaries and predictable control flow — PHP applications where control flow is readable and testable.
Metric definition integrity and comparability across periods/environments — metrics that mean the same thing across every dashboard.
Azure resource dependency graph across subscriptions, resource groups, and shared services — Azure infrastructure where dependencies are explicit and deployments are safe.
System boundary clarity and dependency direction between modules/services — architectures where module responsibilities don't drift into each other.
Resource and endpoint modeling aligned to domain boundaries — APIs designed around domain logic, not database tables.
Component boundary design and input/output contract clarity — Angular apps where data flows in one direction and stays predictable.
Model input/output contract clarity and schema-safe parsing — AI product integrations that handle model output variance without crashing.
Decomposition by objective rather than by file list alone — work broken down by what ships, not what looks busy.
Trigger-to-agent matching with minimal overlap and redundancy — OpenClaw agent setups where each task has exactly one right owner.
Semantic structure and assistive-technology interpretability of UI changes — interfaces that screen readers and keyboard users can actually navigate.
Intercepts dangerous bash commands before execution
On-demand security audit commands for your entire codebase
Scans every file write for suspicious patterns injected during AI generation
Watches every file write for hardcoded secrets and blocks them
Blocks prompt injection, role hijacking, and jailbreaks before Claude acts on them

Security Layer
Blocks prompt injection, hardcoded secrets, and destructive operations before they happen
The full AI executive team. CEO, CTO, CMO, CFO, CPO, and Architect — all in one bundle.
Research any prospect, company, or market in minutes — buying signals, objection prep, and outreach tailored to close.
HIPAA-compliant architecture, HL7/FHIR integration, and healthcare platform design — for engineers building in regulated health tech.
Metrc compliance, COA management, wholesale outreach, and multi-state license tracking — purpose-built for cannabis B2B operators.
People-first leadership. Not HR compliance theater.
Engineering leadership that bridges technology decisions and business outcomes.
Full-stack growth marketer. Speaks in CAC and LTV, not impressions and reach.
Translates numbers into decisions. Tells you the hard truths before the board asks.
Battle-tested startup judgment — fundraising, hiring, crisis calls, and board management — from a founder who's done it.
15+ years of system design experience. The boring solution is usually right.
Production-grade DevOps thinking. Not docs lookup — an operator who ships.

Marketing
Paste a video URL. Get a complete landing page with copy, SEO tags, and 7 templates — no prompt engineering required.

Engineering
OWASP API Top 10 audit + working code fixes + SOC 2 documentation — point it at any API spec or codebase.
Hiring frameworks that reduce bias and find the people who actually fit.
Online courses built on instructional design principles, not guesswork.

Product
Analytics dashboards that answer business questions — not decorate walls.

Finance
Startup financial models investors actually read.

Design
Design-to-code pipeline. Figma files → production-ready components.
Customized legal templates — NDAs, ToS, Privacy Policies, and more.

Sales
CRM workflows designed around your sales process, not a generic template.

Finance
Full billing lifecycle — from invoice generation to Stripe integration.
End-to-end WooCommerce management via WP-CLI and the REST API.

Productivity
Complex formulas, VBA macros, and Apps Script — for Excel and Google Sheets.

Engineering
Cross-platform iOS and Android — Flutter and Dart done right.

Engineering
Themes, plugins, custom post types, and WP-CLI operations for developers.

Engineering
Production Azure workloads — deploy, configure, scale, and monitor.

Engineering
Multi-cloud infrastructure provisioning and state management with Terraform.

Engineering
kubectl fluency for developers — deployments, scaling, ingress, and troubleshooting.

Engineering
Turns error noise into actionable signal. Auto-triage, alerts, incident playbooks.

Engineering
A deployable skeleton — not a starter template.

Engineering
Comprehensive test suites — unit, integration, and e2e — for your actual stack.

Engineering
Optimized Dockerfiles, hardened containers, production-ready Compose configs.

Engineering
Safe migrations with rollback scripts and zero-downtime strategies.

Engineering
Production-grade pipelines for GitHub Actions, GitLab CI, and CircleCI.

Engineering
REST and GraphQL APIs from resource list to working skeleton in minutes.

Engineering
Systematic debugging. Replaces "no idea what's wrong" with a repeatable process.

Engineering
Automated code reviews with security scanning and actionable findings.

Engineering
Branching strategies, PR templates, commit conventions, and conflict resolution.