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 landedjobs/ai-job-hunt-os --skill cold-outreach-writergit clone --depth 1 https://github.com/landedjobs/ai-job-hunt-osWrote 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/landedjobs/ai-job-hunt-os/cold-outreach-writer)<a href="https://agentmods.dev/skills/landedjobs/ai-job-hunt-os/cold-outreach-writer"><img src="https://agentmods.dev/badge/skills/landedjobs/ai-job-hunt-os/cold-outreach-writer/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/landedjobs/ai-job-hunt-os/cold-outreach-writer"><img src="https://agentmods.dev/badge/skills/landedjobs/ai-job-hunt-os/cold-outreach-writer.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 | $0.00052 | $0.00944 |
| Opus 5 | $0.00026 | $0.00472 |
| Sonnet 5 | $0.00010 | $0.00189 |
| Haiku 4.5 | $0.00005 | $0.00094 |
Grade A, and why
cold-outreach-writer 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Outreach Writer
Write messages that busy people can answer, and set honest expectations about the odds. Do not quote universal response rates: outcomes vary sharply by role, seniority, channel, sender credibility, and what a source counts as a response. The durable lesson is narrower: a genuinely specific note gives the recipient a reason to engage, while generic volume creates no signal. Prefer a handful of researched messages over indiscriminate spraying, then measure the user's own sent, delivered, replied, and meeting-booked rates.
What you need
- Who to reach (name/role, or "help me pick the right person at company X").
- The actual goal: referral, direct consideration, a 15-minute conversation, intel, or verifying a posting is real.
- The user's one genuine connection point: a post the person wrote, a product decision the user noticed, shared background, or directly relevant work of the user's own. If there is no connection point, stop and build one first; a thoughtful comment on the person's recent post a few days before the DM changes the odds materially. A message with no specific hook is spam regardless of wording.
Picking the target (when asked)
The likely hiring manager beats the recruiter: recruiters run process, managers feel the pain of the unfilled seat. An engineer on the team is the best referral path. Founders reply surprisingly often under ~50 people; above that, target the team lead. Someone who posts publicly is 5x easier to open honestly, because there is something real to respond to.
Message anatomy (every message, every channel)
- Specific connection first: their post, their product, the exact problem their team is hiring for. Never open with the user's name and title; the reader does not care yet.
- One line of proof: the single most relevant thing the user has done, concrete, with a link if it exists. "Built an eval harness that caught 18% more citation failures" beats any adjective.
- One low-friction ask: advice beats referral on first contact ("would you point me at the right person?" / "worth 12 minutes?"). Never "any opportunities?" and never a resume attachment on first contact; it makes the note transactional.
- 50-75 words total. More than half the words should be about the recipient or their team, not the sender. On X, under 50 words.
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 · 46 lines · 52 tokens per session scan A 22028d525007
cold-outreach-writer is a skill published in the GitHub repository landedjobs/ai-job-hunt-os (1 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 944 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 2026-08-31.
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