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Using AgentFox? The user documentation (install, quickstart, guides, CLI and API reference,
self-hosting) lives on the website at useagentfox.com/docs, and its
source is in dashboard/app/docs/. This directory holds the material
behind the product: how it is built, why it is built that way, and how its numbers were measured.
docs/
├── getting-started.md a linear first hour, from install to your own agent governed
├── product-tour.md every integration surface, commands by task, self-hosting
├── status.md what is built, partial and absent (generated)
├── architecture/ how the system is put together
├── design/ what it must do, and how we know whether it does
├── evaluation/ how the numbers were measured, and how to read them
├── adr/ architecture decision records: what was decided, and what lost
├── deployment/ running it yourself, beyond the website's self-host page
└── assets/ images used by the top-level README
A linear first hour: install, initialise, scan a repo, run the demo, connect an agent over HTTP, read findings, turn enforcement on. Each step says what it proves.
Implementation status, generated by probing the codebase rather than written by hand (python scripts/gen/coverage.py --write). Says what is built, partial and absent.
Anyone deciding whether a capability actually exists yet.
Each place the policy binds (auto(), the gateway, LangGraph, the OpenAI Agents SDK, TypeScript, MCP, Claude Code hooks), the commands grouped by task, what the demo prints, and self-hosting.
Evaluators who want the whole product on one page.
The full HTTP API: authentication, the inline enforcement routes, and every control-plane route. Route tables are generated (python scripts/gen/api_routes.py).
The single canonical product requirements document: the argument, the product, the plan, and what has shipped since (including monitoring and live probing, §13). Long, and the source of truth for requirement IDs.
How deployed agents actually fail: 57 modes in 8 families plus 5 found by an independent audit, grounded in catalogued incidents, with what covers each.
Anyone building a risk case, and anyone checking ours.
A second coverage view, built from the architecture of an agentic request rather than from the failure-mode catalogue, so it is not circular. Generated by probe.
Anyone checking for gaps the authors did not think of.
Where each competitor sits in the stack and what it decides on, from their docs and code; our architectural primitives mapped to bound benchmark claims; pitch lines, objections, and the head-to-head runs still missing.
Founders and AEs preparing a technical pitch, and the sceptical buyer checking it.
Gaps found re-checking the HLD and LLD against the live code, what has been fixed since, and the settings a production deployment needs (secrets, cron, webhooks, Slack, the showcase flag).
Every wrapped open-source project: licence, health, verdict, our exposure, and why some well-known projects are deliberately off the critical path.
Contributors adding a dependency, and licence review.
The documents that began as PRD appendices keep their letters in their titles and section
numbers (Appendix A to E, §B.6 and so on), because other documents cite them that way.
The product capability by capability: what it does, how it was measured, every round including the ones that went badly, and how it differs from the market.
Evaluators, and anyone who wants the methodology rather than the headline.
The study behind the judgment tiers: where a hosted judgment beats our detectors and where it loses. Its headline numbers are bound in benchmarks/claims.yaml.
Evaluators who want the evidence, not the summary.
A working record, kept for provenance: research preceding a round of benchmarks, with candidate datasets, verified licences, and rejected candidates with reasons. Not maintained once that work was done.
The benchmark index: every harness, its dataset, its licence and how to re-run it.
Anyone reproducing a result.
Numbers quoted in these documents are bound to result files by
benchmarks/claims.yaml; python scripts/check/claims.py --check fails if
a quoted figure drifts from its source.
Rotate the token encryption key and the audit signing key: the _PREVIOUS settings, agentfox admin keys rotate, the automatic job and how to confirm nothing still needs the old key.
The Claude Code operator plugin: skills, commands, subagents, MCP server and safety hooks for driving the product from a coding agent. Its runtime-neutral parts are in plugins/shared/.
OpenAI's open-source multi-agent airline app run live through a local gateway with the OpenAI Agents SDK adapter: setup, configuration over the HTTP API, scripted scenarios and a check that asserts what was blocked, held and approved.