Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/sstraus/tuicommander/pigit clone --depth 1 https://github.com/sstraus/tuicommanderWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.01224 |
| Opus 5 | $0.00000 | $0.00612 |
| Sonnet 5 | $0.00000 | $0.00245 |
| Haiku 4.5 | $0.00000 | $0.00122 |
Grade A, and why
pi scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pi — UI layout and detection
Agent: pi (@earendil-works/pi-coding-agent).
Version audited: 0.83.0 · Date: 2026-08-02 · Theme: rose-pine-moon.
All values below were captured live from a real PTY session (raw ANSI), not inferred.
Identity & rendering
| Property | Value |
|---|---|
| Binary | pi (npm global; the executable on disk is the node interpreter) |
| Rendering engine | @earendil-works/pi-tui (own TUI lib — not Ink, not Bubble Tea) |
| Repaint style | Full-frame, wrapped in synchronized updates (\033[?2026h … \033[?2026l) |
| Screen clear | \033[2J\033[H\033[3J on startup repaint |
| Cursor positioning | Relative — \033[3A up / \033[3B down, then \033[1G, cursor hidden (\033[?25l) |
| Config dir | ~/.pi/agent/ |
| Sessions | ~/.pi/agent/sessions/<encoded-cwd>/<ISO-ts>_<uuid7>.jsonl |
Process identity gotcha. proc_pidpath() (macOS) and /proc/<pid>/comm (Linux) both return
the node interpreter for a pi session, not pi. Foreground-process classification therefore
falls back to argv[0] for known interpreters — see is_script_interpreter in pty.rs and
read_process_argv0 in process_env.rs. Without that fallback pi is invisible as an agent.
Bottom zone
Four rows, in this order, present in every state:
──────────────────────────────────────────── separator, RGB(196,167,231)
<composer> reverse-video cursor block + blanks
──────────────────────────────────────────── separator
~/Gits/personal/tuicommander (main) cwd + branch, RGB(110,106,134)
↑1.3k ↓1.8k R15k W6.0k CH88.5% $0.104 3.4%/272k (auto) (openai) gpt-5.6-sol • medium
- No prompt glyph. The composer is a bare reverse-video cell (
\033[7m \033[0m) followed by blanks.is_prompt_linematches nothing here — readiness cannot be prompt-based. - Status row is the reliable "this is a pi screen" marker: the context gauge
N%/Nkplus the•model separator. Seeis_pi_status_rowinpty.rs.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 96 lines · 0 tokens per session scan A 0a775c7b4640
pi is an agent published in the GitHub repository sstraus/tuicommander (125 stars, last pushed 5d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,224 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
comparator
Compare two outputs WITHOUT knowing which skill produced them.
fable5-apfel-engineer
Heavy-lifting Fable-5 engineer for the apfel project (Apple on-device FoundationModels CLI + OpenAI-compatible server + ApfelCore library). Use for any substantial apfel work — fixing GitHub issues, landing/reviewing fixes, Swift-6 concurrency, the OpenAI-compatible HTTP surface, context-window/token-budget logic, the…
collaboration
How coding agents (Claude Code, Codex, or any future harness) collaborate on this repo: who orchestrates, who implements, who reviews, and what each layer may touch. This is the map; the skills own the mechanics — never restate a skill's commands here or anywhere else (single owner per fact).
claude-code
Connect Claude Code to Remarc with the remarc plugin, and optionally let comments wake live sessions with remarc-hooks.
omp
Install Remarc's public OMP plugins, verify the MCP connection, and pair a session for instant comment delivery.
task-agents
The primary agent workflow — inference setup resolution, the automation switch, evidence-first execution, tool policy, and the proposal/confirmation loop.