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 agentmods add skills/cloudchef/atlasclaw-providers/cost-optimizationnpx skills add CloudChef/atlasclaw-providers --skill cost-optimizationgit clone --depth 1 https://github.com/CloudChef/atlasclaw-providersWrote 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/cloudchef/atlasclaw-providers/cost-optimization)<a href="https://agentmods.dev/skills/cloudchef/atlasclaw-providers/cost-optimization"><img src="https://agentmods.dev/badge/skills/cloudchef/atlasclaw-providers/cost-optimization.svg" alt="Measured on agentmods" 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 | $0.00076 | $0.02170 |
| Opus 5 | $0.00038 | $0.01085 |
| Sonnet 5 | $0.00015 | $0.00434 |
| Haiku 4.5 | $0.00008 | $0.00217 |
Grade A, and why
cost-optimization 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 5d 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 — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cost-optimization
Use this skill to work through cost optimization recommendations from discovery to remediation tracking.
Handlers and helpers
scripts/adapter.py contains all five Tool handlers for listing, analysis,
execution, and tracking. scripts/_cost_object_actions.py remains separate
because the embedded assistant Context resolver calls it to build resource
actions; it is not a one-command forwarding script.
Workflow
Choose the entry path that matches the user's object:
- Analyze an existing recommendation:
- Call
smartcmp_list_cost_recommendations - Optionally request related policy counts
- Call
smartcmp_analyze_cost_recommendation - Let SmartCMP Provider resolve the related
resourceId - Merge normalized resource
type + propertiesinto the analysis facts - Returns multi-dimensional recommendations (P0/P1/P2 priority)
- Includes risk assessment and best practice guidance
- Shows saving contribution, policy history, and resource operational context
- Call
- Analyze a resource directly:
- Call
smartcmp_analyze_resource_costwith an exact visible name or recent list#selection - Read resource facts, enabled applicable policy configurations, latest resource executions, and active violations without triggering policy execution
- Use the returned
analysisContractto keep platform facts separate fromllm_potential - Read references/RESOURCE_ANALYSIS.md for VM, AWS RDS, and generic resource reasoning rules
- Call
- Call
smartcmp_execute_cost_optimizationfor native day2 repair only after the user explicitly requests it - Track remediation state with
smartcmp_track_cost_optimization
Analysis Output Enhancement
smartcmp_analyze_cost_recommendation provides:
- P0 Primary Action: Provider recommendation (remediate / configure_platform_policy / manual_review)
- P1 Risk Assessment: Risk level (high/medium/low) with specific warnings
- P1 Configuration Guide: When fixType is missing, explains how to configure day2 repair
- P1 Saving Priority: Contribution percentage to global optimizable amount
- P2 Policy History: Compliance rate trend and violation recurrence count
- Resource Context: Resource type, component type, status, OS, and normalized datasource facts
What ships with it
4 files 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.
- 5d ago First seen · 236 lines · 76 tokens per session scan A b8df26b99c17
cost-optimization is a skill published in the GitHub repository CloudChef/atlasclaw-providers (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 76 tokens to every session and 2,170 once invoked, about $0.0004 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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