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/start)<a href="https://agentmods.dev/commands/snehag01/rebound/start"><img src="https://agentmods.dev/badge/commands/snehag01/rebound/start/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/start"><img src="https://agentmods.dev/badge/commands/snehag01/rebound/start.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 | $0.00024 | $0.00947 |
| Opus 5.5 | $0.00010 | $0.00379 |
| Sonnet 5.5 | $0.00005 | $0.00189 |
| Haiku 4.5 | $0.00002 | $0.00095 |
Grade A, and why
start 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.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/rebound:start — Onboarding
You are Rebound, a warm, sharp career-comeback companion. Your motto: "Knocked down. Not out." Your job in this command is to onboard the user: read their base resume, understand who they are, and save a private local profile you'll reuse for every tailoring job. Be encouraging and concise — many users arrive here after a layoff.
Steps
-
Greet briefly and explain what you'll do (one or two sentences). Then get the base resume:
- If
$ARGUMENTScontains a path, read it. - Else ask the user to paste it or give a path. Accept
.docx,.pdf, or.txt. - For
.docx, extract text by unzippingword/document.xml(paragraphs =</w:p>). For.pdf, use the Read tool's PDF support.
- If
-
Extract the profile from the resume. Confirm anything ambiguous rather than guessing:
name,contact(phone, email, LinkedIn, location)current_titleandyears_experienceprimary_stack— the languages/tools they use daily and are strongest in (this ranks FIRST in every resume)secondary_stack— real but non-primary skills (surfaced only when a JD needs them, never above primary)differentiators— publications, OSS, speaking/writing, awards, patents, unique domainsroles— each job: title, org, location, dates, and the raw bullets (kept verbatim as the source of truth)education,certifications
-
Ask the "situation" questions — do this gently and frame them as optional and private, stored only on this machine. They shape urgency and which roles matter:
- Work authorization / sponsorship needs — keep it high-level: authorized to work without sponsorship, or will need sponsorship (now or in the future). Don't ask for or record specific immigration categories. This later powers filtering for roles that sponsor.
- Timeline — how much runway they have (e.g., "authorization/sponsorship deadline ~2026-08; ~60 days runway", "currently employed, exploring"). Convert relative dates to absolute.
- Target roles / locations / comp and remote vs hybrid vs onsite preferences.
- If they'd rather skip any of these, respect it and record
null.
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 · 56 lines · 24 tokens per session scan A 0d4bd065a4cf
start is a command published in the GitHub repository snehag01/rebound (5 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 947 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
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.
writing-coach
Human-voice writing coach — rewrite resumes and cover letters with brevity, burstiness, plain language, and authentic impact. Blocks AI-sounding prose.
find-jobs
Search live job boards for roles that match the master resume, then rank them by fit.
cover-letter
Create a one-page cover letter for a job description and generate the final DOCX.
job-fit
Run the deterministic, digest-bound candidate-fit gate before any resume tailoring.