Metrics
by @ivangdavila
Capture, normalize, and report metrics across any domain with reusable dimensions, programmable formulas, and scalable reporting workflows.
clawhub install metricsπ About This Skill
name: Metrics slug: metrics version: 1.0.0 homepage: https://clawic.com/skills/metrics description: Capture, normalize, and report metrics across any domain with reusable dimensions, programmable formulas, and scalable reporting workflows. changelog: Initial release with metric registry design, formula governance, and automation-ready reporting workflows. metadata: {"clawdbot":{"emoji":"π","requires":{"bins":[]},"os":["linux","darwin","win32"]}}
Setup
On first use, read setup.md for integration behavior and memory initialization.
When to Use
Use this skill when the user needs to define, track, analyze, or report metrics for any domain such as social media, sales, product, operations, finance, or personal systems.
This skill structures metric definitions, computes reliable formulas, builds reusable report packs, and maintains scalable automation rules that can grow with the user over time.
Architecture
Working memory lives in ~/metrics/. See memory-template.md for base structure and status behavior.
~/metrics/
βββ memory.md # HOT: goals, active metrics, reporting cadence
βββ registry/ # WARM: metric contracts and dimension dictionaries
βββ formulas/ # WARM: formula specs with version history
βββ reports/ # WARM: report outputs by cadence and stakeholder
βββ automations/ # WARM: scheduled checks and alert policies
βββ archive/ # COLD: retired metrics and old report cycles
Quick Reference
Load only the file needed for the current task to keep context focused.
| Topic | File |
|-------|------|
| Setup and integration | setup.md |
| Memory schema | memory-template.md |
| Metric contract design | metric-registry.md |
| Formula design and governance | formula-playbook.md |
| Report cadences and templates | reporting-pack.md |
| Automation and alerting patterns | automation-patterns.md |
| Data validation and quality gates | data-quality.md |
Core Rules
1. Define a Metric Contract Before Any Calculation
Every metric must have one clear contract: business meaning, numerator, denominator, source tables, update latency, and owner.Never compute or compare metrics when the contract is missing or ambiguous.
2. Separate Raw Signals from Derived Metrics
Raw events are evidence. Metrics are interpreted aggregates. Keep them separate.Store and reason in this order: 1. Raw signal 2. Normalized base metric 3. Derived metric 4. Decision recommendation
3. Use Dimensions to Scale, Not New One-Off Metrics
When users ask for "the same metric but by X", add a dimension instead of creating a duplicate metric.Common high-value dimensions:
4. Version Formulas and Annotate Breaking Changes
Formulas evolve. Comparability fails when formula changes are not tracked.For every formula update, store:
5. Reports Must Be Decision-Oriented
A report is incomplete unless each section ties to a decision owner and explicit next action.Minimum output block for every report:
6. Automate Thresholds with Response Playbooks
Alerts without response rules create noise.Each threshold must include:
7. Prefer Reusable Reporting Packs Over Custom One-Offs
Build reusable templates for daily, weekly, monthly, and campaign reports so the system can scale across teams and domains.Only create custom formats when a stakeholder decision cannot be served by existing packs.
Common Traps
Security & Privacy
Data that leaves your machine:
Data that stays local:
~/metrics/.This skill does NOT:
~/metrics/ for memory storage.Related Skills
Install withclawhub install if user confirms:
analytics β metric analysis patterns and interpretation workflows.dashboard β KPI visualization design and reporting layouts.report β structured reporting outputs for stakeholders.sql β query generation for metric extraction pipelines.excel-xlsx β spreadsheet-based metric operations and exports.Feedback
clawhub star metricsclawhub syncβ‘ When to Use
βοΈ Configuration
On first use, read setup.md for integration behavior and memory initialization.