Curated lessons on getting started building agents with Copilot Studio
This report presents the forensic synthetic code analysis of microsoft/agent-academy, a JavaScript project with 2,985 GitHub stars. SynthScan v2.0 examined 45,753 lines of code across 191 source files, recording 59 pattern matches distributed across 9 syntactic categories. The overall adjusted score of 2.9 places this repository in the Likely human-written band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 59 distinct pattern matches across 9 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | WRITING_STYLE.md | 92 | > ### Why multi-agent systems matter | CODE |
| MEDIUM | docs/index.md | 72 | - **Interested in the foundations of AI agents?** [AI Agents for Beginners](https://microsoft.github.io/ai-agents-for-be | CODE |
| MEDIUM | docs/recruit/01-introduction-to-agents/index.md | 63 | ## Retrieval-Augmented Generation (RAG) | COMMENT |
| MEDIUM | docs/recruit/06-create-agent-from-conversation/index.md | 132 | ### 🌿 What is generative orchestration in the context of agents? {#what-is-generative-orchestration-in-the-context-of-ag | COMMENT |
| MEDIUM | docs/operative/03-multi-agent/index.md | 20 | # 🚨 Mission 03: Multi-Agent Systems {#mission-03-multi-agent-systems} | COMMENT |
| MEDIUM | docs/operative/03-multi-agent/index.md | 55 | ### Why multi-agent systems matter | COMMENT |
| MEDIUM | docs/operative/03-multi-agent/index.md | 128 | ## 🎯 Multi-agent architecture patterns {#multi-agent-architecture-patterns} | COMMENT |
| MEDIUM | docs/operative/03-multi-agent/index.md | 706 | ### 3.2.4 Test multi-agent collaboration | COMMENT |
| MEDIUM | …/recruit-v2-preview/01-introduction-to-agents/index.md | 74 | ## The Memory: Retrieval-Augmented Generation (RAG) | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/index.md | 20 | # 🚨 Mission 03: Multi-Agent Systems {#mission-03-multi-agent-systems} | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/index.md | 55 | ## 🧠 What are multi-agent systems? {#what-are-multi-agent-systems} | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/index.md | 61 | ### Why multi-agent systems matter | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/index.md | 133 | ## 🎯 Multi-agent architecture patterns {#multi-agent-architecture-patterns} | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/index.md | 556 | ### 3.2.4 Test multi-agent collaboration | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/evaluation.md | 1 | # Lab Rewrite Evaluation — operative/03-multi-agent | COMMENT |
| MEDIUM | docs/operative-v2-preview/03-multi-agent/evaluation.md | 218 | ### 3.2.4 Test multi-agent collaboration | COMMENT |
| MEDIUM | docs/special-ops/yaml-specialist/index.md | 510 | ## 🧪 Lab 4.1 - Add Knowledge Sources and Guardrails {#lab-4-1-add-knowledge-sources-and-guardrails} | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | docs/recruit/07-add-new-topic-with-trigger/index.md | 427 | #### Step 1: Trigger phrase | COMMENT |
| LOW⚡ | docs/recruit/07-add-new-topic-with-trigger/index.md | 433 | #### Step 2: Agent asks for details using an Adaptive card | COMMENT |
| LOW⚡ | docs/recruit/07-add-new-topic-with-trigger/index.md | 441 | #### Step 3: User provides dates | COMMENT |
| LOW⚡ | docs/recruit/07-add-new-topic-with-trigger/index.md | 445 | #### Step 4: Cloud flow executed | COMMENT |
| LOW⚡ | docs/recruit/07-add-new-topic-with-trigger/index.md | 449 | #### Step 5: Send a confirmation message to the user | COMMENT |
| LOW | docs/recruit/00-course-setup/index.md | 63 | ## Step 1: Get a Microsoft 365 Account | COMMENT |
| LOW | docs/recruit/00-course-setup/index.md | 76 | ## Step 2: Start a Copilot Studio Trial | COMMENT |
| LOW | docs/recruit/00-course-setup/index.md | 99 | ## Step 3: Create new developer environment | COMMENT |
| LOW | docs/recruit/00-course-setup/index.md | 122 | ## Step 4: Enable Ability to Publish with the Copilot Studio Trial | COMMENT |
| LOW | docs/recruit/00-course-setup/index.md | 190 | ## Step 5: Create new SharePoint site | COMMENT |
| LOW | docs/recruit-v2-preview/00-course-setup/index.md | 60 | ## Step 1: Get a Microsoft 365 Account | COMMENT |
| LOW | docs/recruit-v2-preview/00-course-setup/index.md | 73 | ## Step 2: Start a Copilot Studio Trial | COMMENT |
| LOW | docs/recruit-v2-preview/00-course-setup/index.md | 96 | ## Step 3: Create new developer environment | COMMENT |
| LOW | docs/recruit-v2-preview/00-course-setup/index.md | 119 | ## Step 4: Enable Ability to Publish with the Copilot Studio Trial | COMMENT |
| LOW | docs/recruit-v2-preview/00-course-setup/index.md | 187 | ## Step 5: Create new SharePoint site | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 452 | # Step 1: Use AI to detect country from timezone | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 460 | # Step 2: Show detected country to user | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 467 | # Step 3: Ask user to confirm or correct | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 476 | # Step 4: Use AI to interpret user's confirmation or correction | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 484 | # Step 5: Store confirmed country in global variable | COMMENT |
| LOW⚡ | docs/special-ops/yaml-specialist/index.md | 490 | # Step 6: Confirm to user | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | docs/operative/06-ai-safety/index.md | 107 | 1. **Clear identification**: Use labels like "AI-powered" or "Generated by AI" on responses | CODE |
| HIGH | docs/operative/06-ai-safety/index.md | 338 | 🤖 AI Safety Notice: My responses are generated by AI and include built-in | CODE |
| HIGH | docs/operative-v2-preview/06-ai-safety/index.md | 111 | 1. **Clear identification**: Use labels like "AI-powered" or "Generated by AI" on responses | CODE |
| HIGH | docs/operative-v2-preview/06-ai-safety/index.md | 360 | 🤖 AI Safety Notice: My responses are generated by AI and include built-in | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | docs/recruit/06-create-agent-from-conversation/index.md | 126 | ## 🔮 OK, I've created my agent... how do I next ground it with knowledge? {#ok-ive-created-my-agent-how-do-i-next-ground | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …uit/08-add-adaptive-card/assets/8.1_RequestDevice.json | 83 | "placeholder": "Please provide any specific requirements or comments", | CODE |
| LOW | …1-obtain-user-feedback/assets/11.3.1_CSATFeedback.json | 181 | "placeholder": "Placeholder text", | CODE |
| LOW | …1-obtain-user-feedback/assets/11.3.1_CSATFeedback.json | 271 | "placeholder": "Enter any additional comments you'd like to share", | CODE |
| LOW | …1-obtain-user-feedback/assets/11.3.1_CSATFeedback.json | 181 | "placeholder": "Placeholder text", | CODE |
| LOW | …1-obtain-user-feedback/assets/11.3.1_CSATFeedback.json | 271 | "placeholder": "Enter any additional comments you'd like to share", | CODE |
| LOW | .github/skills/agent-academy-report/SKILL.md | 53 | - **Name normalization**: If only an email address is available, it converts it to a display name — e.g. `john.doe@examp | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …skills/agent-academy-report/scripts/generate_charts.py | 282 | CODE | |
| LOW | …thub/skills/agent-academy-report/scripts/export_pdf.py | 91 | CODE | |
| LOW | …/skills/agent-academy-report/scripts/build_markdown.py | 49 | CODE | |
| LOW | …/skills/agent-academy-report/scripts/build_markdown.py | 503 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …skills/agent-academy-report/scripts/generate_charts.py | 21 | CODE | |
| LOW | …skills/agent-academy-report/scripts/generate_charts.py | 22 | CODE | |
| LOW | …thub/skills/agent-academy-report/scripts/export_pdf.py | 12 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | package-lock.json | 4454 | "resolved": "https://registry.npmjs.org/robust-predicates/-/robust-predicates-3.0.3.tgz", | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | …skills/agent-academy-report/scripts/generate_charts.py | 88 | def chart_completions_over_time(records, charts_dir): | CODE |
| LOW | …skills/agent-academy-report/scripts/generate_charts.py | 127 | def chart_sentiment_by_course(feedback, course_stats, charts_dir): | CODE |