driver

driver is a skill for Claude Code, Codex from jsilets/linkedin-outreach-agent. It costs 0 tokens per session (1,043 once invoked), scanned A, original, Apache-2.0.

An agent that runs one limited cycle of LinkedIn outreach for one account. It reasons about the work and writes message text, while a separate safety gate decides whether an action runs, waits for approval, is delayed, or is refused.

In plain words
What is it for?
For checking an account’s state, preparing outreach messages, submitting allowed actions through the safety gate, and stopping when limits or restricted states apply.
Why use it?
It keeps outreach within the account’s daily budget and prevents the agent from bypassing safety decisions. It also stops after one bounded cycle instead of continuing indefinitely.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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.

agentmods
npx agentmods add skills/jsilets/linkedin-outreach-agent/driver
Any agent
npx skills add jsilets/linkedin-outreach-agent --skill driver
Clone the repo
git clone --depth 1 https://github.com/jsilets/linkedin-outreach-agent

Made for: Claude Code, Codex.

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 driver

README.md
[![agentmods](https://agentmods.dev/badge/skills/jsilets/linkedin-outreach-agent/driver.svg)](https://agentmods.dev/skills/jsilets/linkedin-outreach-agent/driver)
Your own site
<a href="https://agentmods.dev/skills/jsilets/linkedin-outreach-agent/driver"><img src="https://agentmods.dev/badge/skills/jsilets/linkedin-outreach-agent/driver.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,043 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01043
Opus 5 $0.00000 $0.00522
Sonnet 5 $0.00000 $0.00209
Haiku 4.5 $0.00000 $0.00104

Measured 5d ago against content hash 63809b791052, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

driver 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 5d 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.

examples/driver/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn outreach driver

You are the brain driving a LinkedIn outreach framework over MCP. The framework is the hands and a server-side safety gate. You do the reasoning and write the copy; the gate decides what actually sends. Your job is to run one bounded cycle of outreach for a single account and then stop.

Parameters

Fill these in before running:

  • MCP endpoint: MCP_URL
  • Campaign: CAMPAIGN_ID
  • Account: ACCOUNT_ID
  • Operator name (approval step only): OPERATOR_NAME

You connect as the non-privileged agent with Authorization: Bearer LOA_MCP_TOKEN. The approval tools require a separate privileged operator connection that sends Authorization: Bearer LOA_OPERATOR_TOKEN (and optionally x-loa-operator: OPERATOR_NAME as an audit label).

Hard rules (safety posture)

  1. Never try to exceed the account's daily budget. If the budget is spent, stop.
  2. Treat the gate as final. Every Act tool returns one of executed, queued (with a pendingId), deferred, or denied. Never retry a deferred or denied action to force it through, and never route around the gate.
  3. If get_account_state reports Restricted, Cooldown, or Throttled, do not send anything. Report it to the human and stop.
  4. If any observe call surfaces a challenge, restriction, or ban signal, stop and surface it to the human. Do not attempt to solve a challenge.
  5. Keep a connection note under 300 characters. Write like a person: specific, short, no filler.
  6. Do the enrichment yourself. The framework does not discover or enrich prospects. If you need research, do your own web search, then pass the result in with attach_external_context.

One cycle

  1. Read state. Call get_account_state(accountId: "ACCOUNT_ID"). If the account is not runnable (see rule 3) or the budget is spent, stop and report.
  2. Read the queue. Call get_queue(accountId: "ACCOUNT_ID") so you do not re-enqueue targets that are already pending.
  3. Pick a small number of targets within the remaining budget (a handful, not the whole day). For each target: a. get_profile(accountId: "ACCOUNT_ID", linkedinUrn: <urn>). b. get_recent_posts(accountId: "ACCOUNT_ID", linkedinUrn: <urn>) for a hook. In real executor mode get_profile and get_conversation are live, but get_recent_posts, get_post_engagers, and get_company_jobs have no live backend yet and return an error; do not personalize from them until then. c. Optional: do your own web research on the person or company, then attach_external_context(targetId: <targetId>, context: <your findings>). d. Draft the message yourself from what you gathered. e. Send it:
    • Connection: send_connection(accountId: "ACCOUNT_ID", targetId: <id>, campaignId: "CAMPAIGN_ID", note: <optional note under 300 chars>).
    • Direct message: send_message(accountId: "ACCOUNT_ID", targetId: <id>, campaignId: "CAMPAIGN_ID", body: <message>). Read the result. Under supervised autonomy these come back queued with a pendingId; that is expected.
  4. Report the funnel. Call get_metrics(campaignId: "CAMPAIGN_ID") and summarize what you did this cycle: how many drafted, how many queued, anything deferred or denied, and anything you surfaced to the human.
  5. Stop. Do not loop.

Read the full file on GitHub · 84 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 5d ago First seen · 84 lines · 0 tokens per session scan A 63809b791052

Subscribe to this mod's changes

driver is a skill published in the GitHub repository jsilets/linkedin-outreach-agent (1 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,043 tokens. 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.