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/jananthan30/Resume-BuilderWrote 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/jananthan30/resume-builder/resume-team)<a href="https://agentmods.dev/commands/jananthan30/resume-builder/resume-team"><img src="https://agentmods.dev/badge/commands/jananthan30/resume-builder/resume-team/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/jananthan30/resume-builder/resume-team"><img src="https://agentmods.dev/badge/commands/jananthan30/resume-builder/resume-team.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 | $0.00016 | $0.03897 |
| Opus 5.5 | $0.00006 | $0.01559 |
| Sonnet 5.5 | $0.00003 | $0.00779 |
| Haiku 4.5 | $0.00002 | $0.00390 |
Grade A, and why
resume-team 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Team Coordinator
Use the native subscription host to coordinate a factual, role-separated resume draft for this job description:
$ARGUMENTS
Authoritative executable path
CANDIDATE-FIT PREFLIGHT (MANDATORY FIRST GATE)
Before invoking the native team, any role agent, or creating an output/application
directory, resolve master_resume_path from config.json and put the exact job
description in a private temporary UTF-8 file. The configured master resume is the
only resume that may be screened; never screen or substitute a previously tailored
resume. Generate one safe run_id, one safe case_id, and one strict ISO calendar
as_of_date, then run the deterministic machine preflight:
python candidate_fit_preflight.py --resume <configured-master-resume> --job-description <private-exact-JD.txt> --run-id <run_id> --case-id <case_id> --as-of-date <YYYY-MM-DD> --json
The JSON report must contain exactly the trusted candidate-fit-policy-v3
assessment bound to those run/case IDs, date, master-resume SHA-256, and exact-JD
SHA-256. Recompute its canonical JSON SHA-256 as candidate_fit_report_digest.
Continue only on exit 0 and a valid report with threshold: 70.0, score >= 70,
extraction_trustworthy: true, hard_knockouts: [], passed: true, and
codes: []. Exit 1, any score below 70 (including 60–69), or any hard knockout
is terminal REJECTED:CANDIDATE_FIT; do not invoke Researcher, Writer, Auditor,
Editor, or native_resume_team.py, and do not create an application directory,
DOCX, tracker row, or resume draft. Exit 2 or any unavailable, malformed,
non-canonical, stale, or digest-mismatched report is
FAILED:CANDIDATE_FIT_PREFLIGHT and fails closed. There is no automatic or manual
workflow bypass. ATS and HR baseline scores are separate advisory diagnostics and
cannot override this gate.
The prohibition above covers the authorized pipeline only: no gate outcome may be
negotiated into the native runtime, its receipts, or its authorized wrappers.
Separately, the user may record a deliberate manual override with
candidate_fit_override.py (candidate-fit-override/v1, decision
PROCEED_MANUAL): it requires a rejected gate and an explicit reason, binds the
exact gate/review reports and digests it overrules, and authorizes only a
coordinator-built manual package (truthful master-sourced content,
evidence_audit.py, human_voice_audit.py, resume_integrity_audit.py,
non-authorized renderers, MANUAL_DRAFT.txt labeling). It never invokes the
runtime, creates receipts, or updates the tracker through authorized wrappers.
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 · 139 lines · 16 tokens per session scan A cba694a73cbe
resume-team is a command published in the GitHub repository jananthan30/Resume-Builder (87 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 3,897 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 2026-08-30.
Other commands, from other repositories
job-search
Search live IT vacancies on freehire and shortlist the ones worth applying to.
tailor-cv
Reframe a CV toward one vacancy, citing evidence for every claim.
triage-inbox
Sort application mail into the freehire tracker and drain the link queues.
market-fit
Score a stack against live vacancy demand and name the gaps worth closing.
track-applications
Review where every application stands and bring the tracker up to date.
start
Onboard with Rebound — capture your base resume and build your private profile (skills, differentiators, and situation).