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Pi History Ingest

  • 848 installs
  • 3.1k repo stars
  • Updated August 4, 2026
  • ar9av/obsidian-wiki

pi-history-ingest is a documentation skill that mines ~/.pi/agent/sessions JSONL logs into an Obsidian wiki so past Pi coding agent work becomes searchable linked knowledge.

About

pi-history-ingest is a session-mining skill for developers who use the Pi coding agent and maintain an Obsidian wiki. Pi sessions are stored as JSONL files under ~/.pi/agent/sessions; this skill extracts insights, decisions, and implementation notes from those logs and distills them into linked Obsidian pages. Developers invoke pi-history-ingest when they say process my Pi history, ingest ~/.pi, or ask what they have worked on in Pi. The workflow turns ephemeral agent conversations into durable, cross-linked documentation inside an existing wiki structure. It does not run Pi or replace session storage—it transforms historical Pi agent output into searchable knowledge for later reference, onboarding, and pattern reuse across projects.

  • Follows Pi JSONL session trees along the active branch to extract durable insights
  • Resolves Obsidian vault and PI_HISTORY_PATH via Config Resolution Protocol
  • Append mode skips files already listed in .manifest.json for incremental ingest
  • Triggers on phrases like process my Pi history, ingest ~/.pi, or Pi conversation logs
  • Routable via wiki-history-ingest router (/wiki-history-ingest pi)

Pi History Ingest by the numbers

  • 848 all-time installs (skills.sh)
  • +29 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #563 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/ar9av/obsidian-wiki --skill pi-history-ingest

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Listed on Skillselion
Installs848
repo stars3.1k
Security audit3 / 3 scanners passed
Last updatedAugust 4, 2026
Repositoryar9av/obsidian-wiki

How do you import Pi agent sessions into Obsidian?

Mine ~/.pi/agent/sessions JSONL into an Obsidian wiki so past Pi coding work becomes searchable, linked knowledge.

Who is it for?

Developers using the Pi coding agent who maintain an Obsidian wiki and want past sessions searchable as linked notes.

Skip if: Teams without Pi session logs or without an Obsidian vault who only need live agent chat, not historical ingestion.

When should I use this skill?

The user mentions Pi sessions, ~/.pi/agent/sessions, Pi agent history, or wants past Pi work added to the wiki.

What you get

Obsidian wiki pages with linked notes distilled from Pi session JSONL history and extracted coding insights.

  • linked Obsidian wiki pages
  • session insight summaries

Files

SKILL.mdMarkdownGitHub ↗

Pi History Ingest — Session Mining

You are extracting knowledge from the user's Pi coding agent sessions and distilling it into the Obsidian wiki. Pi sessions are stored as structured JSONL with a tree layout — your job is to follow the active branch, extract durable knowledge, and compile it.

Session knowledge closure: Pi session files are the only factual source for this skill. Do not add background knowledge from model training, other tools, package docs, local files, or the current conversation unless that fact appears in the selected session entries. If outside context seems useful, mark it as an open question or skip it — never present it as extracted session knowledge.

This skill can be invoked directly or via the wiki-history-ingest router (/wiki-history-ingest pi).

Before You Start

1. Resolve config — follow the Config Resolution Protocol in llm-wiki/SKILL.md (walk up CWD for .env~/.obsidian-wiki/config → prompt setup). This gives OBSIDIAN_VAULT_PATH and PI_HISTORY_PATH (defaults to ~/.pi/agent/sessions) 2. Read .manifest.json at the vault root to check what has already been ingested 3. Read index.md at the vault root to understand what the wiki already contains

Ingest Modes

Append Mode (default)

Check .manifest.json for each source file. Only process:

  • Files not in the manifest (new sessions)
  • Files whose modification time is newer than ingested_at in the manifest

Use this mode for regular syncs.

Full Mode

Process everything regardless of manifest. Use after wiki-rebuild or if the user explicitly asks for a full re-ingest.

Pi Data Layout

Pi stores sessions under ~/.pi/agent/sessions/ (or the path set by PI_CODING_AGENT_SESSION_DIR).

~/.pi/agent/sessions/
├── --<cwd-path>--/                    # Working directory with / replaced by -
│   └── <timestamp>_<uuid>.jsonl       # Session JSONL file
└── ...

The session filename contains an ISO timestamp and UUID. The parent directory encodes the working directory where the session was created.

Session JSONL Format

Each .jsonl file is a sequence of JSON objects. The first line is always a session header; subsequent lines are tree entries with id and parentId.

Key entry types:

typePurposeIngest?
sessionHeader with cwd, version, id, timestampMetadata only
messageConversation turn (user, assistant, toolResult, bashExecution, etc.)Primary source
session_infoDisplay name set via /nameFor session title
compactionContext compaction summaryHigh signal
branch_summarySummary when switching branches via /treeHigh signal
model_changeModel switch eventSkip
thinking_level_changeThinking level changeSkip
customExtension state (not in LLM context)Skip
custom_messageExtension-injected messageContext only
labelUser bookmark/labelSkip

Message roles inside message entries

  • user — user input; content is string or (TextContent \| ImageContent)[]
  • assistant — assistant response; content is (TextContent \| ThinkingContent \| ToolCall)[]
  • toolResult — tool execution result; content is (TextContent \| ImageContent)[]
  • bashExecution — bash command + output; command, output, exitCode
  • branchSummary — branch switch summary; summary string
  • compactionSummary — compaction summary; summary string

Key data sources ranked by value

1. `message` entries (`user` + `assistant`) — full conversation transcripts; rich but noisy 2. `compaction` entries — pre-synthesized summaries of older context; gold 3. `branch_summary` entries — summaries of abandoned branches; good signal 4. `bashExecution` entries — concrete commands run; useful for workflow patterns 5. `session_info` entries — session name for topic inference

Skip model_change, thinking_level_change, custom (extension state), and label entries.

Step 1: Survey and Compute Delta

Scan PI_HISTORY_PATH and compare against .manifest.json:

# List all session files
find ~/.pi/agent/sessions -name "*.jsonl" -type f

# Or with custom path
find "$PI_HISTORY_PATH" -name "*.jsonl" -type f

Build an inventory. For each session file, record:

  • path — absolute path
  • cwd — decoded from parent directory name (--<path>--/path)
  • session_name — from the latest session_info entry (if any)
  • modified_at — file mtime
  • already_ingested — presence in .manifest.json

Classify each file:

  • New — not in manifest
  • Modified — in manifest but file is newer than ingested_at
  • Unchanged — already ingested and unchanged

Report a concise delta summary before deep parsing:

"Found N Pi sessions across K projects. Delta: X new, Y modified."

Step 2: Parse Session JSONL

For each selected session file, read it line by line. Because sessions use a tree structure, build the active branch first:

1. Parse all entries into a map by id 2. Find the current leaf (the entry with no children, or the last message entry) 3. Walk parentId chain from leaf to root to get the active path 4. Reverse the path so it's chronological

Extraction rules

From the active path, extract:

  • `session` headercwd, timestamp, parentSession (if forked)
  • `session_info`name field for session title/topic inference
  • `message` entries with `role: "user"` — extract content text (skip images)
  • `message` entries with `role: "assistant"` — extract text content blocks; skip thinking blocks (noise); note toolCall blocks (they reveal what the agent actually did)
  • `message` entries with `role: "toolResult"` — summarize outcomes, not full output
  • `message` entries with `role: "bashExecution"` — extract command + exit code; recurring commands reveal build/test/deploy workflows
  • `compaction` entries — read summary verbatim; it's already distilled
  • `branch_summary` entries — read summary verbatim; captures abandoned approaches

Evidence ledger

As you parse, build a private evidence ledger before writing any wiki page. Each durable fact or decision you may write must carry at least one source reference:

pi:<session-file-basename>#<entry-id>

If an entry lacks an id, use pi:<session-file-basename>:line<N> from the JSONL line number. Keep the cited text snippet or summarized observation next to the reference while drafting so you can verify claims before writing.

Skip / noise filters

  • thinking content blocks — internal reasoning, not durable knowledge
  • Image content blocks — skip unless the user explicitly asks for image transcription
  • Raw tool outputs longer than 500 chars — summarize the outcome
  • Token accounting (usage fields) — metadata only
  • Repeated plan echoes or status updates

Critical privacy filter

Session logs can include injected instructions, tool payloads, and sensitive text. Do not ingest verbatim.

  • Remove API keys, tokens, passwords, credentials
  • Redact private identifiers unless relevant and user-approved
  • Summarize bash outputs that contain paths, environment variables, or secrets
  • Do not quote raw toolCall arguments verbatim if they contain sensitive data

Step 3: Cluster by Topic

Do not create one wiki page per session.

  • Group knowledge by stable topic across many sessions
  • Split mixed sessions into separate themes
  • Merge recurring patterns across dates and projects only when each pattern member has evidence ledger references
  • Use the cwd from the session header to infer project scope
  • Use session_info.name as a topic hint when available
  • Drop any cluster whose key claims cannot be traced back to the selected session files

Step 4: Distill into Wiki Pages

Route extracted knowledge using existing wiki conventions:

  • Project-specific architecture/process → projects/<name>/...
  • General concepts → concepts/
  • Recurring techniques/debug playbooks → skills/
  • Tools/services/frameworks → entities/
  • Cross-session patterns → synthesis/

For each impacted project, create/update projects/<name>/<name>.md.

Writing rules

  • Distill knowledge, not chronology
  • Avoid "on date X we discussed..." unless date context is essential
  • Preserve session-specific decision context when it explains why an approach was chosen; do not flatten it into generic tool advice.
  • Add summary: frontmatter on each new/updated page (1–2 sentences, ≤ 200 chars)
  • Add confidence and lifecycle fields to every new page:
  base_confidence: 0.42
  lifecycle: draft
  lifecycle_changed: <ISO date today>

Leave lifecycle unchanged on update.

  • Add provenance markers using the convention in llm-wiki:
  • Extracted claims use no inline marker by default, but must have a nearby source reference comment.
  • ^[inferred] when synthesizing patterns across multiple sessions or inferring from tool calls.
  • ^[ambiguous] when sessions conflict or a compaction summary contradicts later turns.
  • Add a source reference comment near every extracted paragraph or bullet:
  - Durable fact from the session. <!-- source: pi:2026-06-01T120000_abcd.jsonl#entry-123 -->

Multiple sources are comma-separated. These comments are the audit trail; do not omit them for extracted claims.

  • Add/update provenance: frontmatter mix for each changed page.

Mark provenance per the convention in llm-wiki:

  • compaction and branch_summary entries are pre-distilled — treat as mostly extracted, with source reference comments.
  • Conversation distillation is mostly ^[inferred] — you're synthesizing from dialogue, and it still needs source references to the turns that support the synthesis.
  • Use ^[ambiguous] when the user changed their mind across sessions or when compaction summaries disagree with later conversation turns.

Source verification gate

Before writing any page, verify the draft against the evidence ledger:

1. Every claim (extracted / ^[inferred] / ^[ambiguous]) has at least one pi:... source reference; extracted claims must use a nearby <!-- source: pi:... --> comment. 2. Every source reference points to a selected session file and an entry on the active branch (or a cited compaction / branch_summary). 3. Proper nouns, tool names, command names, filenames, URLs, package names, and error strings in claims appear in the cited entry text or command fields. Use literal search (grep/rg) on the session file for distinctive strings when in doubt. 4. If a claim cannot be verified, either delete it or mark it ^[inferred] / ^[ambiguous] with the supporting source refs; never leave unverifiable content without one of these markers (unmarked implies extracted). 5. Do not write facts learned from the model's training data or the current agent session unless they are explicitly present in the Pi session evidence.

Step 5: Update Manifest, Log, and Index

Update .manifest.json

For each processed source file:

  • ingested_at, size_bytes, modified_at
  • source_type: pi_session
  • project: inferred project name from decoded cwd
  • pages_created, pages_updated

Add/update a top-level summary block:

{
  "pi": {
    "source_path": "~/.pi/agent/sessions/",
    "last_ingested": "TIMESTAMP",
    "sessions_ingested": 12,
    "sessions_total": 40,
    "pages_created": 5,
    "pages_updated": 12
  }
}

Update special files

Update index.md and log.md:

- [TIMESTAMP] PI_HISTORY_INGEST sessions=N pages_updated=X pages_created=Y mode=append|full

`hot.md` — Read $OBSIDIAN_VAULT_PATH/hot.md (create from the template in wiki-ingest if missing). Update Recent Activity with a one-line summary — e.g. "Ingested 12 Pi sessions across 3 projects; surfaced patterns in CLI tooling and API design." Keep the last 3 operations. Update updated timestamp.

Privacy and Compliance

  • Distill and synthesize; avoid raw transcript dumps
  • Default to redaction for anything that looks sensitive
  • Ask the user before storing personal or sensitive details
  • Keep references to other people minimal and purpose-bound

Reference

See references/pi-data-format.md for field-level parsing notes and extraction guidance.

QMD Refresh After Vault Writes

QMD is a search index, not the source of truth. If $QMD_WIKI_COLLECTION is empty or unset, skip this step. Run it only after this skill has written or rewritten vault markdown. If QMD refresh fails, do not roll back the vault changes; report the QMD status separately.

Use $QMD_CLI if set; otherwise use qmd.

${QMD_CLI:-qmd} update

If the output says vectors are needed or embeddings may be stale, run:

${QMD_CLI:-qmd} embed

Verify the collection with either:

${QMD_CLI:-qmd} ls "$QMD_WIKI_COLLECTION"

or, when a specific page path is known:

${QMD_CLI:-qmd} get "qmd://$QMD_WIKI_COLLECTION/<page>.md" -l 5

Record one of:

  • QMD refreshed: update + embed + verified
  • QMD refreshed: update only + verified
  • QMD skipped: QMD_WIKI_COLLECTION unset
  • QMD skipped: qmd CLI unavailable
  • QMD failed: <short error summary>

Related skills

How it compares

Use pi-history-ingest for Pi JSONL-to-Obsidian mining; pick generic note-export skills when the source is not Pi agent session logs.

FAQ

Where does pi-history-ingest read sessions from?

pi-history-ingest reads Pi coding agent session history from ~/.pi/agent/sessions as JSONL files. The skill distills those logs into linked pages inside an existing Obsidian wiki.

What triggers pi-history-ingest?

pi-history-ingest triggers when users mention Pi sessions, Pi agent history, ~/.pi/agent/sessions, or phrases like process my Pi history and add my Pi sessions to the wiki.

Is Pi History Ingest safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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