pirecall
v0.1.0
Published
Sync pi.dev agent sessions to SQLite and recall context from past sessions
Maintainers
Readme
pirecall
Sync pi.dev agent sessions to SQLite for analytics. Query your session history, token usage, tool calls, cost, and model switches.
Quick Start
Use pirecall inline in pi sessions. Tell the agent:
"run npx pirecall sync then show me my top 5 projects by token usage"
"use npx pirecall search to find sessions where we discussed database migrations"
"run npx pirecall stats and tell me how much I've spent this week"The agent runs the command, gets structured output, and can answer follow-up questions about your session history.
How It Works
Pi stores sessions as JSONL files in ~/.pi/agent/sessions/.
pirecall parses these into a SQLite database so you can query across
all sessions.
Step 1. Sync your sessions:
npx pirecall syncStep 2. pirecall incrementally imports new content and reports what it found:
Synced 24 sessions, 136 messages, 22 tool calls, 59 model changesStep 3. Query the database using any pirecall command or raw SQL:
npx pirecall stats
npx pirecall search "database migration"
npx pirecall query "SELECT project_path, SUM(cost_total) FROM sessions s JOIN messages m ON m.session_id = s.id GROUP BY project_path ORDER BY 2 DESC LIMIT 5"Important: The agent doesn't know about pirecall unless you mention it. Just mention
{npx,pnpx,bunx} pirecalland the agent will discover subcommands and flags from the CLI output.
Commands
npx pirecall sync # Import sessions (incremental)
npx pirecall stats # Session/message/token/cost counts
npx pirecall sessions # List recent sessions
npx pirecall search <term> # Full-text search across messages
npx pirecall tools # Most-used tools
npx pirecall recall <term> # LLM-optimised context retrieval
npx pirecall query "<sql>" # Raw SQL against the database
npx pirecall schema # Show database table structure
npx pirecall compact # Prune old tool resultsAll commands support --json for programmatic output and
-d, --db <path> to use a custom database path (default:
~/.pi/pirecall.db).
Database Schema
erDiagram
sessions ||--o{ messages : contains
sessions ||--o{ tool_calls : contains
sessions ||--o{ tool_results : contains
sessions ||--o{ model_changes : tracks
messages ||--o{ tool_calls : has
messages ||--o{ tool_results : has
tool_calls ||--o{ tool_results : produces
sessions {
text id PK
text project_path
text cwd
int first_timestamp
int last_timestamp
}
messages {
text id PK
text session_id FK
text parent_id
text type
text provider
text model
text content_text
text content_json
text thinking
int timestamp
int input_tokens
int output_tokens
int cache_read_tokens
int cache_write_tokens
real cost_total
}
tool_calls {
text id PK
text message_id FK
text session_id FK
text tool_name
text tool_input
int timestamp
}
tool_results {
int id PK
text tool_call_id FK
text message_id FK
text session_id FK
text content
int is_error
int timestamp
}
model_changes {
text id PK
text session_id FK
text parent_id
text provider
text model_id
int timestamp
}
sync_state {
text file_path PK
int last_modified
int last_byte_offset
}Model/Provider Tracking
Tracks mid-session model switches from ~/.pi/agent/sessions/.
Pi supports multiple providers (Anthropic, Mistral, etc.) and
pirecall records every switch with provider and model ID.
Why track model changes?
- See which models you actually use vs which you think you use
- Compare cost across providers for similar tasks
- Debug sessions where model switches caused behaviour changes
Example Queries
-- Cost by session
SELECT s.project_path, s.id, SUM(m.cost_total) as cost
FROM sessions s
JOIN messages m ON m.session_id = s.id
GROUP BY s.id
ORDER BY cost DESC
LIMIT 10;
-- Token usage by day
SELECT DATE(timestamp/1000, 'unixepoch') as day,
SUM(input_tokens + output_tokens) as tokens,
ROUND(SUM(cost_total), 4) as cost
FROM messages
GROUP BY day
ORDER BY day DESC;
-- Model usage across providers
SELECT provider, model_id, COUNT(*) as switches
FROM model_changes
GROUP BY 1, 2
ORDER BY switches DESC;
-- Most used models
SELECT model, COUNT(*) as count
FROM messages
WHERE model IS NOT NULL
GROUP BY model
ORDER BY count DESC;
-- Tool usage breakdown
SELECT tool_name, COUNT(*) as count
FROM tool_calls
GROUP BY tool_name
ORDER BY count DESC;
-- Files read in a session
SELECT tc.tool_name, json_extract(tc.tool_input, '$.file_path') as file
FROM tool_calls tc
WHERE tc.tool_name = 'read' AND tc.session_id = 'your-session-id';
-- Cost by provider
SELECT m.provider, ROUND(SUM(m.cost_total), 4) as cost,
SUM(m.input_tokens + m.output_tokens) as tokens
FROM messages m
WHERE m.provider IS NOT NULL
GROUP BY m.provider
ORDER BY cost DESC;Requirements
- Node.js 22+
License
MIT
