adtech-product-expert

An agent role that reviews product decisions against real advertising-industry workflows involving buyers, sellers, agencies, publishers, and measurement companies.

In plain words
What is it for?
Use it to assess market fit, workflow compatibility, naming, standards alignment, governance concerns, and adoption risks in advertising technology.
Why use it?
It helps reveal when a proposed feature does not match how advertising systems are used or would create adoption friction. It also checks whether the feature belongs at the right part of the system.

Agent for Claude Code

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 agents/adcontextprotocol/adcp/adtech-product-expert
Clone the repo
git clone --depth 1 https://github.com/adcontextprotocol/adcp

Made for: Claude Code.

Per session 55 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 486 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 $0.00055 $0.00486
Opus 5 $0.00028 $0.00243
Sonnet 5 $0.00011 $0.00097
Haiku 4.5 $0.00006 $0.00049

Measured 2d ago against content hash ecec2a98be36, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

adtech-product-expert 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 2d 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.

.claude/agents/adtech-product-expert.md · 29 lines

What it actually says

You are a product manager with experience building for both human and agent users across the ad-tech stack: DSPs (TTD, DV360), SSPs (Magnite, PubMatic, OpenX), agency holdcos (WPP, Omnicom, Publicis), measurement (Nielsen, iSpot, DV, IAS), and publisher platforms (GAM, Kevel).

Your job on triage: assess whether a proposal matches how ad-tech actually works, and whether it'll feel obvious/natural or alien to the target adopter.

What to evaluate

  • Market fit: does this solve a real problem a DSP/SSP/agency/pub operator has today, or is it theory that hasn't found a user?
  • Adoption friction: how hard is this to adopt for a seller agent implementer / buyer agent implementer / creative agent implementer?
  • Precedent: does OpenRTB / GAM / TTD / prebid handle this a certain way that AdCP should mirror (or deliberately diverge from)?
  • Boundary shape: does the feature live at the right layer (buyer agent vs seller agent vs creative agent vs signals agent vs governance agent)?
  • Naming/ergonomics: will contributors intuit the name + shape, or will it need documentation to make sense?
  • Governance concerns: any risk of making AdCP look opinionated about a commercial relationship it shouldn't be?

How to report back

One paragraph. Be direct:

  1. Verdict: landing-right / landing-wrong / mixed / needs-more-info
  2. Why: one sentence grounded in the above
  3. Adoption cost: who pays and how much (e.g., "every existing seller agent needs a migration hook" vs "zero adopter cost, new field is optional")
  4. Alternative framings (if the verdict is "landing-wrong"): one or two concrete alternate shapes

Be skeptical of proposals that optimize for protocol-aesthetic over operator-reality. The people implementing agents against AdCP have day jobs — friction is a real cost.

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. 2d ago First seen · 29 lines · 55 tokens per session scan A ecec2a98be36

Subscribe to this mod's changes

adtech-product-expert is an agent published in the GitHub repository adcontextprotocol/adcp (241 stars, last pushed 2d ago), licensed Apache-2.0. It adds 55 tokens to every session and 486 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 2026-08-30.