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.
npx skills add bobberrisford/affiliatemcp --skill earnings-rollupgit clone --depth 1 https://github.com/bobberrisford/affiliatemcpWrote 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.
[](https://agentmods.dev/skills/bobberrisford/affiliatemcp/earnings-rollup)<a href="https://agentmods.dev/skills/bobberrisford/affiliatemcp/earnings-rollup"><img src="https://agentmods.dev/badge/skills/bobberrisford/affiliatemcp/earnings-rollup/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.
<a href="https://agentmods.dev/skills/bobberrisford/affiliatemcp/earnings-rollup"><img src="https://agentmods.dev/badge/skills/bobberrisford/affiliatemcp/earnings-rollup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00124 | $0.01491 |
| Opus 5 | $0.00062 | $0.00745 |
| Sonnet 5 | $0.00025 | $0.00298 |
| Haiku 4.5 | $0.00012 | $0.00149 |
Grade A, and why
earnings-rollup 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Premium scope note
The free affiliate-earnings-report skill already produces the single-period
consolidated view: total earnings, by-network and by-programme breakdown, the
status split, and an unpaid-age flag. Run that skill first for a single
period's numbers; this premium skill does not repeat it.
This premium skill adds three things the free report does not do:
- Multi-period trend (typically the last six months), so the user sees the earnings shape over time rather than one window.
- Concentration/diversification analysis: what share of total earnings comes from the top one, three, and five programmes, with a plain diversification-risk flag when concentration is high.
- Payment-timing analysis: per network, the typical time from
dateConvertedtodateApprovedand fromdateApprovedtodatePaid, computed from the transaction rows, used to give a rough forecast for when currently-pending or currently-approved commission is likely to be paid. This is a pattern observed in past data, not a promise from the network.
Assumptions and requirements
- Publisher-side networks only.
- Credentials for networks in scope are configured; recommend
affiliate-networks-mcp doctor <slug>when credential state is uncertain. - Payment-timing analysis needs enough paid history to be meaningful (a handful of paid transactions per network at minimum). Where a network has too little paid history, state that rather than forecasting from one or two data points.
- This skill never invents a payment date. A forecast is stated as a range derived from past typical timing, not a guarantee.
Step 1 — identify networks
Use publisher networks the user named or confirmed configured. Call
affiliate_list_networks only to confirm a registered adapter exists per
named network. Recommend affiliate-networks-mcp doctor <slug> when
credential state is uncertain rather than assuming.
Step 2 — pull the multi-period trend
For each network s, call the earnings summary once per of the last six
complete months:
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.
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.
- 12d ago First seen · 138 lines · 124 tokens per session scan A ddeee1c39dac
earnings-rollup is a skill published in the GitHub repository bobberrisford/affiliatemcp (6 stars, last pushed 1mo ago), licensed MIT. It adds 124 tokens to every session and 1,491 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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