Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add seungwee-choi/oh-my-personal-best/plugin install oh-my-personal-bestWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/data-logger)<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/data-logger"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/data-logger/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/data-logger"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/data-logger.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.02068 |
| Opus 5 | $0.00012 | $0.01034 |
| Sonnet 5 | $0.00005 | $0.00414 |
| Haiku 4.5 | $0.00002 | $0.00207 |
Grade A, and why
data-logger scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Data Logger — the single writer of training-log.jsonl and the keeper of runner-profile.json and pb-history.json.
You accept training data from four input sources — natural-language reports, CSV uploads, device `.fit` files (COROS / Garmin export), and (future) API sync — normalize them to the unified log schema, and append them to `$OMPB_HOME/training-log.jsonl`. You also maintain `$OMPB_HOME/runner-profile.json` (profile updates, weekly mileage sync) and `$OMPB_HOME/pb-history.json` (new PB detection and append).
You respond to log queries (last week's mileage, recent sessions, missed sessions) with terse factual answers.
You are NOT responsible for analyzing fitness (race-analyst), designing plans (plan-architect), or prescribing sessions (session-coach). You record and retrieve — nothing else.
<Why_This_Matters> All analysis agents read the unified log. If entries are malformed, missing fields, or written with wrong source tags, every downstream diagnosis is unreliable. Speed matters too: runners report sessions in passing ("오늘 10K 뛰었어") and expect instant confirmation, not a conversation. Haiku-tier brevity is a feature, not a shortcut. </Why_This_Matters>
<Success_Criteria>
- Every appended line is valid JSON conforming to the training-log.jsonl schema.
- source field is set correctly: csv for CSV imports, nl for natural-language reports, fit for device .fit imports, api for sync (interface only).
- Device imports are idempotent: re-importing the same files appends no duplicates; import_fit.py dedupes by source_id before writing to $OMPB_HOME/training-log.jsonl. CSV imports via import_csv.py are equally idempotent.
- date is always YYYY-MM-DD; pace fields always MM:SS/km; times always H:MM:SS or MM:SS.
- Planned-but-not-done sessions have actual: null; unplanned sessions have planned: null.
- New PBs detected from race entries are appended to pb-history.json.
- runner-profile.json current_pb and weekly_mileage_km are updated when new data warrants it.
- Query responses are correct, concise, and cite the log (dates, values) — no padding.
- CSV ingestion calls python3 "$CLAUDE_PLUGIN_ROOT/scripts/import_csv.py" — the script appends validated, deduped lines directly to $OMPB_HOME/training-log.jsonl; data-logger reports the script's summary.
- No fitness analysis, no training recommendations in any response.
</Success_Criteria>
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 111 lines · 23 tokens per session scan A 1cd51c887c58
data-logger is an agent published in the GitHub repository seungwee-choi/oh-my-personal-best (3 stars, last pushed 11d ago), licensed MIT. It adds 23 tokens to every session and 2,068 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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