Dotagents

How I configure and extend Pi, my coding agent harness.

Dotagents is my personal setup for Pi. It lives in a single repository that symlinks into ~/.pi/agent/ and combines a shared operating contract, model defaults, and a small set of extensions, skills, and prompts.

Nothing here is a framework. Each piece solves a concrete friction point from daily work—keeping long tasks honest, isolating noisy loops, reviewing diffs before commit, or shaping a problem before writing code.

View repository · Core harness · Extensions · Skills · Prompts

Core harness

Before any extension or skill runs, two files set the baseline: AGENTS.md defines how agents behave across my repositories, and pi-settings.json configures models, context compaction, and loaded packages.

Operating rules (AGENTS.md)

  • Jujutsu (jj) for version control — check status before starting, keep each logical task in its own atomic change, and never mix unrelated edits.
  • beads_rust (br) in .beads/ for local-first issue tracking, explicit dependency graphs, and session handoffs.
  • Mandatory quality gates (make format, make check, make test) before any task is marked complete.
  • Build only what is requested: no speculative abstractions, no unrequested backwards-compatibility shims, and modular boundaries with thin interfaces.

Runtime and model defaults (pi-settings.json)

Default model
openai/gpt-6.1-sol at medium thinking with +codemode enabled, dark theme, and automatic context compaction (16,384 reserve tokens, 12,000 recent tokens kept).
Model roster
Local MLX inference (Qwen3.8-27B-4bit on 127.0.0.1:8080) alongside OpenAI (gpt-6.1-sol, gpt-6-astra, gpt-6-luna), Anthropic (claude-opus-5-5, claude-sonnet-5-5), DeepSeek (deepseek-flash), Moonshot (kimi-k3), and Z.AI (glm-5.3).
Package loading
Extensions and packaged skills load declaratively from the packages list in pi-settings.json (via GitHub or npm), alongside local skills/ and prompts/ directories symlinked into ~/.pi/agent/.

How this setup works

Extensions
Change what the Pi harness can do through lifecycle hooks, tools, slash commands, or terminal UI widgets.
Skills
Give the model reusable domain workflows, checklists, and helper scripts that load on demand when a task matches.
Prompts
Give the human a named slash command for a repeatable multi-step workflow.

Extensions (6)

  • Pi Progress Bar

    Extension

    Passive task board and footer widget that tracks what the agent actually finished, grounded in tool evidence and Jev verification.

    By Vedang Manerikar · git:github.com/vedang/pi-progress-bar

    Read guide · View source

  • Pi Review

    Extension

    Structured code review workflow that branches into a dedicated review session, separates agent-fixable bugs from human callouts, and returns cleanly.

    By Earendil · git:github.com/earendil-works/pi-review

    Read guide · View source

  • Pi Boomerang

    Extension

    Runs an autonomous task or template chain and collapses the raw intermediate turns into a compact summary on the session tree.

    By Nico Bailon · git:github.com/nicobailon/pi-boomerang

    Read guide · View source

  • Pi Interactive Shell

    Extension

    Full PTY and xterm emulation inside Pi for running interactive CLIs, dev servers, and background Pi sessions.

    By Nico Bailon · npm:pi-interactive-shell

    Read guide · View source

  • Pi Intercom

    Extension

    Local Unix-socket messaging between running Pi sessions for multi-session coordination, blocking ask/reply calls, and wakeups.

    By Nico Bailon · npm:pi-intercom

    Read guide · View source

  • Pi Exa

    Extension

    Web search and URL content extraction via Exa, giving the agent source-backed discovery and bounded page reads.

    By Vedang Manerikar · git:github.com/vedang/pi-exa

    Read guide · View source

Skills (6)

  • Shaping Skills

    Skill

    Ryan Singer's Shape Up workflow packaged for Pi: framing problems, comparing solution shapes, breadboarding affordances, and writing kickoff docs.

    By Ryan Singer · Packaged for Pi by Vedang Manerikar · git:github.com/vedang/shaping-skills

    Read guide · View source

  • Modularity Skills

    Skill

    Architecture design, coupling review, and documentation skills grounded in Vlad Khononov's Balanced Coupling model.

    By Vlad Khononov · Packaged for Pi by Vedang Manerikar · git:github.com/vedang/modularity

    Read guide · View source

  • ADR

    Skill

    Workflow and Bun CLI for drafting, superseding, linking, and validating Architecture Decision Records.

    By Vedang Manerikar · git:github.com/vedang/pi-adr

    Read guide · View source

  • Chrome CDP

    Skill

    Attaches to an already-open local Chrome tab over the Chrome DevTools Protocol to inspect accessibility trees, screenshots, or live DOM state.

    By Petr Baudis · Forked by Vedang Manerikar · git:github.com/vedang/chrome-cdp-skill

    Read guide · View source

  • Test Audit

    Skill

    Gates new tests with four boundary questions and prunes mock-heavy, duplicate, or implementation-coupled tests from existing suites.

    Adapted from OpenClaw · Maintained in Dotagents · skills/test-audit/SKILL.md

    Read guide · View source

  • Tufte Visualization

    Skill

    Applies Edward Tufte's principles—high data-ink ratio, zero chartjunk, direct labeling, and small multiples—to charts and dashboards.

    By Vedang Manerikar · skills/tufte-viz/SKILL.md

    Read guide · View source

Prompts (3)

  • Sharpen Communication

    Prompt

    Clarifies audience, goal, and tone, then rewrites rough drafts using BLUF (Bottom Line Up Front) and MECE structure.

    By Vedang Manerikar · prompts/sharpen-communication.md

    Read guide · View source

  • Orchestration Watchdog

    Prompt

    Spawns a read-only background Pi ticker that wakes the coordinator session every N minutes to check worker sessions, jj status, and commit gates.

    By Vedang Manerikar · prompts/orchestration-watchdog.md

    Read guide · View source

Using this setup

Everything on this page lives in vedang/dotagents or in the standalone repositories linked from each card. Take individual extensions, skills, or prompts that solve a problem you actually have—this is a personal working rig, not a framework to install wholesale.