pi-cc-compact

Ports Claude Code's compaction prompt (9-section <analysis>+<summary>) to pi's session_before_compact hook. Faithful reconstruction of the leaked full-compact prompt.

Packages

Package details

extensionskill

Install pi-cc-compact from npm and Pi will load the resources declared by the package manifest.

$ pi install npm:pi-cc-compact
Package
pi-cc-compact
Version
0.1.0
Published
Jun 30, 2026
Downloads
165/mo · 20/wk
Author
npmc_5
License
MIT
Types
extension, skill
Size
20.7 KB
Dependencies
0 dependencies · 2 peers
Pi manifest JSON
{
  "extensions": [
    "./extensions"
  ],
  "skills": [
    "./skills"
  ]
}

Security note

Pi packages can execute code and influence agent behavior. Review the source before installing third-party packages.

README

pi-cc-compact

Claude Code's compaction prompt, ported to pi.

pi-cc-compact is a pi extension that replaces pi's default context-compaction summary with the exact 9-section <analysis> + <summary> prompt Anthropic ships inside Claude Code.

The prompt was reconstructed from the leaked/deobfuscated compact_service prompt observed in @anthropic-ai/claude-code v2.1.68. Every part that matters is reproduced faithfully:

  • System prompt: "You are a helpful AI assistant tasked with summarizing conversations."
  • No-tools preamble (CRITICAL: Respond with TEXT ONLY...)
  • <analysis> scratchpad instruction (chronological reasoning)
  • 9 required sections: Primary Request & Intent · Key Technical Concepts · Files and Code Sections · Errors and Fixes · Problem Solving · All User Messages · Pending Tasks · Current Work · Optional Next Step
  • Custom instructions support (from /compact [instructions])
  • Iterative context (previous summary carried forward)
  • formatCompactSummary() extraction — only the <summary> block is stored; the <analysis> scratchpad is discarded, exactly like Claude Code.

It hooks pi's session_before_compact event and returns the generated summary as the compaction result.


Does it actually help? — A/B benchmark

Yes — measured head-to-head against pi's default compaction on the exact same session that produced this package, on the same model, across 10 interleaved trials each. Full methodology and raw data: exp/ and exp/RESULTS.md.

Setup

Knob Value
Corpus the session that built this package (153 messages, ~78k tokens serialized)
Model zai/glm-4.7 (free, 204k ctx) — identical for both arms
maxTokens 20000 (Claude Code's override), both arms
Trials 20 calls total (10 pi + 10 cc), shuffled, concurrency 5
Prompts extracted verbatim from each tool's source

Headline results (10/10 OK on both arms)

Metric pi-default Claude-Code Δ
Output length 5,183 chars (1,296 tok) 11,766 chars (2,942 tok) CC 2.27× longer
Latency 93 s 135 s CC 1.45× slower
Length variance (CV) 13 % 25 % CC less predictable
Section coverage 100 % (6/6) 100 % (9/9) tie
<analysis>/<summary> tags n/a 10/10 perfect compliance
Avg entity recall 8.3 / 10 10.0 / 10 CC perfect

The real differentiator — entity recall

How often each key fact from the session survived compaction (out of 10 runs):

Entity pi-default Claude-Code
pi-cc-compact (this pkg) 10/10 10/10
Claude Code 10/10 10/10
session_before_compact hook 10/10 10/10
9-section / analysis format 10/10 10/10
leak source (v2.1.68) 10/10 10/10
GitHub publish step 10/10 10/10
extensions/index.ts (file) 8/10 10/10
OpenRouter (tried earlier) 7/10 10/10
패키지 / Korean topic 6/10 10/10
Hypa (the suspect pkg investigated) 2/10 10/10

CC captures every entity in every run. pi-default silently drops long-tail detail — most strikingly, the entire Hypa investigation (a major subplot of the session) survived only 20 % of the time under pi's terse format.

Verdict

CC trades 2.3× post-compaction context cost and 1.45× latency for materially better recall (notably the long-tail details pi's terse format omits). Both prompts are structurally perfect. So:

  • If you want a lean, fast checkpoint → keep pi's default.
  • If you want a faithful, near-lossless carry-forward across compactions → install pi-cc-compact.

The cost is real (more tokens stay in context after each compaction), so this is best for long, complex sessions where losing "what we already figured out" hurts more than the extra tokens.

Reproduce

git clone https://github.com/pinion05/pi-cc-compact
cd pi-cc-compact
node exp/load_corpus.mjs > exp/corpus.txt   # regenerate corpus from a session
node exp/run.mjs                              # ~10 min, 20 LLM calls

exp/corpus.txt is git-ignored (it's a serialized personal session); regenerate it by pointing load_corpus.mjs at any .jsonl session file.


Why

Pi's default compaction summary follows pi's own ## Goal / ## Progress / ... format — a concise checklist. Some users prefer the denser, intent-preserving style Claude Code uses, in particular its insistence on listing all user messages and the verbatim last task so intent doesn't drift across compactions. This package gives you that style without leaving pi.

Install

# Global (available everywhere)
pi install npm:pi-cc-compact

# Project-only
pi install -l npm:pi-cc-compact

Or pin a version:

pi install npm:pi-cc-compact@0.1.0

Try without installing

pi -e npm:pi-cc-compact

How it works

  1. On compaction (auto or /compact), pi fires session_before_compact with messagesToSummarize + any split-turn prefix.
  2. This extension serializes those messages to text (serializeConversation), prepends the reconstructed Claude Code prompt, and calls the model.
  3. The <summary> block is extracted from the response (analysis discarded).
  4. The summary is returned as pi's compaction result — firstKeptEntryId and tokensBefore are passed through unchanged from pi's preparation.

Configuration

Model selection

By default, the current conversation model is used (matching Claude Code, which summarizes with its mainLoopModel). Override with an env var:

# Cheap/fast summarization with Gemini Flash
export PI_CC_COMPACT_MODEL="google/gemini-2.5-flash"

# Or any provider/model id registered in your models.json
export PI_CC_COMPACT_MODEL="anthropic/claude-haiku-4"

Format: provider/modelId. If unset or malformed, the conversation model is used.

Max output tokens

Hard-set to 20000, mirroring Claude Code's maxOutputTokensOverride. This is intentional — the 9-section summary needs the room. (Not currently configurable.)

/compact [instructions]

Custom instructions passed to /compact are honored as Additional Instructions:, exactly like Claude Code's PreCompact-hook integration.

Behavior on failure

If the model call fails, returns empty, or has no API key, the extension falls back to pi's default compaction silently (with a warning). Your session is never left without a summary.

Notes & caveats

  • Extended thinking: Claude Code disables thinking during compaction. This extension does not currently disable it (depends on provider support in the complete() call). On thinking-capable models the summary may cost more tokens.
  • Tool results are truncated to 2000 chars by pi's serializeConversation before this extension ever sees them — same budget Claude Code effectively works within.
  • Not affiliated with Anthropic. The prompt text is reconstructed from public leaks for interoperability. "Claude Code" is a trademark of Anthropic.

Uninstall

pi remove npm:pi-cc-compact

License

MIT