Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/galiprandi/job-seekernpx agentmods add skills/galiprandi/job-seeker/profileWrote 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/galiprandi/job-seeker/profile)<a href="https://agentmods.dev/skills/galiprandi/job-seeker/profile"><img src="https://agentmods.dev/badge/skills/galiprandi/job-seeker/profile/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/galiprandi/job-seeker/profile"><img src="https://agentmods.dev/badge/skills/galiprandi/job-seeker/profile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 145 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 223 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00025 | $0.03014 |
| Opus 5.5 | $0.00010 | $0.01206 |
| Sonnet 5.5 | $0.00005 | $0.00603 |
| Haiku 4.5 | $0.00003 | $0.00301 |
Grade A, and why
profile 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile
Pre-flight
- Load active preferences (see
memoryskill):node scripts/db.js "SELECT category, key, value, confidence, source FROM preferences WHERE user_id = <user_id> AND status = 'active' ORDER BY category, key" - Load existing profile if present:
node scripts/db.js "SELECT data->'profile' AS profile, data->'job_preferences' AS job_preferences, data->'style_profile' AS style_profile FROM users WHERE id = <user_id>" - If profile exists, validate changes before overwriting
Flow overview
Step 1: CV analysis → extract experience, sector, profile, inferred seniority
Step 2: Gap questionnaire → only what the CV doesn't clarify (adaptive to inferred profile)
Step 3: Current situation + expectations → employment status, urgency, salary, work mode, availability
Step 4: Strategy → targets, sources, aggressiveness (informed by everything above)
Step 5: Polish suggestion → align CV and LinkedIn profile to the job target to maximize matches
Step 1: CV analysis
Ask user for CV (URL or PDF). Extract:
- Full name and title/profession
- Professional summary (elevator pitch)
- Work experience (company, role, period, achievements, team size, reporting line if applicable)
- Core competencies and tools (tech stack, software, methodologies, equipment, whatever is relevant to the field)
- Soft skills (leadership, communication, etc.)
- Certifications and courses
- Education (degrees, institutions)
- Languages and proficiency level
- Quantifiable achievements (metrics, impact)
- Notable projects or relevant work samples
Step 1b: Inferred profile
From the CV data, infer:
| Signal from CV | Inferred field | Used for |
|---|---|---|
| Years of experience, previous roles | career_stage (intern, junior, mid, senior, staff, principal, director+) |
Which questionnaire blocks to show, seniority filtering |
| Team size managed, titles with Lead/Manager/Head | has_management (bool) |
Whether to show management-related questions |
| Core competencies and tools | core_skills |
Step 2 gap questions on skill preferences |
| Industries of previous employers | industry_history |
Step 2 gap questions on industry preferences |
| Company sizes (startup vs corporate) | company_size_history |
Step 2 gap questions on company size |
| Sector or functional area | sector |
Step 2 gap questions, platform tiering |
| Languages and publications/conferences | visibility_level |
Outreach tone, referral strategy |
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 Changed 985ec9121324
- 1mo ago First seen · 244 lines · 25 tokens per session scan A 637aef872e76
profile is a skill published in the GitHub repository galiprandi/job-seeker (58 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 3,014 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 skills, from other repositories
ai-dev-jobs-mcp
Search indexed AI and ML jobs, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP.
Cold Email Writer
Write personalized cold outreach emails to hiring managers and founders - specific, human, not a pitch deck.
resume-tailor
Use when the user has a specific job posting and wants to customize their resume, CV, work document, and/or cover letter for that role. Also use when they say "I'm applying to..." or share a job link.
vitaecontext-wiki-maintenance
Maintainer-only skill for refreshing VitaeContext wiki knowledge from official sources. Use only from a local repository clone when a maintainer asks to refresh one module, audit all module wiki entries, or audit module source lists.
claim-check
Use when the user wants a final truth pass before submitting a resume, CV, cover letter, LinkedIn section, or application package. Also use when they ask whether a draft contains unsupported, inflated, or hallucinated claims.
resume-builder
Use when the user wants to create or update a source work document in resume or CV format, or create a source cover letter from scratch. Triggers on US resumes ("build my resume") and UK/EU-style work CVs ("build my CV", "I need a CV for a UK role", "European CV"). US academic CVs are out of scope. For first-time…