pi-continual-learning

Continual learning for Pi across the two surfaces that matter at runtime — model weights are explicitly out of scope:

• Harness — declarative tool-call guardrails. Layered JSON policies are evaluated on every tool call; matching calls are blocked (or gated behind user confirmation) with corrective guidance fed back to the model, so the system's tool-use behavior evolves without touching weights.
• Prompts — durable project memory: retrieval, injection, auto-memory guidance, and manual consolidation keep task-intent mapping and system guidance current across sessions.

Install

pi install npm:pi-continual-learning

Commands

Command	Purpose
/memory	Memory management menu: instructions, model, consolidation, settings
/consolidate	Consolidate now: memory first, then harness guardrails and project AGENTS.md mined from session history
/harness	Show active tool-call guardrails, or create a rule from a prompt (default: project personal .pi/harness.local.json, --shared for project repo, --global for user)

Guardrails configuration

Policies layer innermost-last; a policy name defined in several layers resolves to the innermost definition, and any layer can disable names. Every policy is validated against the runtime schema before it can become active; unknown fields are rejected with a diagnostic rather than silently ignored:

1. Built-in defaults ship with the package.
2. Pi agent directory harness.json (+ harness.local.json; defaults to ~/.pi/agent, honors PI_CODING_AGENT_DIR)
3. <project>/.pi/harness.json (+ harness.local.json)

Policy shape:

{
  "name": "ui-fixed-width",
  "tools": ["edit", "write"],
  // AND-gate: scope the policy to a class of calls first...
  "require": { "path": "path", "pattern": "\\.(tsx|css)$" },
  // ...then patterns inspect only text being written, never edit oldText
  "paths": ["content", "newText", "edits.newText"],
  "patterns": ["width:\\s*\\d{3,}px"],
  "action": "block",
  // The policy reason is fed back when a call is blocked or confirmed,
  // and appears in the display-only transcript event for observe:
  "reason": "Fixed pixel widths break responsiveness. Use design tokens or responsive units."
}

Only the declarative policy fields shown above are supported: name, tools, paths, pattern or patterns, optional require, action, and reason. Fields such as scope and rule are not aliases and are rejected. A matching policy can block, confirm, or observe: observe leaves the call untouched and records a display-only harness event with its reason. Policies do not run multi-step checks, probe services, or repair runtime state.

A generalized example — AI-generated UI widths violating layout rules — ships at examples/ui-width.harness.json: edits touching UI files that contain fixed pixel widths above the threshold are blocked with design guidance, while the same text in non-UI files passes through. Drop the file's contents into your project .pi/harness.json to activate it.

To create a rule directly, pass a natural-language request: /harness block edits that add hard-coded colors. By default, it targets the project personal layer at <project>/.pi/harness.local.json. Use --shared (or --project, --repo) to target the git-tracked <project>/.pi/harness.json, or --global (or --user) to target ~/.pi/agent/harness.local.json. The request is sent as a follow-up with an explicit write protocol: it reads that exact target file, creates it there when missing, preserves existing entries, and verifies the result without wandering to other layers.

Built-in defaults cover known-futile automation: interactive auth commands (npm/pnpm/yarn login|adduser|logout) and OTP-via-file/chat routing are blocked with guidance to hand those steps to the user's own terminal.

Harness consolidation

After a verified memory consolidation, /consolidate runs a second read-only planner against the same immutable session snapshot: it mines blocked tool calls, confirmation outcomes, and user corrections, then proposes bounded policy/skill-prompt changes citing that evidence. The parent alone applies them — atomically, and only to the personal project-local layer (.pi/harness.local.json). Shared layers are never written; a failed or rejected harness plan never touches applied memory results; no-context runs skip the phase entirely.

AGENTS.md consolidation

The third pipeline phase treats the repository-root AGENTS.md like trained weights. Against the same snapshot, a read-only planner proposes at most five evidence-cited edits — rewrite, remove, add, or extract addressable units. The parent enforces the discipline in code before anything is applied:

• Every cited quote must appear verbatim in the snapshot text; unverifiable quotes are discarded mechanically, and an operation left without evidence never reaches the automatic application step.
• A brand-new unit needs batched evidence (at least two cited occurrences in the current session).
• The post-edit document must fit the byte budget (default 16 KB ≈ 4k English tokens by the bytes/4 heuristic — deliberately tighter than backpass's ~20 KB default and Claude Code's 25 KB MEMORY.md load cap; lower it further for primarily Chinese files, where UTF-8 packs fewer tokens per byte); once the file sits at or above budget, updates are zero-sum — removals pay for additions.
• Narrow instructions are extracted instead of kept: trigger-scoped guidance becomes a harness skill prompt; durable detail becomes a memory file.

After the mechanical gates pass, every surviving operation is applied autonomously in one atomic write (with a pre-apply digest for mid-apply shutdown recovery). User-level instruction files are never touched, and the child planner remains read-only. Configure via the per-project settings file:

{ "autoMemory": true, "agentsMd": { "budgetBytes": 16384 } }

"disabled": true inside agentsMd turns the phase off. A failed AGENTS.md phase never touches applied memory or harness results.

Skill prompt guidance

skillPrompts adds corrective guidance when Pi expands a configured /skill:<name> invocation. The same four layers apply (user, user-local, project, project-local), with the innermost definition winning by skill name. disabled only affects tool-call policies, not skill prompts:

{
  "skillPrompts": {
    "using-open-artifacts": {
      "prompt": "Use coda0.com as the default instance unless the user specifies another host.",
      "target": "system"
    },
    "impeccable": {
      "prompt": "For Live on macOS, use open <served app URL>, never helper serverPort or agent-browser; then keep one foreground live-poll.mjs active.",
      "target": "system",
      "userMessagePattern": "^live$"
    }
  }
}

target: "system" appends the prompt to the current system prompt. The target: "user" form delivers a hidden custom context message because Pi's before_agent_start hook cannot rewrite the already-expanded user message; both targets are matched only against Pi's complete expanded skill XML, not a raw /skill: command or arbitrary XML-looking text. An optional userMessagePattern narrows a prompt to the expanded block's user-message suffix (for example ^live$); it is a regular expression and invalid patterns are skipped with a configuration diagnostic. Guidance is appended idempotently when a hook is evaluated more than once.

Memory

See AGENTS.md and procedures/consolidate.md for the memory loading rules, privacy constraints, and the parent-owned consolidation protocol. State lives in harness memory directories; only safe files sync to public .memory/.