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 shivamsriva31093/gcp-ironclad --skill gcp-spend-guardrailsgit clone --depth 1 https://github.com/shivamsriva31093/gcp-ironcladWrote 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/shivamsriva31093/gcp-ironclad/gcp-spend-guardrails)<a href="https://agentmods.dev/skills/shivamsriva31093/gcp-ironclad/gcp-spend-guardrails"><img src="https://agentmods.dev/badge/skills/shivamsriva31093/gcp-ironclad/gcp-spend-guardrails/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/shivamsriva31093/gcp-ironclad/gcp-spend-guardrails"><img src="https://agentmods.dev/badge/skills/shivamsriva31093/gcp-ironclad/gcp-spend-guardrails.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 | $0.00095 | $0.02054 |
| Opus 5 | $0.00048 | $0.01027 |
| Sonnet 5 | $0.00019 | $0.00411 |
| Haiku 4.5 | $0.00010 | $0.00205 |
Grade A, and why
gcp-spend-guardrails 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST \ How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GCP Spend Guardrails (APPLY)
Overview
Per project, applies three blast-radius controls — but only when each is genuinely safe per the safety matrix in docs/superpowers/specs/2026-05-24-gcp-api-key-ironclad-skill-design.md §6. Actions that fail the safety gate are demoted to "flag for review" and surfaced for the human, never auto-applied.
When to Use
- Triggered by
gcp-ironcladas Phase 3a, after the read-only audits. - Or invoked standalone when you want only the spend-control half of the suite.
Inputs
SESSION_DIRenv var (must already containaudit.jsonandanomalies.jsonfrom prior phases when invoked by the driver).DRY_RUNenv var: if1, plan all actions but apply none. Default0.QUOTA_FLOOR_PER_DAYenv var: minimum daily request quota for Gemini API. Default5000.QUOTA_MULTIPLIERenv var: peak-multiplier for quota sizing. Default5.
Outputs
Writes ${SESSION_DIR}/guardrails-applied.json matching output.schema.json.
Safety matrix (excerpt)
| Action | Auto-apply ONLY when | Demoted to "flag" when |
|---|---|---|
| Set Gemini API quota | API enabled + ≥7d usage + proposed > peak | No usage data; new project (<7d); export missing |
| Quota sizing | max(peak_30d × 5, 5000/day) |
Peak shows abuse signature → use floor only |
| Create budget alerts | caller is billing.admin + no existing budget at threshold |
viewer-only; budget already configured |
| Recommend spend-cap budget | never auto-applied — console-only (no gcloud/API surface as of July 2026), and pausing a live service is a human call | always flagged, never applied |
| Disable idle API | zero 30-d usage + enabled >7d + not sys-* |
any usage in 30d; enabled <7d; system project |
Execution
Action 1 — Quota on generativelanguage.googleapis.com
For each project where generativelanguage.googleapis.com is enabled:
- Read peak daily request count from the last 30 days via Monitoring API (same metric as the audit). If <7 days of data → skip with reason
"insufficient_usage_data". - Compute
target = max(peak * QUOTA_MULTIPLIER, QUOTA_FLOOR_PER_DAY). - Anti-abuse guard: if peak is itself a known abuse signature (e.g., the project appears in
anomalies.jsonwithmultipleOver > 100), useQUOTA_FLOOR_PER_DAYinstead ofpeak * QUOTA_MULTIPLIER. - Compare against current quota; if equal → outcome
"skipped"with reason"already_at_target". - Otherwise (and not
DRY_RUN), apply via:
Rollback (record ingcloud alpha services quota update \ --consumer="projects/${P}" \ --service="generativelanguage.googleapis.com" \ --metric="generativelanguage.googleapis.com/generate_content_paid_requests" \ --unit="1/d/{project}" \ --override-value="${target}" \ --forcedetails.rollback):gcloud alpha services quota update --consumer=projects/${P} --service=generativelanguage.googleapis.com --metric=... --unit=... --override-value=<previous> - If
gcloud alpha services quota updateis unavailable (alpha-surface drift), fall back to the REST API:curl -X POST \ -H "Authorization: Bearer $(gcloud auth application-default print-access-token)" \ -H "Content-Type: application/json" \ "https://serviceusage.googleapis.com/v1beta1/projects/${P}/services/generativelanguage.googleapis.com/consumerQuotaMetrics/.../limits/.../consumerOverrides" \ -d "{\"overrideValue\":\"${target}\"}"
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 · 128 lines · 95 tokens per session scan A ac74973384c9
gcp-spend-guardrails is a skill published in the GitHub repository shivamsriva31093/gcp-ironclad (24 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,054 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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