can1357
4fe2572629
- Added a new `--since` CLI window option and applied a timestamp cutoff to tools, edits, and followups queries, including session-count updates. - Updated edit analytics to treat `is_error` as authoritative, added hashline op parsing from edit input, and expanded failure classification patterns for hashline error cases.
session-stats
Ad-hoc analyses over the local agent session corpus
(~/.omp/agent/sessions/). SQLite-backed; data is synced once into the same
~/.omp/stats.db that packages/stats uses, then queried by short Python
scripts.
Layout
scripts/session-stats/
sync.py # walks ~/.omp/agent/sessions/ and populates ss_* tables
analyze.py # tools | edits | followups subcommands over the synced db
One-time prep
pip install tiktoken
Sync
bun run stats:sync # incremental
python3 scripts/session-stats/sync.py --workers 16 --full # rebuild all
python3 scripts/session-stats/sync.py --limit 200 # newest 200 only
The sync is incremental: per-file mtime, size, byte_offset, and
parser_version are tracked in ss_sessions. Re-runs only parse new bytes
and only re-tokenize / re-classify what changed. A bump of EDIT_PARSER_VERSION
in sync.py invalidates ss_edit_* rows on next sync.
Tokenization is o200k_base (GPT-4o / GPT-5 family) via tiktoken — well
within ~5–10% of Claude's BPE in aggregate.
Schema
All tables are prefixed ss_ to avoid collision with packages/stats.
| Table | Granularity |
|---|---|
ss_sessions |
one row per .jsonl; carries sync state + session metadata |
ss_tool_calls |
one row per toolCall content block (arg_json, arg_tokens) |
ss_tool_results |
one row per toolResult message (result_text, result_tokens, is_error) |
ss_assistant_msgs |
per assistant message text + thinking blobs and token counts |
ss_user_msgs |
per user message text and token count |
ss_edit_calls |
per edit call: success, warnings, raw_input_len |
ss_edit_sections |
per ¶PATH section in an edit; precomputed longest_repeat_*, dup_anchors. Legacy §PATH sections from pre-2026-05 sessions still parse. |
Indexes on (tool_name, timestamp) and (session_file, seq) make per-tool
aggregations and ordered session walks cheap.
Analyses
bun run stats:tools # per-tool token totals
bun run stats:tools -- --by d --top 8 # bucket by day, top 8 tools each
bun run stats:edits # edit-tool reliability audit
bun run stats:edits -- --since w # edit sub-types over the last week
bun run stats:followups # five hashline-edit detectors
bun run stats:followups -- --max-fix 2 --min-dup 8 --show 20
All three accept -n N / --folder SUBSTR to scope the query, plus
--since <h|d|w|m|Nh|Nd|Nw> to keep only calls newer than a time window
(per-call timestamp, so it slices long sessions precisely). The edits
audit reads each call's is_error flag as the authoritative success/failure
signal and decodes hashline op kinds (replace, insert after, delete,
replace block, …) into the verb distribution.
The Rust crate that previously lived here was retired in favor of this SQLite-backed flow. The schema persists everything the analyses used to recompute on every run (token counts, hashline parse output, success flags), so subsequent invocations are sub-second over the full corpus.