Roadmap

This roadmap is a working plan, not a release contract. It describes the direction of sivtr in outcome terms so the project can stay useful as a small terminal tool while growing into a unified agent memory workspace for humans and agents.

Roadmap map

Reliable CLI
  -> Multi-agent workspace
    -> Skills and playbooks
      -> High-signal TUI
        -> Remote collaboration
          -> sivtr-me

Track	Status	Target outcome
CLI foundation	In progress	A daily command-line utility for capturing, searching, selecting, and exporting terminal and agent work.
Agent support	In progress	Provider-neutral parsing and browsing for AI-agent conversation records.
Skills and playbooks	In progress	Reusable agent procedures that use sivtr as the unified memory entry point.
TUI workspace	Planned	A dense keyboard-first interface for many sessions, many providers, and long conversations.
Remote collaboration	Later	Permissioned access to teammate or remote agent chat records for collaborative memory workflows.
sivtr-me	Later	An evidence-backed personal AI-era profile built from real work records.

CLI foundation

The near-term priority is to make the command-line surface complete, predictable, and scriptable. sivtr should be trustworthy as a daily utility before it becomes a broader personal data layer.

• Capture command output from pipe mode.
• Capture subprocess output with sivtr run.
• Import shell session logs.
• Copy recent command input, output, and command blocks by selector.
• Search saved output history with SQLite.
• Provide TOML configuration for core behavior.
• Tighten command naming and option consistency across copy, history, codex, hotkey, and workspace flows.
• Make selectors and filters easier to compose in shell scripts.
• Expand search beyond basic matching toward explicit scopes, literal/keyword/fuzzy/semantic methods, source filters, ranking, and context-rich machine-readable results.
• Strengthen import, export, and search behavior for larger local archives.
• Keep configuration explicit, portable, and safe to share.

Agent support

Agent sessions are a first-class memory source. The product goal is for agent transcripts to behave like normal sivtr sources rather than special-case features.

• Parse Codex session records.
• Parse Claude-style session records.
• Copy the latest user, assistant, tool, turn, or full session block.
• Browse local and mirrored session directories through picker workflows.
• Support more agent providers behind the shared session-provider interface.
• Keep provider-specific parsing isolated from shared selection, search, and export logic.
• Make session discovery robust across local, mirrored, and shared transcript directories.
• Expose provider selection consistently in CLI commands, hotkeys, and the TUI workspace.
• Avoid binding the data model to one vendor’s transcript format.

Skills and playbooks

Skills make sivtr usable by agents as a shared memory entry point. They turn generic memory commands into reusable procedures such as “fix the latest terminal error,” “continue from the last task,” or “write a timeline of recent work.”

• Add an initial skills/sivtr-memory/ package with command recipes, evidence discipline, workflows, and examples.
• Document why skills are part of the product model rather than just optional prompt snippets.
• Define a stable packaging convention for community skills and local team playbooks.
• Build a skill registry so users can discover workflows such as terminal-failure debugging, timeline generation, PR handoff, recap, and onboarding.
• Add examples that show agents using refs and validation evidence from workspace memory.
• Keep skill procedures grounded in existing CLI commands; do not let community playbooks imply unavailable sivtr features.

TUI workspace

The TUI should remain fast and keyboard-first, but it needs to scale from single-output browsing to multi-source workspace navigation.

• Browse captured output in a Vim-style terminal UI.
• Search within captured output.
• Select character, line, and block ranges.
• Pick sessions and dialogue blocks interactively.
• Refine the workspace picker for many sessions, providers, and long conversations.
• Improve search scope, result navigation, and visual feedback.
• Make selection behavior consistent across terminal output, command blocks, and AI dialogue blocks.
• Improve rendering for markdown, tool calls, and structured agent content.
• Keep the interface dense, predictable, and editor-friendly.

Remote collaboration

Remote collaboration extends the local memory model to permissioned teammate or remote agent records. The goal is not to become a hosted transcript service by default; it is to let explicit collaborators connect relevant chat/session records so agents can coordinate across people and machines.

• Support remote or teammate memory sources behind explicit opt-in configuration.
• Preserve source refs and provenance across remote records.
• Provide selective disclosure controls so sensitive local memory is not shared accidentally.
• Let agents answer questions such as “what did the other agent already try?” or “show the remote validation output before I continue.”
• Keep local-first behavior as the default even when remote sources are available.

sivtr-me

After the CLI and workspace foundations are stable, the larger direction is sivtr-me: a personal profile generated from accumulated work records. Unlike a static resume, it should be evidence-backed and continuously updated from real terminal sessions, AI conversations, project history, and selected artifacts.

• Define the local data model for long-lived personal work records.
• Summarize projects, tools, domains, and working style from real records.
• Surface representative conversations, decisions, code changes, debugging traces, and shipped outcomes.
• Build a public or private profile that can answer “what has this person actually worked on?”
• Support selective disclosure so sensitive records stay local while high-signal summaries can be shared.
• Preserve provenance from every displayed claim back to underlying sessions or artifacts.

Non-goals

The roadmap does not imply that sivtr will become:

• a terminal emulator;
• a hosted transcript storage service by default;
• an unrestricted remote chat mirror without explicit permission;
• a vendor-specific wrapper for one AI assistant;
• a replacement for source control, issue trackers, or note-taking tools.

sivtr should stay small at the edge and structured at the core.

Principles

• Capture first. Important work should be recorded when it happens, not reconstructed later from memory.
• Local by default. Personal transcripts and terminal history should remain under user control unless explicitly exported.
• Provider-neutral. Agent support should be implemented through replaceable providers and stable shared abstractions.
• Skills are interfaces. A skill is how an agent learns to operate the shared memory layer; it should be precise, testable, and evidence-seeking.
• Composable CLI. Every interactive feature should have a scriptable path where practical.
• Provenance matters. Summaries, profiles, and exports should be traceable back to source sessions and command output.
• Editor-friendly. sivtr should hand off to existing editors and workflows instead of trying to own the whole developer environment.