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 TelivityAI/careerops --skill skillgit clone --depth 1 https://github.com/TelivityAI/careeropsWrote 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/telivityai/careerops/skill)<a href="https://agentmods.dev/skills/telivityai/careerops/skill"><img src="https://agentmods.dev/badge/skills/telivityai/careerops/skill/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/telivityai/careerops/skill"><img src="https://agentmods.dev/badge/skills/telivityai/careerops/skill.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 | $0.00044 | $0.00847 |
| Opus 5.5 | $0.00018 | $0.00339 |
| Sonnet 5.5 | $0.00009 | $0.00169 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
careerops 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.
This is a copy
100% identical to careerops — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CareerOps skill
Career OS — operate on the user's board pack (exported JSON from the CareerOps web app) or their self-hosted Supabase project.
Doctrine (non-negotiable)
- No invented facts — employers, titles, dates, metrics, and skills must come from the user's materials / bullet memory / portfolio.
- No auto-apply / no auto-send — drafts are copy/paste only; the human submits on the employer site and sends their own mail.
- Tags ≠ stage moves — Apply / Stretch / Skip are suggestions until the user acts.
- Memory provenance —
body_originalis immutable; AI polish requires Accept; promotion is bidirectional (source_type/source_id↔ accomplishment links). resume_structis canonical — promotion and portfolio promote go through one atomic write that syncsresume_text(never silent dual-write divergence).- Generate retrieval — checked → role-linked → relevance → recency tie-break only (not newest-20).
- Enrichment = inbox + Accept — GitHub/LinkedIn (and similar) proposals land as candidates; never silent scrape into resume.
- Deferred forever (unless doctrine changes) — auto-apply, auto-send, silent scrape into resume, invented salary bands, ungated multi-agent writes of experience without accept.
See docs/DOCTRINE_MEMORY.md and docs/ROADMAP.md in the CareerOps repo.
Modes
| Mode | Purpose |
|---|---|
scan |
Review sourced roles; flag blocklist, age, remote, duplicates |
evaluate |
Build a decision pack (summary, risks, suggested call) |
rank |
Order roles by fit signals without applying |
tailor |
Draft resume/cover from checked / ranked materials only |
interview |
Prep angles + story-bank prompts (roadmap: durable interview events) |
followup |
Draft follow-up / thank-you notes (never send) |
outcome |
Record offer/reject notes (roadmap: structured offer fields via pack) |
advise |
Structured career advisor brief — materials-only past; labeled market judgment |
What ships with it
8 files 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.
- 1mo ago First seen · 62 lines · 44 tokens per session scan A 6350f51c0459
careerops is a skill published in the GitHub repository TelivityAI/careerops (50 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 847 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to careerops, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
evidence-miner
Harvest real, citable achievements from the user's git history, PRs, and work documents, and turn the confirmed ones into STAR stories. Use when the user wants to mine their repos or work artifacts for accomplishments, can't remember what they achieved, or wants to build their story bank from evidence instead of…
job-search
Find current job postings matching the user's profile, using public job-board search endpoints and web search. Use when the user wants to find jobs, search for openings, scrape job boards, or asks "any new positions?". Zero dependencies; degrades honestly to building search URLs when boards block fetching.
ats-detective
Work out which Applicant Tracking System a company uses, then apply that vendor's specific CV rules (keyword strategy, date format, file type, layout). Use when the user asks which ATS a company runs, how to beat a specific ATS, or before tailoring a CV for a named company. Zero dependencies; degrades honestly to…
ruthless-cv-optimizer
Rewrite a CV/resume against a specific job description with zero fluff, zero fabrication, and ATS-safe output. Use when the user wants to optimize, tailor, rewrite, or "roast" their CV or resume for a job, or asks to improve resume bullets. Runs in two phases and MUST pause for user answers between them.
linkedin-360brew-planner
Plan and draft LinkedIn posts optimized for 360Brew, LinkedIn's decoder-based ranking model. Use when the user wants LinkedIn post ideas, a content plan, a post draft, or asks why their LinkedIn posts get no reach. Grounds every post in the user's real stories and enforces the 2026 ranking rules (saves over likes, no…
mock-interviewer
Run a realistic, pressure-tested mock interview for a specific role, one question at a time, with honest feedback at the end. Use when the user wants interview practice, a mock interview, or to rehearse answers for an upcoming interview.