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 bjorn-ingmanson/thefroject-plugins --skill build-my-profilegit clone --depth 1 https://github.com/bjorn-ingmanson/thefroject-pluginsWrote 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/bjorn-ingmanson/thefroject-plugins/build-my-profile)<a href="https://agentmods.dev/skills/bjorn-ingmanson/thefroject-plugins/build-my-profile"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/build-my-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/bjorn-ingmanson/thefroject-plugins/build-my-profile"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/build-my-profile.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 | $0.00046 | $0.00947 |
| Opus 5 | $0.00023 | $0.00474 |
| Sonnet 5 | $0.00009 | $0.00189 |
| Haiku 4.5 | $0.00005 | $0.00095 |
Grade A, and why
build-my-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 12d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build My Profile
Create a personal profile that helps Claude understand how the user works, writes, and communicates. This profile persists across sessions and makes every interaction more relevant.
What you're building
Three files in context/:
working-style.md— how the user approaches tasks, iterates, gives instructions, and makes decisionswriting-style.md— tone, structure, vocabulary, formatting preferences, and patternsprofile.md— a compact summary (200-500 words) suitable for Claude's User Preferences
Where to find the data
Pull from every connected source available. The more data, the better the profile.
Slack (if MCP connected):
- Read the user's recent messages across channels (last 30-60 days)
- Look at how they give instructions, ask questions, respond to requests
- Note tone differences between channels (casual in general chat, structured in planning)
- Identify recurring phrases, sign-offs, formatting habits
Gmail (if MCP connected):
- Read sent emails from the last 30-60 days
- Analyze greeting style, paragraph length, closing style
- Note differences by recipient type (internal vs external, up vs down the org chart)
- Identify what they write themselves vs what they forward or delegate
Notion (if MCP connected):
- Read pages the user has authored or recently edited
- Look at how they structure documents: headings, lists, tables, free text
- Note vocabulary and terminology preferences
- Identify what kinds of documents they create most often
If no sources are connected:
- Ask the user directly. Use a conversational interview, not a questionnaire.
- Ask for 3-5 examples of writing they're proud of (emails, posts, docs, anything)
- Ask about their role, daily workflow, and what "good output" looks like to them
- Build the profile from their answers and examples
How to build each file
working-style.md
Analyze how the user works, not what they work on.
Look for:
- How they start tasks (jump in vs plan first, brief vs detailed instructions)
- How they iterate (small tweaks vs big rewrites, how many rounds)
- How they give feedback (direct vs diplomatic, specific vs general)
- How they make decisions (data-driven vs intuition, fast vs deliberate)
- What they delegate vs do themselves
- Patterns in how they ask for help (full context upfront vs progressive disclosure)
- Common frustrations or corrections they make repeatedly
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.
- 12d ago First seen · 101 lines · 46 tokens per session scan A fdaf7a5f79d4
build-my-profile is a skill published in the GitHub repository bjorn-ingmanson/thefroject-plugins (1 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 947 once invoked, about $0.0002 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 2026-08-31.
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