analyze-costs — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited analyze-costs (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Analyze cloud costs and identify savings using Harness Cloud Cost Management (CCM) via MCP.
Call MCP tool: harness_get
Parameters:
resource_type: "cost_account_overview"Returns total spend, provider breakdown, and trend vs previous period.
Call MCP tool: harness_get
Parameters:
resource_type: "cost_breakdown"Multi-dimensional breakdown by service, environment, team, region.
Call MCP tool: harness_list
Parameters:
resource_type: "cost_perspective"Then get detailed data for a specific perspective:
Call MCP tool: harness_get
Parameters:
resource_type: "cost_perspective"
resource_id: "<perspective_id>"Call MCP tool: harness_get
Parameters:
resource_type: "cost_timeseries"Call MCP tool: harness_list
Parameters:
resource_type: "cost_recommendation"For detailed recommendation info:
Call MCP tool: harness_get
Parameters:
resource_type: "cost_recommendation_detail"
resource_id: "<recommendation_id>"Summary statistics:
Call MCP tool: harness_get
Parameters:
resource_type: "cost_recommendation_stats"Call MCP tool: harness_list
Parameters:
resource_type: "cost_anomaly"To dismiss a known anomaly:
Call MCP tool: harness_execute
Parameters:
resource_type: "cost_anomaly"
action: "report_feedback"
resource_id: "<anomaly_id>"
body: { feedback: "FALSE_ANOMALY" } # or TRUE_ANOMALY / NOT_RESPONDEDCall MCP tool: harness_get
Parameters:
resource_type: "cost_commitment"## Cloud Cost Analysis
**Period:** Last 30 Days
### Summary
| Provider | Spend | vs Previous |
|----------|-------|-------------|
| AWS | $X | +X% |
| GCP | $X | +X% |
| Azure | $X | -X% |
### Top Recommendations
1. **Rightsize <resource>** - Save $X/month (95% confidence)
2. **Convert to Reserved** - Save $X/month
3. **Delete unused resources** - Save $X/month
### Anomalies
- <date>: <service> spiked $X above expected
### Actions
- [ ] Rightsize instance X
- [ ] Purchase reserved capacity
- [ ] Clean up unused volumes| Resource Type | Operations | Description |
|---|---|---|
cost_account_overview | get | Account-level total spend summary |
cost_summary | get | Perspective-scoped cost summary |
cost_timeseries | get | Cost trends over time |
cost_breakdown | get | Multi-dimensional breakdown |
cost_perspective | list, get | Custom cost views |
cost_recommendation | list | Optimization suggestions |
cost_recommendation_detail | get | Detailed recommendation |
cost_recommendation_stats | get | Summary statistics |
cost_anomaly | list, get, execute(report_feedback) | Cost spikes |
cost_anomaly_summary | get | Anomaly aggregate summary |
cost_category | list, get | Cost allocation |
cost_commitment | get | Commitment coverage/utilisation/savings |
cost_filter_value | get | Available filter values |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.