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Add cross-tool positioning, Python helpers, tiers, and hygiene docs

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Five improvements to position the library as a serious engineering project:

1. Cross-tool compatibility — new README "Works With" section honestly
   documenting where skills run (Claude Code natively; SKILL.md bodies
   port to other agents and chat LLMs as system prompts).

2. Python helper scripts (stdlib-only) for the three strongest skills:
   - sprint-planning: capacity_calculator.py (recommended commitment)
   - rice-prioritisation: rice_calculator.py (ranks, flags quick wins/moonshots)
   - cs-health-scorecard: health_score.py (weighted total + RAG)
   Each is wired into its SKILL.md and synced to the plugin copies.

3. Explicit skill tiering — TIERS.md + README section marking 46
   Production-Ready skills and calling out Experimental (external-dependency)
   ones; everything else is Stable.

4. Repository hygiene — new CHANGELOG.md (Keep a Changelog format) and
   SKILL-AUTHORING-STANDARD.md; refreshed SECURITY.md version table and
   helper-script disclosure; added .gitignore.

5. Related Projects — README section linking to alirezarezvani/claude-skills
   and the major awesome-claude-skills / awesome-claude-code lists.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016JWn5jRD5tcEFKrubjQ6Px
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2026-06-17 07:48:48 +00:00
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skills/rice-prioritisation/SKILL.md
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@@ -25,6 +25,24 @@ Ask the user for these if not provided:
## RICE Formula
RICE Score = (Reach × Impact × Confidence) / Effort
## Programmatic Helper
This skill ships with a stdlib-only Python script that calculates and ranks RICE scores so the maths is consistent and the quick-win / moonshot flags are applied by rule, not by feel. Feed it the initiatives once R, I, C, and E are gathered.
```bash
# From a JSON file (confidence accepts 0.8 or 80)
python3 scripts/rice_calculator.py initiatives.json
# Or from a CSV with header: name,reach,impact,confidence,effort
python3 scripts/rice_calculator.py initiatives.csv --format csv
# Or piped in
echo '[{"name":"Onboarding","reach":5000,"impact":2,"confidence":0.8,"effort":3}]' \
| python3 scripts/rice_calculator.py -
```
It outputs a ranked table with computed RICE scores and auto-flags **quick-win** (strong score, low relative effort), **moonshot** (high impact, high effort), and **low-confidence** (≤50%) items. Use the computed ranking as the starting point, then apply the validation step below — never accept a surprising top rank without checking the estimates behind it.
## Process
1. For each initiative provided, gather or estimate R, I, C, E values
2. Flag where estimates are weak and note what data would improve them