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.
npx skills add olegvg/resume-tailor-plugin --skill onboardinggit clone --depth 1 https://github.com/olegvg/resume-tailor-pluginWrote 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/skills/olegvg/resume-tailor-plugin/onboarding)<a href="https://agentmods.dev/skills/olegvg/resume-tailor-plugin/onboarding"><img src="https://agentmods.dev/badge/skills/olegvg/resume-tailor-plugin/onboarding/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/skills/olegvg/resume-tailor-plugin/onboarding"><img src="https://agentmods.dev/badge/skills/olegvg/resume-tailor-plugin/onboarding.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 | $0.00036 | $0.00740 |
| Opus 5.5 | $0.00014 | $0.00296 |
| Sonnet 5.5 | $0.00007 | $0.00148 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
onboarding 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 14d 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 — 24 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Candidate Profile Onboarding
Build or update the requested career data store from supplied evidence. Preserve factual uncertainty and user preferences so later applications can select truthful, permitted claims. This skill stands alone; it does not require resume-tailor, a particular runtime, or export tooling. Tailoring or formatting alone does not trigger profile creation.
Read profile-contract.md before extracting or updating. It defines location, identity, sources, career facts, optional sections, visibility, durable preferences, scoped decisions and unresolved facts. Accept an existing schema rather than migrating it for compliance.
Extract before asking
- Resolve the target and scope. Use the explicitly supplied profile path first. Otherwise use an unambiguous established profile in the chosen workspace. New profiles default to
resume/<candidate-label>/master-profile.mdthere; honor a different requested path. A neutral collision-free file label is not a person's name. Keep candidate data out of installed plugin assets and caches. For an update, read the relevant existing profile before editing. - Read the supplied evidence. Extract supported identity, contacts, career chronology, employment capacity, contribution and outcomes into source-linked facts. Available read-only tools may read supplied files or URLs; if extraction fails, state what is missing and continue with readable material. Preserve source dates separately from employment/implementation dates. Do not search unrelated candidate records or private session history.
- Bind identity and qualify claims. Keep distinct candidates' extracts separate. If records may describe different people, ask which record/person is intended before merging or persisting; recency and an explicit filename do not resolve identity. Preserve measured versus estimated/target/test values, personal versus team/advisory/agent-assisted contribution, title, skills recency and approved public wording. Do not fill a missing name, month, metric, certificate or outcome by inference.
- Ask only consequential follow-ups. Review what extraction already answered. Clarify material identity, conflicts, missing truth, public-name/NDA permission or target-path ambiguity. Do not require a biography questionnaire, quantified achievements or a language/market pair. Sparse records can yield a useful profile with unknowns. A direct human correction becomes the current fact with its source; retain superseded context and any separate uncertainty it leaves unresolved.
- Preserve preference scope. Separate durable disclosure restrictions and established preferences from one-output/application decisions. Retain existing visibility/variant definitions. A one-PDF B2 description may narrow supported C1 but does not change the canonical level; no override establishes unsupported expertise. Do not treat role inclusion as platform publication visibility.
- Complete the requested artifact. For an authorized profile creation/update, write only supported facts, provenance and relevant restrictions/uncertainties. Preserve unrelated existing content and schema. A chat-only request stays in chat with no files or profile mutation. Neither task implies a resume, cover letter, export, application submission or platform update.
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.
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.
- 14d ago First seen · 24 lines · 36 tokens per session scan A b3ca124713f5
onboarding is a skill published in the GitHub repository olegvg/resume-tailor-plugin (47 stars, last pushed 13d ago), licensed MIT. It adds 36 tokens to every session and 740 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 2026-10-02.
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