Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add aksheyw/career-command-center-template/plugin install career-ccWrote 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/aksheyw/career-command-center-template/outreach)<a href="https://agentmods.dev/skills/aksheyw/career-command-center-template/outreach"><img src="https://agentmods.dev/badge/skills/aksheyw/career-command-center-template/outreach/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/aksheyw/career-command-center-template/outreach"><img src="https://agentmods.dev/badge/skills/aksheyw/career-command-center-template/outreach.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 | $0.00041 | $0.00506 |
| Opus 5 | $0.00020 | $0.00253 |
| Sonnet 5 | $0.00008 | $0.00101 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
outreach 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 9d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are generating outreach messages for the user's job search. The user has described the target contact or company.
STEP 1: Read the outreach templates
Read ${CLAUDE_PLUGIN_ROOT}/skills/resume-customizer/references/career-tools.md for the 6 outreach templates and personalization guidance. Read ${CLAUDE_PLUGIN_ROOT}/references/YOUR_PROFILE.md for the user's name, title, phone, LinkedIn, portfolio, and key achievements.
STEP 2: Identify the right template
Select based on the user's input:
| Situation | Template |
|---|---|
| Cold LinkedIn connection request | Template 1 (300 char limit) |
| LinkedIn InMail to hiring manager | Template 2 |
| Cold email to recruiter | Template 3 |
| WhatsApp / direct message to warm contact for referral | Template 4 |
| Following up after no response | Template 5 |
| Thank you after interview | Template 6 |
If the context is ambiguous, ask which situation applies before generating.
STEP 3: Personalize the message
Mandatory personalizations:
- Replace
[NAME]with the person's name if provided - Replace
[COMPANY]with the actual company name - Replace
[SPECIFIC]with something real about their work or company news if mentioned - Replace
[ROLE]with the actual role if known - For Template 2 (InMail): include a specific company challenge or product reference
- For Template 4 (warm DM): use first name only, keep casual tone
- Pull the user's name, title, scope, achievements, phone, and LinkedIn from
YOUR_PROFILE.md
Never use generic placeholders in the final output — fill them in or explicitly mark what the user needs to fill in manually before sending.
STEP 4: Output the message
Output the ready-to-send message clearly formatted, followed by:
- Channel: [where to send this]
- Length: [character / word count]
- What to customize before sending: [any remaining gaps]
- Follow-up timing: [when to follow up if no response]
For warm outreach, include phone from YOUR_PROFILE.md. For email / InMail, include LinkedIn from YOUR_PROFILE.md.
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.
- 9d ago First seen · 51 lines · 41 tokens per session scan A 29f1c0e3ab3d
outreach is a skill published in the GitHub repository aksheyw/career-command-center-template (1 stars, last pushed 11d ago), licensed MIT. It adds 41 tokens to every session and 506 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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