draft-outreach

draft-outreach is a skill for Claude Code from tmargolis/career-navigator. It costs 73 tokens per session (1,405 once invoked), scanned A, original, Apache-2.0.

A writing tool that creates ready-to-send messages for LinkedIn, email, or LinkedIn InMail, based on your goal and available contact context.

In plain words
What is it for?
Use it to contact recruiters, hiring managers, peers, or other professional connections, including first messages and follow-ups.
Why use it?
It helps you write relevant outreach without guessing about previous conversations. When available, it uses email and calendar history for messages to a known person.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the career-navigator plugin — 46 skills, 3 MCP servers shipped together

Good fit Use it to contact recruiters, hiring managers, peers, or other professional connections, including first messages and follow-ups.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tmargolis/career-navigator/draft-outreach
Install

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.

Any agent
npx skills add tmargolis/career-navigator --skill draft-outreach
Clone the repo
git clone --depth 1 https://github.com/tmargolis/career-navigator

Made for: Claude Code.

Or install career-navigator, the plugin that ships this one along with the rest of its 46 skills, 3 MCP servers.

Wrote 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.

agentmods badge for draft-outreach

README.md
[![agentmods](https://agentmods.dev/badge/skills/tmargolis/career-navigator/draft-outreach.svg)](https://agentmods.dev/skills/tmargolis/career-navigator/draft-outreach)
Your own site
<a href="https://agentmods.dev/skills/tmargolis/career-navigator/draft-outreach"><img src="https://agentmods.dev/badge/skills/tmargolis/career-navigator/draft-outreach.svg" alt="Measured on agentmods" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,405 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00073 $0.01405
Opus 5 $0.00036 $0.00702
Sonnet 5 $0.00015 $0.00281
Haiku 4.5 $0.00007 $0.00140

Measured 8d ago against content hash 676cf34b8e09, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

draft-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 8d 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.

skills/draft-outreach/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Invoke writer in draft-outreach mode.

Invocation

  • Use the exact agent name writer. Retry once with the same name if invocation fails.

Workflow

Application data uses the split layout defined in references/tracker-schema.md — read it before any read or write.

  1. Prior communication history (enrichment — default for named recipients): Outreach to a specific person or known contact at a company should be grounded in real mail/calendar context when the host allows—not guesswork.

    1. If a ContactContextBrief is already in chat → use it as-is (full block to writer).
    2. Else if Gmail/M365 inbox and/or calendar tools appear in this session → run contact-context end-to-end before invoking writer, unless the user explicitly says to skip history (“no prior thread,” “brand-new contact,” “template only”) or the ask is purely generic with no named recipient yet. Do not invent threads.
    3. Else (no mail/calendar tools in session) → still invoke writer, but pass a single line: Prior communication: not retrieved — inbox/calendar tools not available in this session; do not imply prior email or meetings.

    If the user says they sent mail but the address was wrong or search is empty, follow contact-context “User said they sent”; email_address_notes carries address candidates. Include calendar_notes, upcoming_meetings, and warm_networking in the handoff when present—if upcoming_meetings is non-empty, outreach should not read as a cold first touch.

  2. Read {user_dir}/CareerNavigator/profile.md and {user_dir}/CareerNavigator/voice-profile.md (create stub if missing).

  3. Voice preflight: If voice-profile.md has no user-pasted block under ## User writing samples or ## User writing samples (launch) (substantive excerpts), ask before invoking writer: paste 2–5 LinkedIn posts or short professional writing; mention optional launch voice harvest (résumé/CV/cover text from disk); user may reply skip (low voice match). If they paste, append a dated ## User writing samples section. If samples already exist, skip this ask.

  4. From conversation, capture: channel, recipient archetype (title/company if known), objective (info chat, referral check-in, post-event ping), and any StrategistHandoff, ContactContextBrief, or facts the user pasted.

  5. Pass a structured brief to writer in draft-outreach mode. Required: include the full ## ContactContextBrief markdown block when available, or the Prior communication: fallback from step 0. writer must thread summary, open_loops, hooks_for_writer, calendar_notes, upcoming_meetings, and warm_networking into the draft when present—see agents/writer/AGENT.md. Do not draft final copy in this skill—delegate.

  6. Present writer output (variants if offered). Remind: connectors support warm threading when available.

  7. Sent confirmation + auto-track: After presenting the copy, say:

    "Let me know when you've sent this and I'll log it to your tracker."

Read the full file on GitHub · 54 lines

Changes

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.

  1. 8d ago First seen · 54 lines · 73 tokens per session scan A 676cf34b8e09

Subscribe to this mod's changes

draft-outreach is a skill published in the GitHub repository tmargolis/career-navigator (13 stars, last pushed 9d ago), licensed Apache-2.0. It adds 73 tokens to every session and 1,405 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens