AWS Cost Operations
zxkane/aws-skills
AWS cost optimization, monitoring, and operational excellence expert.
Finds unused data in Axiom by analyzing query patterns, then deploys a cost dashboard and ingest monitors to keep spend under the contract limit.
Install Axiom Cost Control
$ npx skills add openclaw/clawhub --skill controlling-costs -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openclaw/clawhub controlling-costs --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/controlling-costs .claude/skills/controlling-costs && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .claude/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openclaw/clawhub --skill controlling-costs -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openclaw/clawhub controlling-costs --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/controlling-costs .agents/skills/controlling-costs && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .agents/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/clawhub --skill controlling-costs -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openclaw/clawhub controlling-costs --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/controlling-costs .cursor/skills/controlling-costs && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .cursor/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openclaw/clawhub.git --path .agents/skills/controlling-costs--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openclaw/clawhub --skill controlling-costs -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openclaw/clawhub controlling-costs --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/controlling-costs .gemini/skills/controlling-costs && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .gemini/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openclaw/clawhub controlling-costsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openclaw/clawhub --skill controlling-costs -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/controlling-costs .github/skills/controlling-costs && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .github/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/clawhub --skill controlling-costs -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openclaw/clawhub controlling-costs --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/clawhub.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/controlling-costs .opencode/skills/controlling-costs && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "controlling-costs" agent skill from https://github.com/openclaw/clawhub/tree/main/.agents/skills/controlling-costs into .opencode/skills/controlling-costs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "controlling-costs", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
controlling-costs- GitHub stars
- 9.5k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 615 words
- Files
- 15 (incl. scripts)
- Skills in repo
- 56
- Repo updated
- First seen
- Licence
- MIT
At a glance
Finds unused data in Axiom by analyzing query patterns, then deploys a cost dashboard and ingest monitors to keep spend under the contract limit.
- Works in 5 steps: Check Existing Setup → Discovery → Dashboard → …
- Reducing Axiom costs by finding unused columns or field values
- SKILL.md covers Before You Start, Which Phases to Run, Phase 0: Check Existing Setup and Phase 1: Discovery, plus 5 more sections
- Runs Shell scripts from its folder; calls jq
What it does
The agent starts by loading the axiom-sre and building-dashboards skills, finding the audit dataset (axiom-audit first, checking that it holds usageCalculated events), and confirming that axiom-history is readable, which the optimization phase needs. It also asks you for the deployment name, the audit dataset name and your contract limit in TB per day, which the monitors require.
Work then runs in phases. Phase 0 looks for an existing cost dashboard and compares it to templates/dashboard.json for drift. Phase 1 runs scripts/baseline-stats to capture daily ingest stats and build an analysis queue. Phase 2 deploys a dashboard of ingest trends, burn rate, projections, waste candidates and top users. Phase 3 lists notifiers, asks which one should receive cost alerts and creates monitors. Phase 4 uses the queue to find unused columns and field values.
Which phases run depends on the request: reducing costs or finding waste runs phases 0, 1 and 4, full setup runs 0 to 3, and a drift check runs 0 alone. Scripts take -h for usage, must not be piped to head or tail, and require jq.
When your agent uses it
- Reducing Axiom costs by finding unused columns or field values
- Tracking ingest spend with trends, burn rate and projections on a dashboard
- Creating monitors that alert as ingest approaches the contract limit
- Checking an existing cost dashboard for drift from the template
Example prompts
- “Find waste in our Axiom data and tell me which columns nobody queries.”
- “Set up cost control for our Axiom deployment with a dashboard and monitors.”
- “Check whether our Axiom cost dashboard has drifted from the template.”
Requirements
- An Axiom deployment with an audit dataset and axiom-history access
- The axiom-sre and building-dashboards skills
- jq
- Your contract limit in TB per day, for the monitors
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c23e34a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 9 files in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
jq
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Axiom Cost Control loads about 1.7k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 615 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from openclaw/clawhub at commit c23e34a, republished under its MIT licence (© openclaw). 615 words, ~1,687 tokens.
Download SKILL.mdSave it as
.claude/skills/controlling-costs/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.- name
- controlling-costs
- description
- Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.
Axiom Cost Control
Dashboards, monitors, and waste identification for Axiom usage optimization.
Before You Start
Load required skills:
skill: axiom-sre skill: building-dashboardsBuilding-dashboards provides:
dashboard-list,dashboard-get,dashboard-create,dashboard-update,dashboard-deleteFind the audit dataset. Try
axiom-auditfirst:apl ['axiom-audit'] | where _time > ago(1h) | summarize count() by action | where action in ('usageCalculated', 'runAPLQueryCost')- If not found → ask user. Common names:
axiom-audit-logs-view,audit-logs - If found but no
usageCalculatedevents → wrong dataset, ask user
- If not found → ask user. Common names:
Verify
axiom-historyaccess (required for Phase 4):apl ['axiom-history'] | where _time > ago(1h) | take 1If not found, Phase 4 optimization will not work.
Confirm with user:
- Deployment name?
- Audit dataset name?
- Contract limit in TB/day? (required for Phase 3 monitors)
Replace
<deployment>and<audit-dataset>in all commands below.
Tips:
- Run any script with
-hfor full usage - Do NOT pipe script output to
headortail— causes SIGPIPE errors - Requires
jqfor JSON parsing - Use axiom-sre's
axiom-queryfor ad-hoc APL, not direct CLI
Which Phases to Run
| User request | Run these phases |
|---|---|
| "reduce costs" / "find waste" | 0 → 1 → 4 |
| "set up cost control" | 0 → 1 → 2 → 3 |
| "deploy dashboard" | 0 → 2 |
| "create monitors" | 0 → 3 |
| "check for drift" | 0 only |
Phase 0: Check Existing Setup
# Existing dashboard?
dashboard-list <deployment> | grep -i cost
# Existing monitors?
axiom-api <deployment> GET "/v2/monitors" | jq -r '.[] | select(.name | startswith("Cost Control:")) | "\(.id)\t\(.name)"'If found, fetch with dashboard-get and compare to templates/dashboard.json for drift.
Phase 1: Discovery
scripts/baseline-stats -d <deployment> -a <audit-dataset>Captures daily ingest stats and produces the Analysis Queue (needed for Phase 4).
Phase 2: Dashboard
scripts/deploy-dashboard -d <deployment> -a <audit-dataset>Creates dashboard with: ingest trends, burn rate, projections, waste candidates, top users. See reference/dashboard-panels.md for details.
Phase 3: Monitors
Contract is required. You must have the contract limit from preflight step 4.
Step 1: List available notifiers
scripts/list-notifiers -d <deployment>Present the list to the user and ask which notifier they want for cost alerts.
If they don't want notifications, proceed without -n.
Step 2: Create monitors
scripts/create-monitors -d <deployment> -a <audit-dataset> -c <contract_tb> [-n <notifier_id>]Creates 3 monitors:
- Total Ingest Guard — alerts when daily ingest >1.2x contract OR 7-day avg grows >15% vs baseline
- Per-Dataset Spike — robust z-score detection, alerts per dataset with attribution
- Query Cost Spike — hardened z-score with 30d baseline, 5d exclusion gap, persistence-based gating (median_z > 3, p25_z > 2.5)
The spike monitors use notifyByGroup: true so each dataset triggers a separate alert.
See reference/monitor-strategy.md for threshold derivation.
Phase 4: Optimization
Show full SKILL.md (277 more words)Show less
Get the Analysis Queue
Run scripts/baseline-stats if not already done. It outputs a prioritized list:
| Priority | Meaning |
|---|---|
| P0⛔ | Top 3 by ingest OR >10% of total — MANDATORY |
| P1 | Never queried — strong drop candidate |
| P2 | Rarely queried (Work/GB < 100) — likely waste |
Work/GB = query cost (GB·ms) / ingest (GB). Lower = less value from data.
Analyze datasets in order
Work top-to-bottom. For each dataset:
Step 1: Column analysis
scripts/analyze-query-coverage -d <deployment> -D <dataset> -a <audit-dataset>If 0 queries → recommend DROP, move to next.
Step 2: Field value analysis
Pick a field from suggested list (usually app, service, or kubernetes.labels.app):
scripts/analyze-query-coverage -d <deployment> -D <dataset> -a <audit-dataset> -f <field>Note values with high volume but never queried (⚠️ markers).
Step 3: Handle empty values
If (empty) has >5% volume, you MUST drill down with alternative field (e.g., kubernetes.namespace_name).
Step 4: Record recommendation
For each dataset, note: name, ingest volume, Work/GB, top unqueried values, action (DROP/SAMPLE/KEEP), estimated savings.
Done when
All P0⛔ and P1 datasets analyzed. Then compile report using reference/analysis-report-template.md.
Cleanup
# Delete monitors
axiom-api <deployment> GET "/v2/monitors" | jq -r '.[] | select(.name | startswith("Cost Control:")) | "\(.id)\t\(.name)"'
axiom-api <deployment> DELETE "/v2/monitors/<id>"
# Delete dashboard
dashboard-list <deployment> | grep -i cost
dashboard-delete <deployment> <id>Note: Running create-monitors twice creates duplicates. Delete existing monitors first if re-deploying.
Reference
Audit Dataset Fields
| Field | Description |
|---|---|
action | usageCalculated or runAPLQueryCost |
properties.hourly_ingest_bytes | Hourly ingest in bytes |
properties.hourly_billable_query_gbms | Hourly query cost |
properties.dataset | Dataset name |
resource.id | Org ID |
actor.email | User email |
Common Fields for Value Analysis
| Dataset type | Primary field | Alternatives |
|---|---|---|
| Kubernetes logs | kubernetes.labels.app | kubernetes.namespace_name, kubernetes.container_name |
| Application logs | app or service | level, logger, component |
| Infrastructure | host | region, instance |
| Traces | service.name | span.kind, http.route |
Units & Conversions
- Scripts use TB/day
- Dashboard filter uses GB/month
| Contract | TB/day | GB/month |
|---|---|---|
| 5 PB/month | 167 | 5,000,000 |
| 10 PB/month | 333 | 10,000,000 |
| 15 PB/month | 500 | 15,000,000 |
Optimization Actions
| Signal | Action |
|---|---|
| Work/GB = 0 | Drop or stop ingesting |
| High-volume unqueried values | Sample or reduce log level |
| Empty values from system namespaces | Filter at ingest or accept |
| WoW spike | Check recent deploys |
© openclaw, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 14 other files (scripts) in .agents/skills/controlling-costs of openclaw/clawhub.
- SKILL.md
- README.md
- reference/analysis-report-template.md
- reference/dashboard-panels.md
- reference/monitor-strategy.md
- scripts/analyze-query-coverage
- scripts/baseline-stats
- scripts/create-monitors
- scripts/deploy-dashboard
- scripts/lib/ast-parser.jq
- scripts/lib/format-bytes.sh
- scripts/list-notifiers
- scripts/setup
- scripts/test-ast-parser
- templates/dashboard.json
Open the folder on GitHubat commit c23e34a
Compare with similar skills
Axiom Cost Control next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Axiom Cost Control this skillopenclaw/clawhub | 9.5k | — | ~1.7k | Automated safety check: Pass | MIT | |
| AWS Cost Operationszxkane/aws-skills | 367 | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Cost Managementgrafana/skills | 279 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| AWS Cost OperationsMicrock/ordinary-claude-skills | 403 | 1 repos | ~2.5k | Automated safety check: Pass | Custom licence | |
| Prometheus Missing Data Troubleshootingprometheus/prometheus-mcp | 118 | — | ~587 | Automated safety check: Pass | Apache-2.0 | |
| Vercel Optimize Auditvercel-labs/agent-skills | 32k | 9 repos | ~4.3k | Automated safety check: Pass | None |
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Related
Categories
Questions about Axiom Cost Control
What does Axiom Cost Control do?
Finds unused data in Axiom by analyzing query patterns, then deploys a cost dashboard and ingest monitors to keep spend under the contract limit. The agent starts by loading the axiom-sre and building-dashboards skills, finding the audit dataset (axiom-audit first, checking that it holds usageCalculated events), and confirming that axiom-history is readable, which the optimization phase needs. It also asks you for the deployment name, the audit dataset name and your contract limit in TB per day, which the monitors require.
When should I use Axiom Cost Control?
Axiom Cost Control fits situations like: reducing Axiom costs by finding unused columns or field values; tracking ingest spend with trends, burn rate and projections on a dashboard; creating monitors that alert as ingest approaches the contract limit; checking an existing cost dashboard for drift from the template.
How do I install Axiom Cost Control in Claude Code?
Run `npx skills add openclaw/clawhub --skill controlling-costs -a claude-code`. Or copy the skill folder (.agents/skills/controlling-costs in openclaw/clawhub) into .claude/skills/controlling-costs in your project. Claude Code loads it when a task matches its description.
How do I install Axiom Cost Control in Codex?
Run `npx skills add openclaw/clawhub --skill controlling-costs -a codex`. Or copy the skill folder (.agents/skills/controlling-costs in openclaw/clawhub) into .agents/skills/controlling-costs in your project. Codex loads it when a task matches its description.
Can I use Axiom Cost Control in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openclaw/clawhub --skill controlling-costs -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/controlling-costs, .gemini/skills/controlling-costs, .github/skills/controlling-costs and .opencode/skills/controlling-costs in your project.
What does Axiom Cost Control need to run?
Going by SKILL.md and its folder, Axiom Cost Control needs a shell for the scripts in its folder and the command-line tools its instructions call (jq). Our summary lists: An Axiom deployment with an audit dataset and axiom-history access; The axiom-sre and building-dashboards skills; jq; Your contract limit in TB per day, for the monitors.
Does Axiom Cost Control access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Axiom Cost Control safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Axiom Cost Control use?
Axiom Cost Control is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Axiom Cost Control use?
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Axiom Cost Control?
Skills that share tags, products or a category with Axiom Cost Control: AWS Cost Operations (zxkane/aws-skills, 367 stars), Cost Management (grafana/skills, 279 stars), AWS Cost Operations (Microck/ordinary-claude-skills, 403 stars) and Prometheus Missing Data Troubleshooting (prometheus/prometheus-mcp, 118 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Axiom Cost Control?
openclaw (a GitHub organization) maintains it in openclaw/clawhub, which has 9,495 GitHub stars. The repository holds 56 skills in this directory. The repository was last updated on October 7, 2026.
Source: openclaw/clawhub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.