The graph that catches what code review misses.
A defect slipped through because the requirement was never written down, the test was never linked, and the architecture standard was never addressed. SysEdge makes all three visible — in a queryable graph, before the code ships. Measured on a real external open-source codebase you can reproduce: 71% fewer orientation tokens. Twelve parallel Claude sessions, one shared ontology, zero duplicate implementations.
Requirements quality — before tests, before code
Bad requirements produce bad code reliably. SysEdge ships a quality-review command that evaluates every user story and use case against a named set of research-backed standards — automatically, from graph queries, without an AI API key. The structural checks (13 QUS criteria, 6 traceability rules) run in seconds. The AI guidance layer (Cockburn UC patterns, semantic story quality) runs when you want it.
Structural checks (TRC-*, QUS-001–006) run free with no AI key. Add --ai to invoke the AI guidance layer: Cockburn UC completeness (UC-G-001–006) and semantic story quality (QUS-G-001–007). Requirements quality in depth →
Why not a memory tool, a code-graph, or AI code review?
Memory tools remember your chats. Code-graph tools index your source. AI code reviewers analyse the diff. All are useful — none can flag what was never written. They have no way to surface a requirement that was never specified, a test that was never registered, or an architecture standard that was never addressed — because there is no diff for the thing that was never built. SysEdge is the layer that models what your system is supposed to do and whether it's actually verified.
Full comparison: SysEdge vs memory tools, code graphs, and AI code review →
Reproducible verification — Formbricks (external open-source TypeScript)
One defect. Four things the graph caught that code review didn't.
We cloned Formbricks from GitHub and ran SysEdge against it cold — no prior knowledge of the codebase. The defect: DEF-FBK-001 — survey response export includes PII when anonymisation is enabled. The token saving (71%) is real, but it's the smallest part of the story.
Without SysEdge: 14,512 input+output tokens (30 input + 14,482 output), plus 1,797,494 cache-read tokens to orient on the codebase.
With SysEdge: 4,141 input+output tokens (22 input + 4,119 output), plus 473,649 cache-read tokens — graph queries replaced source reading.
71% fewer input+output tokens — ~73% on total tokens including cache reads (1,812,006 → 477,790).
But the graph also surfaced three deeper problems that explain why the defect existed in the first place:
1 — The requirement for anonymisation was never written down
Running coverage-review --uc UC-FBK-005 (Export responses to CSV) against the 7 AS-REQ dimensions returned 3 FAILs. The most direct cause of the defect:
Also flagged: AS-REQ-007 FAIL (0 linked tests — no traceability from spec to test) and 4 WARN findings on auth boundaries and testability.
Requirements traceability in depth →
2 — The export feature had zero tests at every V-model tier
test-gaps --instance surveys on the Formbricks graph:
No unit test. No API contract test. No Playwright UI flow. The export feature had shipped and been deployed with zero test coverage at any tier — invisible to coverage percentages because the feature was never registered in the test graph.
V-model test coverage in depth →
3 — The closest existing test had 7 of 7 AS-TEST dimensions failing
Pointing audit-test --uc UC-FBK-005 at the response.spec.ts Playwright file — the nearest test to the export feature — produced 7 FAILs across the AS-TEST-UC dimensions:
Additional FAILs: no end-to-end happy path, no equivalence partitions, no semantic correctness assertions, no specification derivation comments in any test.
AI test quality audit in depth →
4 — The architecture standard for PII export had no addressing decision
The graph contained SEC-PII-001: "When a survey has anonymisation enabled, all response export endpoints must strip PII fields before returning data." This standard existed — but had no ADR (Architecture Decision Record) confirming how the codebase addresses it. A single query surfaces this:
Three security standards. Zero decisions recorded. The defect was not a surprise — it was the predictable result of a specification gap, a test gap, and an architecture gap that all existed simultaneously and were all invisible without the graph.
SECOND VERIFICATION — DOCUMENSO (E-SIGNATURE PLATFORM)
We ran the same analysis on Documenso — an open-source DocuSign alternative. 15 minutes from cold clone to 5 findings. The Inngest job handlers that process envelope expiration have no tests. The expiration specification describes only the happy path. For a legally-binding e-signature platform, that's material.
Read the Documenso case study →Where SysEdge fits
SysEdge is often compared to two adjacent kinds of tool: AI memory/RAG tools that remember your chat sessions, and code-graph tools that index your source for navigation. Both are useful — and different. They map what your code or your chats contain. SysEdge maps what your system is supposed to do and whether it's verified, enforcing requirements traceability, test coverage, and architecture standards as the source of truth.
Pricing
Free CLI. One-time bootstrap kit.
The CLI gives you the full graph from the terminal. The bootstrap kit adds the web visualiser, AI audit commands, Docker setup, architecture standards library, and session skill files — everything to be productive in an afternoon.
| What you get | Free CLI | Bootstrap Kit · $149 |
|---|---|---|
| CORE | ||
| Briefing, worklog, test-gaps — session start in 30 seconds | ✓ | ✓ |
| Requirements traceability: US → UC → Feature → Test chain | ✓ | ✓ |
| Enhancements, defects, design proposals — with parallel-session coordination | ✓ | ✓ |
| V-model 4-tier coverage (component / integration / UC / e2e) | ✓ | ✓ |
| Code scan: Go, TypeScript, Python, Java, C# — symbols + tests auto-linked | ✓ | ✓ |
| Backup, per-instance restore, audit staleness tracking | ✓ | ✓ |
| MIT + Commons Clause licence | ✓ | ✓ |
| BOOTSTRAP KIT ONLY | ||
AI test quality audit — audit-test evaluates test files against 7 AS-TEST dimensions; coverage-review evaluates UC sets against 7 AS-REQ dimensions | — | ✓ |
| Architecture standards YAML — 53 standards across security, operations, development, infrastructure; ADR compliance tracking | — | ✓ |
| Web visualiser — drill-down graph, entity editor, coverage tiers, export panel | — | ✓ |
| Import skills — /import-stories, /import-use-cases, /import-requirements, /import-architecture | — | ✓ |
| Export commands — stories, use-cases, application-arch, technical-arch as structured Markdown | — | ✓ |
| /init-sysedge — auto-seed your project from directory scan | — | ✓ |
| Docker Compose + one-command setup | — | ✓ |
| All Claude Code skill files + session role templates | — | ✓ |
| 12 months of updates + email support | — | ✓ |
Per repository · one-time · instant download · VAT included
AT 10 SESSIONS/DAY · SONNET 4.6 · ORIENTATION TOKENS ONLY
Bootstrap kit pays back in 5 days at 10 sessions/day. Full measurement methodology →
Free CLI: MIT + Commons Clause — free for your own projects including commercial software.
Bootstrap kit: licensed per repository · 12 months updates · unlimited team members on that repo.
20+ parallel sessions or custom language support — contact us.
Full licence conditions → ·
Privacy policy →
The graph catches what the review missed.
SysEdge came out of running a 12-instance Claude Code system — twelve parallel sessions, one shared codebase. The findings from Formbricks and Documenso aren't unusual: unspecified exception paths, untested features, unaddressed standards, zero specification derivation in existing tests. They are the normal state of a codebase without a knowledge graph. With one, they become graph queries.
Verified on two production codebases, cloned cold from GitHub:
Documenso (e-signature) — 5 findings in 15 minutes → ·
Formbricks — 71% token reduction + 4 spec gaps →