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 stan-rym/liam-linkedin-ads-MCP --skill liam-spendgit clone --depth 1 https://github.com/stan-rym/liam-linkedin-ads-MCPWrote 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/stan-rym/liam-linkedin-ads-mcp/liam-spend)<a href="https://agentmods.dev/skills/stan-rym/liam-linkedin-ads-mcp/liam-spend"><img src="https://agentmods.dev/badge/skills/stan-rym/liam-linkedin-ads-mcp/liam-spend/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/stan-rym/liam-linkedin-ads-mcp/liam-spend"><img src="https://agentmods.dev/badge/skills/stan-rym/liam-linkedin-ads-mcp/liam-spend.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 | $0.00070 | $0.00830 |
| Opus 5 | $0.00035 | $0.00415 |
| Sonnet 5 | $0.00014 | $0.00166 |
| Haiku 4.5 | $0.00007 | $0.00083 |
Grade A, and why
liam-spend 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Liam: spend analysis
Answer one question: is the money going where the results are? Produce a verdict and moves, never a raw table dump.
How to reach Liam
Prefer the liam MCP tools if they are loaded (list_campaigns, get_performance,
performance_summary, performance_trend). Otherwise use the CLI: liam <command>,
or node <liam-repo>/packages/cli/dist/index.js <command> if not globally linked.
CLI report presets: last_7_days, last_30_days, last_90_days, month_to_date,
last_month. For custom windows use the MCP tools with explicit startDate/endDate
(YYYY-MM-DD). Everything here is read-only.
What to pull
Default period is last_30_days unless the user names one.
performance_summaryfor the account rollup: total spend, conversions, flags.get_performanceatcampaign_grouplevel, thencampaignlevel, thencreativelevel. Spend, impressions, clicks, conversions per row.performance_trend(weekly) at account or top-group level for pacing.list_campaignsfor the structure: names, statuses, and which entities are ACTIVE but absent from reporting (active with zero delivery is itself a finding).
How to analyze
Compute the account average cost per conversion first; it is the yardstick for waste.
- Total and direction. Total spend for the period and the delta vs the prior
equivalent period (from the trend, or a second
get_performancewindow). - Concentration. Share of spend per campaign group. Flag when one group takes more than ~60% of spend; say whether its share of conversions justifies it.
- Efficiency map. For each group and campaign: spend, conversions, cost per conversion, and share-of-spend vs share-of-conversions. The interesting rows are the ones where those two shares diverge.
- Wasted spend. Entities with zero conversions whose spend exceeds ~2x the account average cost per conversion. Sum this into one "wasted this period" dollar figure; it is usually the headline. Also flag CPC outliers above ~1.5x the account average and CTR below ~0.3% on meaningful volume.
- Pacing. From the weekly trend: is daily spend accelerating or decaying? Note anything that looks like a campaign silently dying (delivery falling week over week with unchanged status).
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 · 66 lines · 70 tokens per session scan A 1cf0fee75916
liam-spend is a skill published in the GitHub repository stan-rym/liam-linkedin-ads-MCP (22 stars, last pushed 1mo ago), licensed MIT. It adds 70 tokens to every session and 830 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.
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