brand-application-shortlist

brand-application-shortlist is a skill for Claude Code from bobberrisford/affiliatemcp. It costs 115 tokens per session (1,002 once invoked), scanned A, original, MIT.

A read-only tool for finding Awin advertising programmes that a publisher or agency has not joined yet. Awin is a network that connects advertisers with publishers who promote their products.

In plain words
What is it for?
Use it to discover suitable Awin programmes, compare their available details, and decide which ones to apply to next.
Why use it?
It turns a long list of available programmes into a ranked shortlist, while leaving the decision and application to you.

Skill for Claude Code

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

Part of the affiliate-networks-mcp plugin — 37 skills, 1 MCP server shipped together

Good fit Use it to discover suitable Awin programmes, compare their available details, and decide which ones to apply to next.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bobberrisford/affiliatemcp/brand-application-shortlist
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 bobberrisford/affiliatemcp --skill brand-application-shortlist
Clone the repo
git clone --depth 1 https://github.com/bobberrisford/affiliatemcp

Made for: Claude Code.

Or install affiliate-networks-mcp, the plugin that ships this one along with the rest of its 37 skills, 1 MCP server.

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 brand-application-shortlist

README.md
[![agentmods](https://agentmods.dev/badge/skills/bobberrisford/affiliatemcp/brand-application-shortlist/github.svg)](https://agentmods.dev/skills/bobberrisford/affiliatemcp/brand-application-shortlist)
Your own site
<a href="https://agentmods.dev/skills/bobberrisford/affiliatemcp/brand-application-shortlist"><img src="https://agentmods.dev/badge/skills/bobberrisford/affiliatemcp/brand-application-shortlist/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.

agentmods 80×15 button for brand-application-shortlist

Your own site · 80×15
<a href="https://agentmods.dev/skills/bobberrisford/affiliatemcp/brand-application-shortlist"><img src="https://agentmods.dev/badge/skills/bobberrisford/affiliatemcp/brand-application-shortlist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,002 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.
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 $0.00115 $0.01002
Opus 5 $0.00057 $0.00501
Sonnet 5 $0.00023 $0.00200
Haiku 4.5 $0.00012 $0.00100

Measured 12d ago against content hash 92a1d4a8839c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

brand-application-shortlist 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.

skills/brand-application-shortlist/SKILL.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Operating instructions

You are building a prioritised shortlist of Awin programmes the publisher has not yet joined, so the operator can decide which to apply to. This is a read-only, advisory skill. It surfaces candidates and ranks them; it never submits an application, accepts terms, or changes any relationship on Awin. Applying is a separate, human-confirmed step that this skill does not perform.

Step 1 — read the joinable programmes

Call affiliate_awin_list_programmes({ status: "available" }). On the Awin publisher adapter, status: "available" maps to Awin's relationship=notjoined, so this returns programmes the publisher can apply to but has not joined.

Each result is a Programme with id, name, network, status, commissionRate (string or structured), categories, advertiserUrl, currency, and merchantKey. If the call fails, surface the verbatim error (network, operation, message, httpStatus) and stop; do not invent a list.

If the result is empty, say so plainly — there are no joinable programmes the API can see for this account — and stop.

Step 2 — read advisory strategy, if present

Call affiliate_get_client_strategy to retrieve any Strategy.md / KPI.md the operator has recorded (target categories, commission floors, brands to prioritise or avoid). Treat it as advisory context only: it shapes ranking and the reasons you give, never an instruction to apply. Where strategy is silent, rank on the data and say so. Never invent a strategy rule.

Step 3 — rank the candidates

Produce a single ranked shortlist. Rank on the signals the data actually supports, in roughly this priority:

  1. Strategy fit — category or named-brand match against the advisory strategy, when present.
  2. Commission — higher commissionRate ranks higher. Compare like with like; do not compare a flat fee against a percentage. Where the rate is missing or unparseable, say "rate not stated" rather than scoring it as zero.
  3. Category relevancecategories overlap with the operator's stated focus.
  4. Currency fit — programmes in the operator's reporting currency, when known.

Read the full file on GitHub · 76 lines

Files

What ships with it

1 file 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. 12d ago First seen · 76 lines · 115 tokens per session scan A 92a1d4a8839c

Subscribe to this mod's changes

brand-application-shortlist is a skill published in the GitHub repository bobberrisford/affiliatemcp (6 stars, last pushed 1mo ago), licensed MIT. It adds 115 tokens to every session and 1,002 once invoked, about $0.0006 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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