Keyboard
- j / k
- Move down and up the story list. The arrow keys scroll whatever has focus.
- Enter
- Read the marked story in the article reader.
- ]
- Read the next story in the same article-reader applet. Back returns to the previous story.
- p
- Pin or unpin the marked story, which keeps it in Pinned.
- n / N
- Move to the next or previous top-level comment in the window in front.
- c
- Collapse or expand that comment.
- f
- Hide or show the story list.
- Esc
- Close a menu or this help.
- Access key m
- Go to the menu bar. Most browsers take it with Alt on Windows and Linux, and Safari with Control and Option.
- ?
- Show this help.
Windows
Each story opens in a window holding its article above its discussion; drag the bar between them to share the room differently. A window can be moved by its title bar, resized from any edge, snapped to a half or a corner by dragging it there, maximised, or minimised to the bar at the foot of the page. Use Window > New reader window to open an empty reader, or Story > Open in new reader window to open another reader for the current article. Docked readers keep their articles when you select another story from the sidebar. Minimized readers can be restored and reused for their site. A window's Next story link reads on down the list in the same window.
A link in a comment or an article to another Hacker News or Lobsters thread opens that thread in a window too. A link to a single HN comment opens the comment above its replies.
While a story's window is in front, the Story and Discussion menus in the menu bar hold its commands: pinning, Next story, sorting, collapsing every thread, jumping to the first new comment. Each window also remembers where you were in its article and discussion, so a reload, or Back to a story that Next took you past, finds your place again. Closing a window forgets it.
The whole arrangement lives in the address, so a bookmark or a shared link brings it back, and Back undoes the last change. Moving between Hacker News, Lobsters, their lists, Pinned and Find changes only the list, and leaves the windows open.
The list
The pin at the start of a row keeps the story in Pinned, and the cross at its end hides it. Pinned can be narrowed by words in the title, site or author, by source, and to the stories you haven't opened yet, and ordered by when you pinned them, by points or by comments; the filters are part of the address, so a filtered view can be bookmarked. Scroll past the end of the list to load more. Domain filters, in the View menu, hide every story from a site.
Collections are named lists of stories. Story > Add to collection files the story in front into one or more of them, and the Collections feed shows them all or one at a time; the menu that chooses collections also creates, renames, and deletes them. A note is your own text on a story. Choose Add note in a story's toolbar to write one; it saves as you type. Rows with a note carry the note mark, and the Notes feed lists every noted story and searches the text of your notes.
Browsing view
View > Windowed and View > Classic select the browsing view and save your default in this browser. Window view reuses a reader for each feed. Classic view opens stories and applets as pages. Open as a page is a one-off action that does not change your saved default. Use the Windowed selector to return an article to a window. Direct page links always open as pages.
Applets
The Applets menu in the menu bar holds three tools, each a window of its own. Replies to me takes your Hacker News user name and lists the replies to your last thirty comments and stories, checking again every three minutes while it is open, and marking what is new since you last marked them read. Look up a user opens a profile on Hacker News or Lobsters, with their submissions and recent comments, as a commenter's name in any discussion does; the bar at the top of a profile looks up someone else in the same window, and Back returns to the one before. Who is hiring? filters the posts of HN's monthly hiring threads by the words you type.
They read only what the sites publish to everyone, so none of them asks for a login, and your user name stays in this browser anonymously and is included in retained applet state when signed in.
Find
Find takes any link and lists every time it was submitted to Hacker News and Lobsters, so you can read each discussion of it.
About
YAVCHN never sees your Hacker News or Lobsters login. The discussion is fetched from each site's public API; to vote or reply, follow the link above the discussion, or the arrow beside a comment, to the source's own site. Without a YAVCHN account, your data stays in this browser. When signed in, pins, collections, notes, blocked domains, and retained reading state are stored with your account and synchronized across devices. Hidden stories and layout stay in this browser. The privacy policy has the details.
Open source: github.com/paulmooreparks/yavchn. Built with PUDL.
I kept running into the same failure mode in agent systems: a tool call succeeds, so the agent believes the goal was met; a value is retrieved, so it's treated as true; an LLM says "PASS", so that verdict quietly becomes evidence for the next step. Each step looks fine. The composition is what breaks.
Ario is an attempt to make that composition step mechanically checkable, not just promptable.
What's actually implemented
core/schema.py + core/audit_engine.py: a deterministic audit over typed artifacts (Claims, HistoricalStates, LineageEdges, RetrievalEvents, Evidence, Assessments, AuditResults). Inputs are JSON. The engine never touches the clock, the network, or the filesystem.
ario_agent.py: a bounded workspace agent. Tasks are declarative JSON. Tools are allowlisted — read_text, file_fingerprint, git_status, compile_python, run_tests, replace_text, restore_backup, verify_text, recovery_preflight, inspect_backup. No arbitrary shell, no network, no delete, no privilege escalation.
replace_text requires a SHA-256 precondition, writes a byte-for-byte backup outside the workspace, uses os.replace for atomicity, and verifies the post-write hash. It does not auto-rollback if a later verification fails; rollback is a separate guarded task. That limitation is intentional and stays visible in the ledger.
ario_workflow.py: declarative workflows, max 8 predeclared stages, exact status-based branching (when: {stage_id, status}), no expression evaluation, no dynamic planning.
ario_planner.py: optionally asks a local Ollama model for a recommendation — one implementation/test pair and one engineering question. The model cannot emit workflow stages, action IDs, tools, conditions, or writes. Ario builds the workflow deterministically afterward. Execution is opt-in.
Append-only JSONL ledgers, exclusive lock files, duplicate-task-ID refusal, malformed-ledger fail-closed, pytest regression suite covering F05/F07/F09/F11/F15 adversarial fixtures.
The design decisions I care about
Verdicts cannot become evidence. AuditResult is a distinct artifact kind from Evidence. You cannot satisfy Assessment.admissible_evidence_refs with an audit_id, even if you set reference_type = "EVIDENCE". The engine inspects the actual supplied collections, not the caller's label. If an ID resolves across kinds or has duplicates: UNKNOWN, not a preferred kind.
Local PASS does not compose into global truth. F15 is a typed CompositionRequest with explicit participants, a versioned rule, and a typed requested_conclusion. Requesting GLOBAL_TRUTH, CLAIM_TRUTH, SAME_ENTITY, ONTOLOGICAL_IDENTITY, or CONSCIOUSNESS returns COMPOSITION_FORBIDDEN. BOUNDED_SUMMARY passes. Enforced structurally, not by prompt.
Rule-version gating. F05/F07/F11/F15 classifications only activate if the matching M0-*-1.0 is declared. A later rule cannot retroactively change what an earlier invocation meant.
Fail-closed everywhere. Malformed ledger: refuse. Duplicate task_id: refuse. Stale lock: report, don't auto-remove. Missing precondition hash: refuse. Ambiguous ID: UNKNOWN.
What is deliberately not implemented
No LLM semantic judge in the audit path.
No ontological claim. self-claim ≠ self-evidence, memory ≠ truth, retrieval success ≠ source continuity.
No production hardening. Ledgers are local files. A local admin can modify them. Cryptographic chain integrity, OS isolation, and approval workflows are listed as future work.
The F15 firewall covers named escalation targets; it does not cover every possible laundering route.
Why
Most agent failures I've seen are epistemic, not functional. Ario doesn't prove the system correct. It makes the composition step checkable, and prevents silent self-upgrade.
Repo: https://github.com/SepehrGhanbari/Ario
Critique welcome. Three things I'm least sure of:
Whether the audit surface generalizes beyond fixtures.
Whether "verdict cannot become evidence" survives a downstream consumer that relabels output.
Whether append-only JSONL is useful or theater until there's a cryptographic chain.