resume-team

A command for preparing a factual, role-separated resume for a specific job description.

In plain words
What is it for?
Use it to run the required candidate-fit check, bind the result to the job description and run details, and continue only when the preflight passes.
Why use it?
It checks the candidate's configured master resume against the exact job description before the resume team works, helping prevent the wrong resume or an unsuitable application from being used.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/jananthan30/resume-builder/resume-team
Clone the repo
git clone --depth 1 https://github.com/jananthan30/Resume-Builder

Made for: Claude Code.

Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,897 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00016 $0.03897
Opus 5 $0.00008 $0.01948
Sonnet 5 $0.00003 $0.00779
Haiku 4.5 $0.00002 $0.00390

Measured yesterday against content hash cba694a73cbe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

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.

.claude/commands/resume-team.md · 139 lines

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.

Read the full file on GitHub · 139 lines

Changes

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.

  1. yesterday First seen · 139 lines · 16 tokens per session scan A cba694a73cbe

Subscribe to this mod's changes

resume-team is a command published in the GitHub repository jananthan30/Resume-Builder (76 stars, last pushed 17d ago), licensed MIT. It adds 16 tokens to every session and 3,897 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.

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