liam-linkedin-ads-MCP: Instructions file for Codex

AGENTS.md

liam-linkedin-ads-MCP AGENTS.md is an instructions file for Codex, OpenCode from stan-rym/liam-linkedin-ads-MCP. It costs 3,292 tokens per session, scanned A, original, MIT.

Repository-specific guidance for a TypeScript monorepo, meaning one code repository containing several related packages and applications. It describes a LinkedIn advertising MCP server, command-line tool, and web application.

In plain words
What is it for?
Working on the Liam LinkedIn advertising system, including its REST client, MCP tools, command-line interface, web route, targeting, conversions, and Salesforce reader.
Why use it?
It helps contributors place changes in the correct package and follow the project’s architecture, authentication, and development conventions.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is stan-rym/liam-linkedin-ads-MCP's own configuration. It tells Codex and OpenCode how to work on liam-linkedin-ads-MCP itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything liam-linkedin-ads-MCP configures →

Reuse

Borrowing it

Nothing to install: this file belongs to stan-rym/liam-linkedin-ads-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/stan-rym/liam-linkedin-ads-MCP/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/stan-rym/liam-linkedin-ads-MCP

Made for: Codex, OpenCode.

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Per session 3,292 This file is loaded in full into every session.
When invoked 3,292 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.03292 $0.03292
Opus 5.5 $0.01317 $0.01317
Sonnet 5.5 $0.00658 $0.00658
Haiku 4.5 $0.00329 $0.00329

Measured 1mo ago against content hash 8751970bd297, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

liam-linkedin-ads-MCP AGENTS.md 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 1mo 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.

AGENTS.md · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Guidance for AI agents and contributors working in this repo. Liam is an MCP server and CLI that creates ad campaigns on LinkedIn and Google Ads. Read this before changing code.

Architecture

pnpm + TypeScript monorepo:

  • packages/shared — the platform-neutral layer: OAuth flow, credential stores, retry policy, the change journal and its lift windowing, named reporting periods, and the KPI math every platform shares. Anything here must be true of both platforms; anything true of only one belongs in that platform's package.
  • packages/core — the LinkedIn engine. No UI. Owns the LinkedIn REST client, every resource module, audience hashing, targeting, conversions, and the Salesforce reader.
  • packages/google — the Google Ads engine. Same shape as core: config and auth, one HTTP chokepoint, thin typed resource modules over GAQL, zod schemas reused as MCP inputs.
  • packages/mcp — MCP server. src/tools.ts (LinkedIn) and src/googleTools.ts (gads_*) are shared by the stdio entry (src/index.ts) and the hosted Vercel route.
  • packages/cli — the liam CLI (commander). LinkedIn at the top level, Google under liam google ... (src/google.ts).
  • apps/web — Next.js app hosting the MCP over HTTP at /api/mcp (Vercel). Two tenants: the env-credential tenant gated by a MCP_AUTH_TOKEN bearer, and bring-your-own credentials callers who send X-Liads-* headers (client id/secret + refresh token, optional account id/version) that the route activates per request via withRequestCredentials (core/config.ts, AsyncLocalStorage).

Data flow: every tool/command builds a client via createLiads() (core/client.ts), which loads config + an auto-refreshing token provider, then calls a resource module. Resource modules are thin typed wrappers over LinkedInClient.request().

Conventions

  • Nothing is ever created live. On LinkedIn, campaigns, campaign groups, and creatives default to DRAFT/intendedStatus: DRAFT. On Google, which has no draft status, campaigns, ad groups, and ads are created PAUSED and the schemas cannot express any other status. Never change either default. Activation is a separate, explicit, human step, and there is deliberately no tool for it on either platform.
  • zod schemas are the source of truth. All tool/command inputs live as zod schemas in core/src/schemas.ts and are reused as MCP tool input schemas (Schema.shape). Add or change a field there first, then thread it through the resource module.
  • Secrets never enter the repo. Local credentials live in ~/.liads/ (LinkedIn: config.json + credentials.json; Google: google.json + google-credentials.json, all mode 0600). Hosted credentials are LIADS_* / GADS_* env vars, or per-request X-Liads-* headers for bring-your-own-credentials callers. The config layer resolves request context first, then env, then files. Never log header credentials.
  • The hosted MCP does not expose the Google tools, and must not start doing so. That endpoint is multi-tenant over per-request LinkedIn credentials while Google credentials would come from shared server env vars, so exposing them would let any caller operate the server's Google Ads account. registerTools(server, { google: false }) in the web route.
  • Internal names are frozen. The package scope @liads/*, the ~/.liads dir, and the LIADS_* env prefix are intentionally NOT renamed to "liam" (renaming breaks stored creds and the deployed Vercel env). The brand "Liam" is visible-surface only. Google config shares ~/.liads for the same reason, and because the change journal at its root already spans both platforms.
  • Match the surrounding code style. Keep comments at the existing density. No em dashes in user-facing strings.

Read the full file on GitHub · 185 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. 1mo ago Changed · +80 lines · +1,589 tokens per session 8751970bd297
  2. 1mo ago First seen · 105 lines · 1,703 tokens per session scan A 9db3185df9ed

Subscribe to this mod's changes

liam-linkedin-ads-MCP AGENTS.md is an instructions file published in the GitHub repository stan-rym/liam-linkedin-ads-MCP (23 stars, last pushed 1mo ago), licensed MIT. It adds 3,292 tokens to every session, about $0.0132 per session on Opus 5.5. 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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