resume-team

resume-team is a skill for Claude Code, Codex from jananthan30/Resume-Builder. It costs 71 tokens per session (1,752 once invoked), scanned A, original, MIT.

A set of separate research, writing, checking, and editing steps for producing a verified Markdown resume draft tailored to a job description.

In plain words
What is it for?
Screening candidate fit, tailoring a resume, checking its sources and consistency, and publishing an approved Markdown draft.
Why use it?
It applies strict checks to the source resume and job fit before creating a draft, helping prevent unsupported or unsuitable changes.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present. Also seen: mentions Codex.

Part of the Resume-Builder plugin — 9 skills, 9 commands, 4 agents, 1 hook, 1 MCP server shipped together

Good fit Screening candidate fit, tailoring a resume, checking its sources and consistency, and publishing an approved Markdown draft.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jananthan30/resume-builder/resume-team
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.

Any agent
npx skills add jananthan30/Resume-Builder --skill resume-team
Clone the repo
git clone --depth 1 https://github.com/jananthan30/Resume-Builder

Made for: Claude Code, Codex.

Or install Resume-Builder, the plugin that ships this one along with the rest of its 9 skills, 9 commands, 4 agents, 1 hook, 1 MCP server.

Wrote 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.

agentmods badge for resume-team

README.md
[![agentmods](https://agentmods.dev/badge/skills/jananthan30/resume-builder/resume-team/github.svg)](https://agentmods.dev/skills/jananthan30/resume-builder/resume-team)
Your own site
<a href="https://agentmods.dev/skills/jananthan30/resume-builder/resume-team"><img src="https://agentmods.dev/badge/skills/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.

agentmods 80×15 button for resume-team

Your own site · 80×15
<a href="https://agentmods.dev/skills/jananthan30/resume-builder/resume-team"><img src="https://agentmods.dev/badge/skills/jananthan30/resume-builder/resume-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,752 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00071 $0.01752
Opus 5 $0.00036 $0.00876
Sonnet 5 $0.00014 $0.00350
Haiku 4.5 $0.00007 $0.00175

Measured 12d ago against content hash 27ed31bd84f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 12d 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.

skills/resume-team/SKILL.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resume Team

  1. Resolve the plugin root two directories above this file. Require macOS or Linux, candidate_fit_preflight.py, native_resume_team.py, config.json, and the configured master resume. Fail closed if any is unavailable. Put the exact job description in a private temporary UTF-8 file, and generate a safe run_id, safe case_id, and strict ISO as_of_date. Before invoking the native team or creating an output directory, screen only master_resume_path from config.json (never a previous tailored resume):

    python candidate_fit_preflight.py --resume <CONFIGURED_MASTER> --job-description <PRIVATE_EXACT_JD.txt> --run-id <RUN_ID> --case-id <CASE_ID> --as-of-date <YYYY-MM-DD> --json

    Continue only on exit 0 and a valid digest-bound candidate-fit-policy-v3 report with threshold 70.0, score at least 70, trustworthy extraction, zero hard knockouts, passed: true, and no codes. Canonically hash the exact report as candidate_fit_report_digest. Exit 1, any score below 70 (including 60–69), or any hard knockout is REJECTED:CANDIDATE_FIT; report it and create no output, draft, DOCX, or tracker row. Exit 2 or an unavailable, malformed, stale, non-canonical, or digest-mismatched report is FAILED:CANDIDATE_FIT_PREFLIGHT. Neither condition has a bypass. ATS/HR scores are advisory and cannot override candidate fit.

  2. Only after candidate fit passes, run the non-model host preflight. Windows is not supported by the hardened runtime; its host preflight returns POSIX_RUNTIME_REQUIRED:

    python native_resume_team.py --host codex --check-host --config config.json

    Continue only when it exits 0 and returns ready: true with every check passing.

  3. Choose only a prospective new output path. Use a user-supplied path only when it does not exist; otherwise derive a sanitized, non-existing applications/<Company> - <Role> path from the job description. Do not create it. Never reuse, replace, or clobber an existing output or resume.md; the runtime intentionally has no replacement mode.

  4. Capture the runtime's exact stdout in a private temporary result file so the result-provided authorization sidecar path and digest remain available to finalization:

    runtime_result_file="$(mktemp)"; python native_resume_team.py --host codex --job-description-file <PRIVATE_EXACT_JD.txt> --output-dir <APP_DIR> --config config.json --run-id <RUN_ID> --case-id <CASE_ID> --as-of-date <YYYY-MM-DD> >"$runtime_result_file"

    Preserve and check the Python process exit status before parsing the single JSON result from that file. Do not reconstruct result fields from logs or filenames. The runtime independently recomputes the same fit report before constructing an output or role adapter. Require its report and canonical digest to exactly match the caller-validated preflight. Only then does it create <APP_DIR> and atomically bind that exact text to <APP_DIR>/job_description.txt; it accepts only a byte-identical pre-existing regular file and never clobbers a different one. The Researcher contract admits only nonblank, alphanumeric requirements that each cover one exact, unique, complete non-separator JD line; substrings are rejected so surrounding negation, scope, bounds, and qualification cannot be trimmed before the Writer or Auditor sees the rubric.

    Omit --model and --reasoning-effort by default. The hardened subprocess ignores user configuration and transient parent-session settings, so report its effective model/reasoning selection as the isolated managed CLI default and unknown—not as an inherited model, Ultra setting, or profile. Only when the user explicitly requests a Codex pin may you append --model <exact-model> and/or --reasoning-effort ultra. There is no runtime profile or replacement option; always choose a new output directory and fail closed rather than clobber an existing artifact.

  5. Accept draft-stage success only when the process exits 0, the captured result is resume-team-result/v2 with terminal_class: PUBLISHED, its candidate_fit_report and candidate_fit_report_digest exactly match the independently validated preflight, and <APP_DIR>/resume.md exists with the reported final_draft_digest. Independently hash resume.md. Resolve the exact authorization_receipt_path from that result against <APP_DIR> when relative and require the resolved path's parent to equal the resolved output directory. Then invoke the code-bound acceptance gate with the exact result-provided digest and require exit 0 plus verified: true:

Read the full file on GitHub · 90 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 90 lines · 71 tokens per session scan A 27ed31bd84f8

Subscribe to this mod's changes

resume-team is a skill published in the GitHub repository jananthan30/Resume-Builder (83 stars, last pushed 28d ago), licensed MIT. It adds 71 tokens to every session and 1,752 once invoked, about $0.0004 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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