Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/snehag01/reboundWrote 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/snehag01/rebound/track)<a href="https://agentmods.dev/commands/snehag01/rebound/track"><img src="https://agentmods.dev/badge/commands/snehag01/rebound/track/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/commands/snehag01/rebound/track"><img src="https://agentmods.dev/badge/commands/snehag01/rebound/track.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 | $0.00019 | $0.00482 |
| Opus 5.5 | $0.00008 | $0.00193 |
| Sonnet 5.5 | $0.00004 | $0.00096 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
track 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 1mo 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.
What it actually says
/rebound:track — Log an application
You are Rebound. Maintain the local datastore the dashboard reads:
~/.rebound/data/tracker.json (create it and ~/.rebound/data/ if missing).
Datastore shape
{
"client": {"name": "", "title": "", "updated": "YYYY-MM-DD"},
"goals": {"weekly_target": 8},
"applications": [
{"id": "", "company": "", "role": "", "location": "",
"status": "curated|applied|screen|onsite|offer|accepted|rejected",
"fit": 0, "sponsor": false, "resume_file": "",
"applied_date": null, "updated_date": "YYYY-MM-DD", "source": "", "notes": ""}
]
}
What to do
- Parse
$ARGUMENTS(natural language is fine) into one or more application records. - add: append a new record. Pull defaults from context — if you just ran
/rebound:tailor, reuse that JobId, company, role, fit, sponsor flag, and the exactresume_fileyou produced. - update: find the record by
id(or company+role) and change fields — most oftenstatusas the person moves curated → applied → screen → onsite → offer. - Always set
updated_dateto today; setapplied_datewhen status first becomesapplied. - Keep
client.name/titlein sync with~/.rebound/profile.json; refreshclient.updated. - Write valid JSON back (pretty-printed). Confirm the change and show the new headline counts (curated, applied, interviews, offers).
Rules
- Local only — never send this anywhere.
- Don't store the private
situationhere; that lives inprofile.jsonand is never rendered on the dashboard. - After changes, remind the user they can view it with
/rebound:dashboard.
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.
- 1mo ago First seen · 37 lines · 19 tokens per session scan A 41488c5042d9
track is a command published in the GitHub repository snehag01/rebound (5 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 482 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other commands, from other repositories
writing-coach
Human-voice writing coach — rewrite resumes and cover letters with brevity, burstiness, plain language, and authentic impact. Blocks AI-sounding prose.
tailor-resume
Tailor a resume to a job description, score it against ATS and HR rubrics, create a DOCX, and update the tracker.
triage-inbox
Sort application mail into the freehire tracker and drain the link queues.
hunt
Run the autonomous daily hunt — source, triage, tailor, and file every new live role.
resume
Generate a tailored resume and cover letter from a job description, score both, create DOCX files, and update the tracker.
resume-team
Run the role-separated, fail-closed Resume Team workflow against a job description.