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 aaronjmars/aeon-agent --skill spend-watchgit clone --depth 1 https://github.com/aaronjmars/aeon-agentWrote 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/aaronjmars/aeon-agent/spend-watch)<a href="https://agentmods.dev/skills/aaronjmars/aeon-agent/spend-watch"><img src="https://agentmods.dev/badge/skills/aaronjmars/aeon-agent/spend-watch/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/aaronjmars/aeon-agent/spend-watch"><img src="https://agentmods.dev/badge/skills/aaronjmars/aeon-agent/spend-watch.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 | $0.00079 | $0.06609 |
| Opus 5 | $0.00039 | $0.03305 |
| Sonnet 5 | $0.00016 | $0.01322 |
| Haiku 4.5 | $0.00008 | $0.00661 |
Grade A, and why
spend-watch scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **actions** adapter uses the `gh` CLI / `gh api`, authenticated by the workflow's `GH_TOKEN` (`GH_GLOBAL`); it works in-run with no curl fallback. Do **not** route it through `./secretcurl` — `GH_GLOBAL` ends in `_GLOB This is a copy
100% identical to spend-watch — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Today is ${today}.
${var} — scope selector + optional arm flag.
- empty /
all→ sweep every platform whose secret is present, emit one combined digest.neon|vercel|railway|actions→ run one adapter only.- prepend
arm:(e.g.arm:neon,arm:actions) → authorize the adapter's safe write levers for this run. Withoutarm:the skill is read-only: it recommends, never mutates.dry-runappended anywhere → build the digest but do not./notify(for testing).Runs unattended — treat
${var}as final, no confirmation step, except a delete/mutation always re-reads the target's current state before acting (see each adapter's arm rules).
This skill is a cost analyst, not a bill alarm. Each run answers, per platform:
- Attribution — what is consuming the most? Rank drivers by dollars (or the resource unit that maps to dollars), down to the specific object: service, branch, route, RPC method, workflow. Top-N with each line's % share.
- Root cause — why is that line expensive?
- Recommendation — a ranked action list, each carrying: the concrete lever, an effort/risk tag, whether it's armable now, and a saving in real dollars ONLY when the platform's billing API returns real dollars (Railway
currentUsage, Actions overage). Everywhere else there is no dollar figure — the line carries its real signal instead (idle-awake %, % over the included allowance, cache-miss rate, stale-preview count, failure rate). Never invent a$X/mo.
Dollars-only-when-real is the core rule. A fabricated "$5/mo" is worse than the true signal "idle-awake 71%". Rank each recommendation by: real-$ saving first (when known), then signal magnitude × how actionable it is (armable > 1-click > code-change > investigate). The recommendation is the deliverable; the signal justifies it; the dollar is a bonus only when the API hands it over.
Across platforms (all): a roll-up — the real spend where billing exposes it (Railway $, Actions $), the biggest signal-ranked driver anywhere, and the top actions fleet-wide. No synthetic grand total.
The monitoring (deltas, real budgets, signal thresholds) is the trend context and the trigger; the deliverable is the ranked recommendations.
Shared setup (every run)
- Read
memory/MEMORY.mdfor context andmemory/spend-config.mdfor real-$ budgets, signal thresholds, and ignore-lists (see the config schema at the bottom). Ifspend-config.mdis missing, run with the built-in defaults and noteNO_CONFIGin the log — recommendations still work; they rank by signal regardless. - Read the last 7 days of
memory/logs/— used to detect newly expensive drivers vs ongoing, and to avoid repeat-nagging a recommendation already sent. - Parse
${var}:
RAW="$(printf '%s' "${var}" | tr '[:upper:]' '[:lower:]' | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')"
ARM=0; case "$RAW" in arm:*) ARM=1; RAW="${RAW#arm:}";; esac
DRYRUN=0; case "$RAW" in *dry-run*) DRYRUN=1; RAW="$(printf '%s' "$RAW" | sed 's/dry-run//g' | tr -s ' ')";; esac
RAW="$(printf '%s' "$RAW" | sed -e 's/^[[:space:]]*//' -e 's/[[:space:]]*$//')"
case "$RAW" in
""|all) SCOPE=all ;;
neon|vercel|railway|actions) SCOPE="$RAW" ;;
*) SCOPE=all ;; # unrecognized -> full sweep, note it in the log
esac
- Run the matching adapter(s). Each adapter self-skips if its secret is absent — log
<platform>: SKIP no-secretand continue. Inallmode, run every adapter whose secret is present, then run the Synthesis section.
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.
- 3d ago First seen · 346 lines · 79 tokens per session scan A ce4530d9b615
spend-watch is a skill published in the GitHub repository aaronjmars/aeon-agent (11 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 6,609 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to spend-watch, differing in 0 lines, and is treated as a copy.
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