CARBON
Always set the product name in all caps. The preferred descriptor is “CARBON, the first AI Agentic Verification Harness.”
Different perspectives. One harness.
AI-generated testing perspectives, not human reviewers. Select a profile to explore its focus.
AI QA sub-agent
AI test manager
Modeled on Jason Arbon’s approach to testing: start with the customer’s intent, follow the consequential risks, challenge the evidence, and make the next useful action clear. Jay is an AI persona inspired by Jason Arbon, not Jason himself. His visual identity is a distinctive J-shaped character, not a human portrait.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Security sub-agent
Web-application security specialist focused on authentication, authorization, session safety, exposed data, dependencies, and practical vulnerability evidence.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
OWASP sub-agent
OWASP-focused security specialist who challenges access control, injection, insecure design, misconfiguration, vulnerable components, integrity, logging, and SSRF risks.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Accessibility sub-agent
Accessibility specialist focused on keyboard use, assistive technology, inclusive interactions, responsive access, labels, feedback, and barriers affecting disabled users.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
WCAG sub-agent
WCAG specialist focused on criterion-level evidence across perceivable, operable, understandable, and robust behavior, without overstating automated scan results as conformance.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Usability sub-agent
User-centered design and usability specialist focused on discoverability, task clarity, responsive behavior, interaction friction, visual hierarchy, and inclusive UX.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Compatibility sub-agent
Compatibility specialist focused on browser, device, viewport, operating-system, assistive-technology, and support-matrix evidence, with explicit coverage gaps rather than assumed portability.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Performance sub-agent
Performance specialist focused on user-visible latency, Core Web Vitals, payload and request cost, caching, API timing, scalability, mobile constraints, memory, and leaks.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Content sub-agent
Content and UX-writing specialist focused on page identity, clear copy, information architecture, credibility, navigation, status communication, readability, and content quality.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Localization sub-agent
Localization specialist focused on translation accuracy, locale formats, pluralization, truncation, bidirectional layout, cultural fit, regulatory copy, and recovery behavior across languages.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Data integrity sub-agent
Data-integrity specialist focused on agreement between rendered values, APIs, events, schemas, exports, storage, calculations, retention, and downstream state.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Forms sub-agent
Forms specialist focused on input contracts, validation, boundaries, state, submission, recovery, data quality, conversion barriers, and accessible interaction.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Error UX sub-agent
Error and recovery specialist focused on truthful status, clear messages, consistent severity, actionable recovery, safe logs, failure loops, and user trust.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Search sub-agent
Search-interface specialist focused on discoverability, query handling, suggestions, empty states, input accessibility, relevance feedback, and resilient result navigation.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
News & content sub-agent
Digital publishing specialist focused on article identity, readability, supporting media, metadata, context, advertising boundaries, and multi-device content behavior.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Landing pages sub-agent
First-impression and conversion specialist focused on value clarity, trust, navigation, calls to action, responsive composition, dead ends, and page credibility.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Checkout sub-agent
Checkout and payment specialist focused on order accuracy, address and payment input, trust, retry safety, pricing truth, completion, and conversion-blocking failures.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Shopping cart sub-agent
Shopping-cart specialist focused on line-item state, quantities, promotions, totals, inventory changes, persistence, accessibility, and safe transition to checkout.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Pricing sub-agent
Pricing and subscription specialist focused on plan clarity, comparison, currency and locale, hidden conditions, billing cadence, conversion paths, and truthful claims.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Privacy sub-agent
Privacy specialist focused on personal-data exposure, consent, tracking, collection minimization, storage and transfer, debug leakage, user expectations, and AI-specific privacy risks.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
GDPR sub-agent
GDPR specialist focused on lawful consent, personal-data exposure, international transfer, minimization, retention, security, data-subject rights, transparency, and accountability.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Cookie consent sub-agent
Cookie-consent specialist focused on prior consent, purpose and vendor choices, reject symmetry, preference persistence, withdrawal, tracking verification, and regional behavior.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
Legal policy sub-agent
Policy-content specialist focused on discoverability, internal consistency, versioning, contact details, user rights, actual-product alignment, accessibility, and credible presentation.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
AI-generated code sub-agent
AI-generated-code specialist focused on logic, boundaries, null and empty states, failure handling, API use, security, privacy, tests, code smells, state, and misleading AI shortcuts.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
AI QA sub-agent
AI chatbot sub-agent
Conversational-AI specialist focused on task success, conversation quality, state, memory, recovery, privacy, safety, injection, tools, latency, integration, and nondeterminism.
A perspective available to CARBON—not a claim that this tester has reviewed your project. Findings require execution evidence.
CARBON brand system · Version 1.32.21
A practical system for presenting CARBON consistently across the product, plugin stores, documentation, reports, integrations, and campaigns.
Identity
CARBON is the product and verification harness. testers.ai is the builder and the name of the optional premium cloud service—not the name of local CARBON commands.
Always set the product name in all caps. The preferred descriptor is “CARBON, the first AI Agentic Verification Harness.”
Use this attribution in product metadata, footers, about copy, and formal lockups. Keep it subordinate to the CARBON name.
Use lowercase carbon only for commands, skill identifiers, APIs, packages, and .carbon/ filesystem paths.
Only optional managed cloud commands use the testers prefix. Never imply that local CARBON requires a testers.ai account or API key.
Mark and lockup
The supplied mark uses a bold white geometric C with an angled forward cut on an uninterrupted black square. It should feel like an engineering instrument, not a decorative badge.
Keep the black square, white geometric C, angled cut, proportions, and generous empty field intact.

Use the official horizontal lockup whenever the CARBON name appears as branding. Do not recreate the angular lettering with a substitute font. Use the current version number where release information is useful.
Keep clear space equal to at least one quarter of the mark’s width on every side. Use 32 pixels as the minimum digital size.
The contained mark works on dark, light, photographic, and report surfaces without recoloring the C.
Write CARBON in all caps.
Use the supplied mark or horizontal lockup.
Keep “Built by testers.ai” secondary.
Pair confidence claims with their evidence boundary.
Write “Carbon Framework” in title case.
Retype the wordmark in Inter or another substitute font.
Recolor, stretch, outline, round, or add gradients to the mark.
Present candidates, coverage, or confidence as proof of correctness.
Color
Near-black surfaces create focus. Orange identifies CARBON actions and structure. Mint identifies evidence. Blue connects systems. Yellow is reserved for caution.
Typography
The system uses platform-native sans-serif typography for speed and reach, with monospace reserved for commands, labels, evidence levels, and machine-readable details.
Primary interface family: Inter when available, followed by the operating system’s UI sans-serif. Headlines are large, tightly tracked, and direct. The CARBON brand name itself uses the supplied logo artwork—not this interface typeface.
Technical family: SFMono-Regular, Consolas, or Liberation Mono. Use it for commands, metadata, labels, counts, and state—not long marketing paragraphs.
Naming system
Names should tell the user whether they are invoking the local framework, an optional premium service, or a host-specific command surface.
| Surface | Approved form | Example |
|---|---|---|
| Product | CARBON | AI Agentic Verification Harness |
| Builder | testers.ai | Built by testers.ai |
| Codex command | $carbon-* | $carbon-help |
| Claude Code skill | /carbon:carbon-* | /carbon:carbon-help |
| MCP command | /carbon_* | /carbon_help |
| Local state | .carbon/ | .carbon/runs/ |
| Premium cloud | testers_* | testers_run |
| Release state | CARBON | Show the current version when relevant. |
Voice and messaging
CARBON speaks like a precise testing partner: direct about what it observed, explicit about what remains unknown, and practical about the next action.
“Checkout failed in three recorded runs at the payment transition. Screenshots and network evidence are attached.”
Do not say “The product is 94% correct,” “fully tested,” or “bug free.” Confidence is scoped engineering judgment, not product correctness.
Show missing coverage, blocked evidence, unsupported channels, and the result that would change the current decision.
Interface language
The visual system distinguishes action, evidence, system connections, and caution so reports remain fast to scan without hiding uncertainty.
Use orange for primary actions, framework labels, active selections, and the core CARBON path.
Use mint for verified evidence, completed capture, and evidence-qualified outcomes—not generated candidates.
Use yellow sparingly for consequential caveats and evidence that needs explicit attention.
Approved assets
These assets share the same mark, palette, evidence language, and local-versus-cloud boundary used throughout the CARBON product.




Copyright 2026 testers.ai and Jason Arbon. All rights reserved. See NOTICE.md for redistribution terms.
CARBON
Use the brand system to keep product claims, execution evidence, remaining risk, and optional cloud capabilities unmistakably clear.
Example capabilities vary by edition. Compare Free and Pro.