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 agentmods add skills/grcengineering/companion/profile-wizardnpx skills add grcengineering/companion --skill profile-wizardgit clone --depth 1 https://github.com/grcengineering/companionWhat 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 | $0.00055 | $0.00556 |
| Opus 5 | $0.00028 | $0.00278 |
| Sonnet 5 | $0.00011 | $0.00111 |
| Haiku 4.5 | $0.00006 | $0.00056 |
Grade A, and why
profile-wizard 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 3d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
profile-wizard
What
Build the learner profile, not the Companion brain. The Companion brain remains curated in brain/.
When
- The learner is new.
- The learner wants to import learning context.
- The Companion lacks enough context to calibrate teaching.
- A path, lab, or reading plan would be materially better with profile context.
Not For
- Re-checking an existing profile after several sessions. Use
profile-refresher. - Tracking concept state. Use
progress-tracker. - Inferring sensitive behavioural analytics.
Inputs
- Learner answers to the intake prompts.
profile/learner-profile.schema.json.- Optional example profile from
profile/examples/.
Steps
Ask seven voice-friendly prompts. Each answer should be short enough for a 30-60 second spoken response.
- Tell me about your role and what you actually do day to day.
- What's your environment: cloud, on-prem, regulated industry, headcount, team shape?
- What frameworks do you live with?
- Where do you feel stuck or like you're winging it?
- What do you wish you understood better?
- How do you learn best: reading, building, watching, conversation, teaching back?
- How much time can you spend on this in a typical week?
Then summarize what you heard and ask what is wrong or missing before using it.
Validation
- Output matches
profile/learner-profile.schema.json. - Sensitive identifiers are absent.
- The learner can accept, edit, or discard the profile.
Gotchas
- Do not ask for company names, customer names, secrets, live evidence, vendor names, or sensitive details.
- If the learner gives sensitive detail anyway, ask for an abstracted replacement.
- If only one missing profile field matters, ask that field instead of running full intake.
Failure Modes
- Over-collection: stop when teaching can be calibrated.
- Silent mutation: never update profile context without showing the change.
- Brain drift: never write learner facts into
brain/.
Examples
- New learner opens the Companion -> Ask the seven prompts, summarize, then produce a schema-shaped profile.
- Learner asks for a lab but gives no context -> Ask the minimum profile questions needed before
lab-builder. - Learner shares a company name -> Ask them to replace it with an industry and company-size description.
What ships with it
3 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.
- 3d ago First seen · 68 lines · 55 tokens per session scan A 935b50216aec
profile-wizard is a skill published in the GitHub repository grcengineering/companion (32 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 556 once invoked, about $0.0003 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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