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 Not-Diamond/self-care/plugin install self-careWrote 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/commands/not-diamond/self-care/review)<a href="https://agentmods.dev/commands/not-diamond/self-care/review"><img src="https://agentmods.dev/badge/commands/not-diamond/self-care/review.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.02987 |
| Opus 5 | $0.00006 | $0.01494 |
| Sonnet 5 | $0.00002 | $0.00597 |
| Haiku 4.5 | $0.00001 | $0.00299 |
Grade A, and why
review 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 6d 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 — 390 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Unreviewed Reports
Review reports that have not been reviewed yet (review_status: pending). Walks through findings for each report using the same review flow as /self-care:run stages 4, 5, and 6.
Stage 0: Parse Arguments
Parse $ARGUMENTS to extract:
- count: Optional positive integer — the number of reports to review. Defaults to all pending reports if not specified.
Example inputs:
- `` (empty) → review all pending reports
3→ review the 3 most recent pending reports1→ review only the most recent pending report
Stage 1: Find Pending Reports
Use Bash to find all reports with review_status: pending in ./.self-care/reports/:
grep -l 'review_status: pending' ./.self-care/reports/*-triage.md 2>/dev/null | sort -r
This returns report files sorted newest-first (filenames start with YYYY-MM-DD).
For each report file found, verify that a corresponding data sidecar exists. The data file has the same name but with -data.json instead of -triage.md:
- Report:
./.self-care/reports/2026-04-01-abc12345-triage.md - Data:
./.self-care/reports/2026-04-01-abc12345-data.json
Skip any report whose data sidecar is missing (output a warning: ⚠ Skipping <report_file>: data file not found).
If count is specified, take only the first count reports from the sorted list.
If no pending reports are found, output:
No unreviewed reports found in ./.self-care/reports/
And stop.
Otherwise, output:
Found <N> unreviewed report(s). Reviewing <M> report(s)...
Where <N> is the total pending and <M> is the number being reviewed (limited by count if specified).
Stage 2: Review Each Report
For each pending report (newest first):
2a. Load Report Data
Read the data sidecar JSON file. Extract:
- format: trace format (otel or claude-code)
- metadata: trace metadata
- cases: the full case array (type, severity, description, evidence, classification, proposedFix)
- agentContext: optional user-provided context
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.
- 6d ago First seen · 390 lines · 12 tokens per session scan A 65bf9fa8edae
review is a command published in the GitHub repository Not-Diamond/self-care (28 stars, last pushed 4mo ago), licensed MIT. It adds 12 tokens to every session and 2,987 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 2026-08-30.
Other commands, from other repositories
optimize
Show TokenJam's savings/optimize report — where quota is going and what's recoverable. Equivalent to running tj optimize.
status
Show TokenJam's current status for every tracked agent — token usage, cost today, and active alerts. Equivalent to running tj status.
uninstall
Remove TokenJam's Claude Code integration — unwires the statusline, hooks, and OTel env vars that /onboard set up. Equivalent to running tj uninstall --yes. Does not remove the plugin itself.
doctor
Run TokenJam's health check — config, ingest endpoint, and storage. Equivalent to running tj doctor.
onboard
Set up TokenJam for this Claude Code install — wires the zero-token statusline, the resume-brief SessionStart hook, and local OTel telemetry ingest via the existing tj onboard command. Runs 100% locally, no signup.
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.