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/alebgl77/claude-inc/profile-optimizernpx skills add alebgl77/claude-inc --skill profile-optimizergit clone --depth 1 https://github.com/alebgl77/claude-incWrote 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/alebgl77/claude-inc/profile-optimizer)<a href="https://agentmods.dev/skills/alebgl77/claude-inc/profile-optimizer"><img src="https://agentmods.dev/badge/skills/alebgl77/claude-inc/profile-optimizer.svg" alt="Measured on agentmods" 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 | $0.00106 | $0.01034 |
| Opus 5 | $0.00053 | $0.00517 |
| Sonnet 5 | $0.00021 | $0.00207 |
| Haiku 4.5 | $0.00011 | $0.00103 |
Grade A, and why
profile-optimizer 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 4d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile Optimizer — Profile Doctor
"Optimise your profile"
When to use
- A profile gets impressions but no follows, DMs, or inbound leads.
- "Roast my LinkedIn profile." / "Why does nobody message me?"
- "Rewrite my headline — I'm repositioning from freelancer to agency."
- Before an outbound or content push, when the profile has to convert the click.
- New role, new niche — and the profile still sells the old you.
Workflow
- Collect the raw material: current headline, About, banner description, featured items, pinned posts — plus who the profile must attract and the one action they should take (DM, follow, book a call).
- Diagnose. Score each element 1–5 against its actual job: headline (search + hook), banner (positioning billboard), About (hook, then proof), featured (path to the action). Name the single biggest leak in one sentence.
- Rewrite the headline on the formula who you help + outcome + proof — e.g. "I help B2B SaaS founders turn content into pipeline — $12M sourced in 2025." Deliver three options: safe, sharp, spicy.
- Rebuild the About: the first three lines are a hook that survives the fold, then scannable proof blocks (results, method, credibility), then exactly one CTA. First person, short paragraphs, zero third-person bio-speak.
- Write the banner brief: one message, a text overlay of seven words or fewer, where the proof element (logo, metric, artifact) sits, and colour guidance so the profile photo still pops against it.
- Pick three featured items that ladder to the goal — lead magnet, best-performing post, booking link — and rewrite each title as a promise, not a label.
- Keyword pass: weave the 3–5 terms the target audience actually searches into the headline, About, and experience titles. Natural placement only — no stuffing.
- Deliver a before/after for every element, plus a do-this-first list that fits in 20 minutes.
Output format
## Profile Audit: <name> — <platform>
Goal: <who it must attract → the one action they should take>
Biggest leak: <one sentence>
### Headline
BEFORE: <current>
AFTER (safe): <rewrite>
AFTER (sharp): <rewrite>
AFTER (spicy): <rewrite>
### About
BEFORE: <first three lines + one-line verdict>
AFTER: <full rewritten About, paste-ready>
### Banner brief
Message: <...> | Overlay: "<7 words max>" | Proof: <...> | Colour: <...>
### Featured (in this order)
1. <item> — <why it earns the slot>
2. <item> — <why>
3. <item> — <why>
### Keywords woven in
<term> → <headline | About | experience title>
### Do this first (20 minutes)
1. <step>
2. <step>
3. <step>
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.
- 4d ago First seen · 98 lines · 106 tokens per session scan A d2a5363ad469
profile-optimizer is a skill published in the GitHub repository alebgl77/claude-inc (14 stars, last pushed 2d ago), licensed MIT. It adds 106 tokens to every session and 1,034 once invoked, about $0.0005 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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