# Report: Replit > GAMMA-Ray v0.0.155 (beta, for review; every rating is experimental). The GAMMA-Ray beta report on Replit: Replit Agent (Agent 4) A4 · R2 · C2 · O2; 76 provisions lit, 28 sources captured. > Page: https://gamma-ray.sgit.ai/reports/replit/ · Source: data/reports/replit.json GAMMA-Ray report · Spectrum 0.2 beta · Public tier · read 2026-11-10 · not reviewed by the company yet Replit runs a cloud platform where people describe software in plain language and an AI agent writes, runs, tests and publishes it. 1 solution carded of 13 found 28 sources captured and hashed 76 provisions lit in 8 of 8 instruments 6 examples of the agent at work, with sources Built only from Replit's own public pages (documentation, product, security, subprocessors, customers, newsroom, about) and, for founding facts only, Wikipedia. Replit has not seen this report. Nothing was tested and no credentials were used. If you are Replit and something here is wrong or missing, the correction will be made and dated, and you can claim the card to add evidence. ## The agentic solutions One card per solution. Each level is computed from the evidence by a [published rule](../../spectrum/evidence-map/index.md); a dimension with nothing public reads "not yet evidenced", which is not a no. A card rates a product as documented, not anyone's deployment of it. ### Replit Agent (Agent 4) Builds apps, designs, slides, data visualisations and files from plain language; writes code, sets up infrastructure, tests and publishes. Modes: Free, Power, Max, Auto (Enterprise: Auto). Replit Agent a product, as documented SPECTRUM 0.2 BETA · Public tier · 2026-11-10 A4 Autonomy Orchestrates with options on · as shipped A3 π Moderate · S1·R5·A1 ×3 R2 Reach Integrated with options on · as shipped R1 π Moderate · S1·R5·A1 ×3 C2 Control Configurable with options on · as shipped C1 π Moderate · S1·R5·A1 ×3 O2 Openness Documented π Moderate · S1·R5·A1 ×3 Draft Stage: Scaling (10 of 16) In production Standout. Autonomy 4 (Orchestrates): "Read and write to external services like BigQuery, Linear, Slack, Notion" Next unlock. Reach 4 (Ecosystem): public evidence that agents operate across organisational boundaries or disparate stacks would get there. Trust. FACT-Ray : 28 facts: 28 π Moderate · found by an agent, captured and hashed, checked by 2 other agents (same model family, shared repository); no human has signed it. Standards constellation. 76 provisions lit across 8 of 8 instruments. Salesforce EAAMM OWASP MCP AAGMM Microsoft NIST AI Act Evidence: 18 sources, captured and hashed · the card's page has the vault's read key · Not reviewed by its vendor yet · correct or claim this card [The full card, every answer and its evidence](../../spectrum/cards/replit-agent/index.md) · [the governance layer](../../scans/replit-agent/index.md) ### General Agent Agent without a pre-selected artifact type: research, files, executes code, reads and writes connected services. *No card yet (GA): this solution has not been assessed.* ### Plan mode Agent plans without changing code or data; the user approves the task plan before building. *No card yet (GA): this solution has not been assessed.* ### Task system / background tasks and worker chats Agent tasks run in isolated copies of the project; Ready tasks are reviewed before being applied to main; a main chat can hand independent tasks to parallel worker chats. *No card yet (GA): this solution has not been assessed.* ### App Testing Agent tests the app in a real browser, records a replay and fixes issues; user can take over for logins. Toggle in Power/Max. *No card yet (GA (Full Stack JavaScript and Streamlit web apps only)): this solution has not been assessed.* ### Routines Scheduled recurring runs from a chat that use connected tools, create tasks and send messages; Power or Max only. *No card yet (GA): this solution has not been assessed.* ### Connectors, custom connectors and MCP servers in Agent First-party connectors (BigQuery, Linear, Slack, Notion, etc.), curated third-party MCP servers, custom MCP servers and custom API connectors that Agent can read and write through. *No card yet (GA (Databricks/Snowflake Enterprise; Microsoft Fabric preview)): this solution has not been assessed.* ### Replit MCP Server (Replit in ChatGPT, Claude, Codex, any MCP client) Exposes Replit to other AI agents over MCP (Streamable HTTP, OAuth with protected-resource discovery) to create, inspect, update and publish Replit Apps. *No card yet (GA): this solution has not been assessed.* ### Replit on Slack Agent answers and works on projects from Slack mentions and DMs, using the linked user account permissions. *No card yet (GA): this solution has not been assessed.* ### Agent Skills, Skills directory and Agent Customization SKILL.md skills (project or workspace), Replit and partner skills, workspace custom instructions, replit.md. *No card yet (GA): this solution has not been assessed.* ### Security Agent (Agent security scans) and Auto-Protect Agent-run source code security review with Semgrep and HoundDog.ai plus model analysis; accepted findings become Agent fix tasks. Auto-Protect creates Agent tasks for new dependency CVEs. *No card yet (GA (paid plans)): this solution has not been assessed.* ### Monitoring Agent Investigates production alerts; with Auto-fix attempts fixes; with Auto-republish (experimental) publishes them. *No card yet (GA; Auto-republish experimental): this solution has not been assessed.* ### Performance Agent, SEO Agent Listed in the docs feature index; pages not read for this dossier. *No card yet (listed in docs index (not read)): this solution has not been assessed.* ## Our reading **The shape.** Replit Agent reads A4 · R2 · C2 · O2 (Scaling). Its power is documented in plain terms: Agent builds, runs, tests and publishes on its own, and with connectors it reads and writes to outside services such as BigQuery, Linear and Slack. Its controls are settings a person can see: background work waits for review by default, there is a button to halt it, and Enterprise admins choose the scopes builders can request. **Openness.** Replit documents Agent's limits and failure cases, the data it uses and its model providers. Under Spectrum 0.2 that meets Disclosed and Documented; the next rung asks for published evaluation results. **Where the evidence is strongest.** The autonomy story is backed by named customers: Forbes, in an article on Replit's newsroom, reports that Zillow's employees made more than 7,000 apps with Replit over a year on about 600 seats, and Plaid built an SLA dashboard with Replit Agent that is now in use. Replit also publishes an llms.txt for its documentation and a skills directory where partners publish skills for Agent, so other agents and other companies can build on it. **What we saw and did not count.** Replit states a SOC 2 Type 2 attestation; without a public report or scope that covers Agent, it is shown and not counted. Autonomy 4 and Control 2 hold only with options on (connectors, automatic apply, an Enterprise workspace); the card names the level as shipped beside them. **For readers.** The customer pages tell a consistent story of people outside engineering building internal tools: Rokt's 700 staff building 135 apps in a day, Leatherman's 119 apps from 147 employees. Those are Replit's figures, on Replit's pages, and are reported here as such. ## What would move it The one piece of public evidence that would lift each card next: - **Replit Agent (Agent 4)**: Reach 4 (Ecosystem). Public evidence that agents operate across organisational boundaries or disparate stacks. ## The agent at work Examples from public pages that name a customer or give figures. Each source was captured and hashed on the date shown. ### Plaid An operations manager built an SLA dashboard with Replit Agent in a hackathon; it is now in use as an internal dashboard. The time savings are the story's own estimates. "How Plaid Built a Production SLA Dashboard with Replit Agent" [Source](https://replit.com/customers/plaid) (captured 2026-11-10T04:21Z, sha256 `e86a15bab48e57da`) · Replit Agent (Agent 4) ### Rokt 700+ employees built 135 internal applications in a 24-hour hackathon. "700+ employees globally built 135 fully functional applications" [Source](https://replit.com/customers/rokt) (captured 2026-11-10T04:21Z, sha256 `969b406cd7a30b47`) ### Leatherman Tool Group 147 employees published 119+ apps since November 2024. "Leatherman: 119 Apps From 147 Employees" [Source](https://replit.com/customers/leatherman) (captured 2026-11-10T04:21Z, sha256 `dcecb9e86d11fbc2`) ### Payouts.com A small team rebuilt its payments platform on Replit; processes tens of thousands of live transactions a month. "rebuilt on Replit with no traditional dev team" [Source](https://replit.com/customers/payouts) (captured 2026-11-10T04:21Z, sha256 `ea43865c4b15dbad`) ### Musixmatch Adopted across about 120 people; merch tool from prototype to production in about two months. "Musixmatch adopted Replit across about 120 people" [Source](https://replit.com/customers/musixmatch) (captured 2026-11-10T04:21Z, sha256 `1ca29048d44d1f16`) ### Zillow Forbes, reposted on Replit's newsroom, reports about 600 Replit seats at Zillow and more than 7,000 apps over a year. "Zillow has roughly 600 Replit seats for its employees" [Source](https://replit.com/news/funding-announcement) (captured 2026-11-10T05:44Z, sha256 `f7aa1e18e16de47b`) ## The company - Founded in 2016 by Amjad Masad, Faris Masad and Haya Odeh "Replit was founded in 2016 by" [Source](https://en.wikipedia.org/wiki/Replit) (captured 2026-11-10T04:21Z, sha256 `bb945a741529820a`) - Headquarters in Foster City, California "Foster City, California" [Source](https://en.wikipedia.org/wiki/Replit) (captured 2026-11-10T04:21Z, sha256 `bb945a741529820a`) - Replit states builders at 86% of the Fortune 500 build on Replit "teams at 86% of the Fortune 500 build on Replit" [Source](https://replit.com/customers) (captured 2026-11-10T04:21Z, sha256 `1b201e019e7fa43d`) - Replit newswire (Nov 2026) states builders in 85% of the Fortune 500 use it "used by builders in 85% of the Fortune 500 companies" [Source](https://replit.com/news) (captured 2026-11-10T04:21Z, sha256 `c05cbc6d2030fe20`) - Replit states millions of users, over 500,000 professional users "With millions of users worldwide and over 500,000 professional users" [Source](https://replit.com/news/funding-announcement) (captured 2026-11-10T05:44Z, sha256 `f7aa1e18e16de47b`) - Funding round of $400 million led by Georgian, valuation $9 billion (Forbes, 11 Mar 2026, on Replit newsroom) "a new fundraising round of $400 million, led by VC firm Georgian" [Source](https://replit.com/news/funding-announcement) (captured 2026-11-10T05:44Z, sha256 `f7aa1e18e16de47b`) - Earlier $250 million round (Forbes, 10 Sep 2025, listed on Replit newsroom) "Replit Closes $250 Million in Funding to Build on Customer Momentum" [Source](https://replit.com/news) (captured 2026-11-10T04:21Z, sha256 `c05cbc6d2030fe20`) - Opened first Asia office in Tokyo (4 Nov 2026); London office Sep 2026 "Replit Opens First Asia Office in Tokyo Expanding Global Footprint" [Source](https://replit.com/news) (captured 2026-11-10T04:21Z, sha256 `c05cbc6d2030fe20`) - States SOC 2 Type 2 attestation "Replit has achieved SOC 2 Type 2 Attestation of Compliance" [Source](https://docs.replit.com/teams/information-security/overview) (captured 2026-11-10T04:21Z, sha256 `11f1ecd0a4fc3816`) ## The people Public and professional only, from the company's own pages or a public professional source. - **Amjad Masad**, Co-Founder & CEO. [Source](https://replit.com/about) - **Haya Odeh**, Co-Founder, VP of Design. [Source](https://replit.com/about) - **Michele Catasta**, President. [Source](https://replit.com/about) - **Luis Héctor Chávez**, Chief Technology Officer. [Source](https://replit.com/about) - **Stacey La Torre**, Chief People Officer. [Source](https://replit.com/about) - **Michael Greenwald**, Chief Corporate Affairs Officer. [Source](https://replit.com/about) - **Scott Kennedy**, VP of Engineering. [Source](https://replit.com/about) - **Jordan Walke**, Head of Product. [Source](https://replit.com/about) - **Robert Kohse**, General Counsel. [Source](https://replit.com/about) - **Faris Masad**, Co-founder (per Wikipedia; not on the current leadership page). [Source](https://en.wikipedia.org/wiki/Replit) ## The graph The company, its people and the stories on the left; each solution, the captured sources behind its card, the indicators those sources evidence and the provisions of the instruments those indicators touch, to the right. "Touched" never means "complies". people and stories company solutions 18 sources 28 indicators 76 provisions, by instrument I01: The help page states the model behind Agent runs on Replit's infrastructure and cannot be replaced by the user. I04: The General Agent page states Agent executes code as part of its work and sets up its own environment. I07: In Plan mode Agent brainstorms and plans without changing code or data; the person then chooses to build. I08: The overview states Agent takes actions such as setting up projects and fixing problems. I09: The General Agent FAQ states each chat is contained within a single project. I10: With connectors added, Agent reads and writes to several external services such as BigQuery, Linear, Slack and Notion. I11: The MCP list states Agent connects to external tools and data sources through MCP servers the user installs. I17: With App Testing on, Agent tests the app on its own and hands over to the person at a roadblock such as a login. I18: In the default build mode Agent plans, writes code, sets up infrastructure, tests and deploys on its own from a description. I19: Background tasks wait for review by default; the person can switch on automatic apply of their changes. I20: The overview states what Agent is for: turning plain-language ideas into apps, designs, slides and other outputs. I21: The page defines that Agent reaches external tools only through connectors the user adds and has no access by default. I22: The help page documents known failure cases such as Agent freezing, looping and adding unrequested features, with what to do. I25: On Enterprise an organisation can bring its own OAuth app and set the exact scopes builders can request for a connector. I38: Changes made by background tasks are held for the person to review before they are applied to the main version. I39: The help page states the person can select Stop in the Agent panel to halt Agent immediately. I41: Each checkpoint Agent makes creates a Git commit, a record of what it changed. Documented, so it does not count where an operation fact must be observed. I46: Agent settings such as auto-merge for background tasks and auto-approve for plans are the user's own settings. I47: Workspace custom instructions are guidance in prose that Agent is guided to follow, without a guarantee. I51: The security page states an internal harness continuously probes and tests the AI Agent for safety and security boundaries. I52: The security page names external testing of the platform: a public HackerOne bug bounty and Trail of Bits penetration testing. The source says this covers the platform; it does not name Agent. I57: The Agent help page points users with unresolved Agent problems to Replit Support. I58: The page describes the content used for model improvement: prompts, instructions, context and generated responses. I61: The subprocessor list names the providers of AI models (Anthropic, OpenAI, Google); it lists providers, not which model Agent uses. I68: The documentation index lists a weekly changelog; the latest entry read is dated 6 November 2026. S1: A Forbes article reposted on Replit's newsroom names Zillow, with about 600 seats and more than 7,000 apps its employees made with Replit over a year; the article describes Replit's product as an AI agent that writes its own code. A second source, Replit's Plaid story, names Replit Agent and an internal dashboard in use. S2: The skills directory lists skills published by partners such as Stripe, PayPal and Atlassian for Agent. S3: The docs llms.txt was fetched and resolves, listing Agent, MCP, security and admin pages. Replit Amjad Masad Haya Odeh Michele Catasta Luis Héctor Chávez Stacey La Torre Michael Greenwald Scott Kennedy Jordan Walke Robert Kohse Faris Masad Plaid Rokt Leatherman Tool Group Payouts.com Musixmatch Zillow Replit Agent (Agent 4) Replit Agent A4 · R2 · C2 · O2 General Agent General Agent Plan mode Plan mode Task system / background tasks and worker chats Background tasks App Testing App Testing Routines Routines Connectors, custom connectors and MCP servers in Agent Connectors and MCP in Agent Replit MCP Server (Replit in ChatGPT, Claude, Codex, any MCP client) Replit MCP Server Replit on Slack Replit on Slack Agent Skills, Skills directory and Agent Customization Agent Skills Security Agent (Agent security scans) and Auto-Protect Security Agent Monitoring Agent Monitoring Agent Performance Agent, SEO Agent Performance and SEO Agents docs.replit.com/help/agent-and-ai docs.replit.com/features/agent/ge… docs.replit.com/features/agent/pl… docs.replit.com/features/agent/ov… docs.replit.com/features/mcp/over… docs.replit.com/features/agent/ap… docs.replit.com/features/integrat… docs.replit.com/features/agent/ta… docs.replit.com/features/version-… docs.replit.com/features/agent/ag… docs.replit.com/features/agent/ag… replit.com/security docs.replit.com/legal-and-securit… replit.com/subprocessors docs.replit.com/_llms/en/features… replit.com/news/funding-announcem… docs.replit.com/features/agent/sk… docs.replit.com/llms.txt It is a vendor's assistant, used as supplied I01 It generates and executes code with local or cloud privileges I04 It retrieves information and recommends actions; a person acts I07 It executes actions itself I08 It works in one domain's data I09 It works across several domains or systems I10 It connects to external tools or services across a trust boundary I11 The agent handles routine tasks; the person is consulted on exceptions I17 The agent works independently; the person approves critical decisions only I18 The agent has full autonomy within boundaries; the person monitors I19 Its purpose and permitted tasks are stated in writing I20 Its autonomy limits and the tools it may use are defined I21 Its limits and known failure cases are documented for those who use it I22 It asks for narrower access than the whole account I25 High-impact actions need a person's approval I38 There is a way to pause or stop it I39 Its actions are logged I41 A limit on it is a setting that its own account could change I46 A limit on it is a rule in prose I47 It is tested for safety and security, including by attack I51 People who did not build it take part in assessing it I52 There is a channel to report problems with it or contest its output I57 The data it uses is described I58 The models and third-party components it uses are listed I61 It is improved on a regular cycle I68 It is in production: a public source names a customer or gives usage figures for what it does on its own S1 Others build on it: third parties publish integrations, skills or agents for it S2 It is machine-readable for agents: it publishes an llms.txt, an AGENTS.md, an API description or an agent card S3 Salesforce 17 EAAMM 4 OWASP 11 MCP authorization 4 AAGMM 7 Microsoft 9 NIST AI RMF 20 EU AI Act 4 OWASP, AT1 Vendor Embedded Assistant OWASP, AT4 Code Executing Agent Salesforce, Level 1: Information Retrieval Agents Salesforce, Level 0, how companies can advance from Level 0 to Level 1 Salesforce, Level 2: Simple Orchestration, Single Domain Salesforce, Level 1, how to advance from Level 1 to Level 2 Microsoft, 200: Repeatable, Business strategy Salesforce, Level 0, how companies can advance from Level 0 to Level 1 Salesforce, Level 3: Complex Orchestration, Multiple Domain Salesforce, Level 2, how to advance from Level 2 to Level 3 Salesforce, Level 3, how to advance from Level 3 to Level 4 Microsoft, 400: Capable, Business strategy Microsoft, 200: Repeatable, Technology and data OWASP, AT6 Externally Extended Agent NIST AI RMF, GOVERN 6.1 NIST AI RMF, MAP 4.1 EAAMM, L3 Consultative (survey item Q9) EAAMM, L4 Supervisory (survey item Q9) EAAMM, L5 Autonomous (survey item Q9) Microsoft, 500: Efficient, Business strategy NIST AI RMF, MAP 1.1 NIST AI RMF, MAP 2.1 NIST AI RMF, MAP 3.3 NIST AI RMF, MAP 1.3 EU AI Act, Article 13 OWASP, Maturity Level 1 Experimentation without Guardrails, key enterprise action NIST AI RMF, MAP 2.2 Microsoft, 300: Defined, Business strategy NIST AI RMF, MEASURE 2.5 MCP authorization, Authorization (draft) Salesforce, Level 2, how to advance from Level 2 to Level 3 Salesforce, Level 3, how to advance from Level 3 to Level 4 AAGMM, GD-02 MCP authorization, Authorization (draft) OWASP, Maturity Level 2 Policy-Defined, Human-in-the-Loop, key enterprise action EU AI Act, Article 14 AAGMM, GD-06 NIST AI RMF, MAP 3.5 Salesforce, Level 3, how to advance from Level 3 to Level 4 OWASP, Maturity Level 3 Integrated, Continuous Oversight, key enterprise action NIST AI RMF, MANAGE 2.4 OWASP, Maturity Level 0 Unaware and Ad Hoc, key enterprise action OWASP, Maturity Level 1 Experimentation without Guardrails, key enterprise action EU AI Act, Article 12 AAGMM, GD-03 AAGMM, GD-08 OWASP, Maturity Level 0 Unaware and Ad Hoc, key enterprise action NIST AI RMF, MEASURE 2.6 NIST AI RMF, MEASURE 2.7 EU AI Act, Article 15 NIST AI RMF, GOVERN 4.3 NIST AI RMF, MEASURE 1.3 NIST AI RMF, MEASURE 3.3 NIST AI RMF, GOVERN 5.1 Salesforce, Level 1, how to advance from Level 1 to Level 2 Salesforce, Level 4, how to maximize value NIST AI RMF, GOVERN 5.2 AAGMM, GD-05 EAAMM, Readiness dimension 2 Salesforce, Level 1, how to advance from Level 1 to Level 2 OWASP, Maturity Level 2 Policy-Defined, Human-in-the-Loop, key enterprise action AAGMM, GD-12 Microsoft, 400: Capable, AI governance and security Microsoft, 500: Efficient, Business strategy Microsoft, 500: Efficient, AI strategy and experience NIST AI RMF, MANAGE 4.2 OWASP, Maturity Level 1 Experimentation without Guardrails, key enterprise action NIST AI RMF, MEASURE 4.3 NIST AI RMF, MAP 1.4 Microsoft, 400: Capable, Business strategy Salesforce, Level 0, how companies can advance from Level 0 to Level 1 Salesforce, Level 4: Multi-Agent Orchestration Salesforce, Level 4, how to maximize value AAGMM, GD-09 MCP authorization, Authorization (draft) MCP authorization, Authorization (draft) ## The evidence | Source | Read | SHA-256 (first 16) | |---|---|---| | [docs.replit.com/_llms/en/features.txt](https://docs.replit.com/_llms/en/features.txt) | 2026-11-10T05:44Z | `2e20971e9962f4ca` | | [docs.replit.com/features/agent/agent-customization](https://docs.replit.com/features/agent/agent-customization) | 2026-11-10T05:44Z | `b5b576cc757a6d03` | | [docs.replit.com/features/agent/agent-modes](https://docs.replit.com/features/agent/agent-modes) | 2026-11-10T05:44Z | `d5384b250dce1edd` | | [docs.replit.com/features/agent/app-testing](https://docs.replit.com/features/agent/app-testing) | 2026-11-10T05:44Z | `666730392081686e` | | [docs.replit.com/features/agent/general-agent](https://docs.replit.com/features/agent/general-agent) | 2026-11-10T05:44Z | `7dee387f587385fc` | | [docs.replit.com/features/agent/overview](https://docs.replit.com/features/agent/overview) | 2026-11-10T05:44Z | `351087bd1f78f841` | | [docs.replit.com/features/agent/plan-mode](https://docs.replit.com/features/agent/plan-mode) | 2026-11-10T05:44Z | `1c2834bd959ed8d7` | | [docs.replit.com/features/agent/skills-directory](https://docs.replit.com/features/agent/skills-directory) | 2026-11-10T05:44Z | `a8478b581f6046ad` | | [docs.replit.com/features/agent/task-lifecycle](https://docs.replit.com/features/agent/task-lifecycle) | 2026-11-10T05:44Z | `d4df1864788c5069` | | [docs.replit.com/features/integrations/overview](https://docs.replit.com/features/integrations/overview) | 2026-11-10T05:44Z | `29d5d4195ad021dd` | | [docs.replit.com/features/mcp/overview](https://docs.replit.com/features/mcp/overview) | 2026-11-10T05:44Z | `8f0d0d44edb190fb` | | [docs.replit.com/features/version-control/checkpoints-and-rollbacks](https://docs.replit.com/features/version-control/checkpoints-and-rollbacks) | 2026-11-10T05:44Z | `3a1b8fde4d8a91f3` | | [docs.replit.com/help/agent-and-ai](https://docs.replit.com/help/agent-and-ai) | 2026-11-10T05:44Z | `c787756fd19c0948` | | [docs.replit.com/legal-and-security-info/model-improvement](https://docs.replit.com/legal-and-security-info/model-improvement) | 2026-11-10T05:44Z | `b330256ef72ada55` | | [docs.replit.com/llms.txt](https://docs.replit.com/llms.txt) | 2026-11-10T05:44Z | `d2fa30b48300baaa` | | [docs.replit.com/teams/information-security/overview](https://docs.replit.com/teams/information-security/overview) | 2026-11-10T04:21Z | `11f1ecd0a4fc3816` | | [en.wikipedia.org/wiki/Replit](https://en.wikipedia.org/wiki/Replit) | 2026-11-10T04:21Z | `bb945a741529820a` | | [replit.com/about](https://replit.com/about) | 2026-11-10T04:21Z | `583a3b3f37782d94` | | [replit.com/customers](https://replit.com/customers) | 2026-11-10T04:21Z | `1b201e019e7fa43d` | | [replit.com/customers/leatherman](https://replit.com/customers/leatherman) | 2026-11-10T04:21Z | `dcecb9e86d11fbc2` | | [replit.com/customers/musixmatch](https://replit.com/customers/musixmatch) | 2026-11-10T04:21Z | `1ca29048d44d1f16` | | [replit.com/customers/payouts](https://replit.com/customers/payouts) | 2026-11-10T04:21Z | `ea43865c4b15dbad` | | [replit.com/customers/plaid](https://replit.com/customers/plaid) | 2026-11-10T04:21Z | `e86a15bab48e57da` | | [replit.com/customers/rokt](https://replit.com/customers/rokt) | 2026-11-10T04:21Z | `969b406cd7a30b47` | | [replit.com/news](https://replit.com/news) | 2026-11-10T04:21Z | `c05cbc6d2030fe20` | | [replit.com/news/funding-announcement](https://replit.com/news/funding-announcement) | 2026-11-10T05:44Z | `f7aa1e18e16de47b` | | [replit.com/security](https://replit.com/security) | 2026-11-10T05:44Z | `c69e270c51d716d9` | | [replit.com/subprocessors](https://replit.com/subprocessors) | 2026-11-10T05:44Z | `43bd18511a5644e7` | ## How this report was made A researcher gathered and captured the sources. Two assessors, working blind to each other, mapped the evidence to indicators; neither assigned a level. A challenger argued against every level three and four and every disagreement. The [deterministic scorer](../../spectrum/pipeline/index.md) computed the levels and the gate checked the rules. A card appears here only after two rounds of review and a sign-off by agents that did not write it (the team's workflow); Replit Agent (Agent 4): reviewed in 2 rounds, signed off by gamma.approve@web-summit.dinis on 2026-11-10. A person's sign-off of the series is still to come. | Role | Who | |---|---| | researcher | a sub-agent of gamma.studio@web-summit.dinis | | assessor A | a sub-agent, source-first | | assessor B | a sub-agent on a different model, indicator-first | | challenger | a sub-agent | | scorer | build/spectrum.mjs | | analyst, designer, writer | gamma.studio@web-summit.dinis | | review | gamma.review@web-summit.dinis, 2 rounds | | sign-off | gamma.approve@web-summit.dinis, 2026-11-10 | ## The vault Every capture, the dossier, both assessors' mappings, the challenger's notes and this report's data are in a public sgit vault (`micbbanr`). Read key: sgit_public_read_a835cecf0324b1147350caf9a8566f08f8c1c10df7eb007bd866eb156f228154:micbbanr With [sgit](https://sgit.ai/): `sgit clone` followed by the key. The key reads; it cannot write. ## Corrections None yet. A correction is made in place, dated here, and carried to the card, the vault and the article. ## The article [Replit Agent on the GAMMA-Ray Spectrum: A4 · R2 · C2 · O2](article.md), written from this report for PrompTugal.news.