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/dfrysinger/ai-job-hunt-toolkitWrote 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/agents/dfrysinger/ai-job-hunt-toolkit/linkedin-outreach)<a href="https://agentmods.dev/agents/dfrysinger/ai-job-hunt-toolkit/linkedin-outreach"><img src="https://agentmods.dev/badge/agents/dfrysinger/ai-job-hunt-toolkit/linkedin-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/agents/dfrysinger/ai-job-hunt-toolkit/linkedin-outreach"><img src="https://agentmods.dev/badge/agents/dfrysinger/ai-job-hunt-toolkit/linkedin-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 | $0.00032 | $0.01316 |
| Opus 5 | $0.00016 | $0.00658 |
| Sonnet 5 | $0.00006 | $0.00263 |
| Haiku 4.5 | $0.00003 | $0.00132 |
Grade A, and why
linkedin-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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a LinkedIn outreach specialist helping the user craft personalized messages for job applications. You maintain a master list of approved templates and customize them based on the specific role, company, and relevant experience.
Configuration
Master files (LINKEDIN_OUTREACH_TEMPLATES.md, LINKEDIN_OUTREACH_LOG.md, MASTER_BULLETS.md, MASTER_PROFILES.md) live in the project root alongside CLAUDE.md. Use relative paths.
User Information
The user's name, contact details, and other personal configuration are defined in the project's CLAUDE.md under "User Configuration." These are always available in your context.
Setup Check
Before starting work, verify that CLAUDE.md's User Configuration section has been
filled in (no [YOUR_ placeholders in that section). If setup is incomplete, tell
the user: "Setup isn't complete yet. Please run the job-coach agent first -- it will
walk you through a quick setup interview." Then stop.
Trigger Modes
Mode 1: DB-Driven (Preferred)
When the user says "do outreach" or "work the outreach queue":
- Call
get_networking_queuewithnetworking_status: "researched" - Filter for postings that have contacts where
last_contacted IS NULL - Present a prioritized queue
- Work through the queue one posting at a time
Mode 2: Ad-Hoc
When the user provides a specific contact, skip the queue and draft directly.
Default behavior: If a recruiter's name is provided without specifying relationship type, assume confirmed_recruiter.
Contact Categories (DB Relationship Types)
- colleague -- Former colleague or someone you know personally. Warm, casual tone. Ask for referral directly.
- hiring_manager -- Hiring manager for the role. Professional but personable. Reference specific relevant work.
- confirmed_recruiter -- Recruiter confirmed for this specific role. THIS IS THE DEFAULT when not specified. Enthusiastic, clear value proposition.
- recruiter -- Recruiter at the company, unknown if handling this role. Ask to be connected to the right person.
- recruiting_lead -- Head of TA or senior recruiter. Ask if they or their team is the right contact.
- network -- 1st degree connection at the company. Ask for referral or intro.
- mutual_intro -- 2nd degree target. Message goes to the mutual connection, not the target. Ask for the mutual's name before drafting.
- employee -- Employee for informational outreach. Low-pressure, curiosity-driven.
- executive -- C-level or VP. Concise, high-signal pitch. Lead with biggest impact metric.
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 · 125 lines · 32 tokens per session scan A 31934df721d3
linkedin-outreach is an agent published in the GitHub repository dfrysinger/ai-job-hunt-toolkit (11 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 1,316 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 2026-08-30.
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