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.
git clone --depth 1 https://github.com/squerne/open-career-skillsWrote 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/commands/squerne/open-career-skills/setup)<a href="https://agentmods.dev/commands/squerne/open-career-skills/setup"><img src="https://agentmods.dev/badge/commands/squerne/open-career-skills/setup/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/commands/squerne/open-career-skills/setup"><img src="https://agentmods.dev/badge/commands/squerne/open-career-skills/setup.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 | $0.00014 | $0.00355 |
| Opus 5.5 | $0.00006 | $0.00142 |
| Sonnet 5.5 | $0.00003 | $0.00071 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
setup 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.
What it actually says
Set up the user's career profile at profile/profile.md.
First step, always: if profile/profile.md does not exist yet, copy profile/profile.template.md to profile/profile.md. The copy is git-ignored by design; never write personal data into the template itself, and never remove the profile/*.md rules from .gitignore.
Offer the user three paths and follow the one they pick:
- Paste a CV: they paste their CV text (or point you at a file in
documents/if they created one); you extract roles, dates, scope, metrics, skills, and education into the template structure. Preserve every number and named entity exactly; do not embellish or infer seniority. - Guided interview: ask one question at a time (current/target role, last 3 roles with 2-3 concrete outcomes each, top skills, target job and location, salary context if they want it stored). Stop after each question and wait.
- Both: paste first, then interview only for the gaps.
Then write the completed profile/profile.md. Show the user a short summary of what you recorded (not the full file) and remind them: this file is the memory of the workspace; every skill (ruthless-cv-optimizer, star-story-extractor, linkedin-360brew-planner, cover-letter-writer, mock-interviewer) reads it, and it is git-ignored so it stays out of any public fork.
If they mentioned any story-worthy achievement during setup, suggest running /extract-story on it next.
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 · 17 lines · 14 tokens per session scan A fb84d2705b61
setup is a command published in the GitHub repository squerne/open-career-skills (26 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 355 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 commands, from other repositories
instinct-import
Import instincts from external sources.
learn
Extract patterns and learnings from current session.
mempalace-status
Show the current state of your memory palace — wings, rooms, drawer counts, and suggestions.
ingest
Ingest source material into an active wiki. Accepts URLs, file paths, PDFs, freeform text, or processes the inbox. Supports tweets via Grok MCP.
rem_help
Each section is printed verbatim by --help for the command it names. The agreed design is issue #1656; change a page there and here together.
memory
Read-side memory operations on the knowledge graph: search past decisions and patterns, load session context, view decision timelines, render Mermaid graph visualizations. Subcommands: search, load, history, viz, status. Use when finding or reviewing what memory already holds. For storing new knowledge instead, invoke…