01 — TL;DR
If you need trigger clarity above all else, pick speech (3.6/5). evaluation-methodology (3.1/5) is a reasonable alternative if you're already in its source ecosystem. They overlap in methodology skill territory.
Side by side
3.1/5
3.6/5
Where they differ
- Trigger clarity. trigger clarity: speech is clearly stronger (4.5 vs 5.0). For workloads where this dimension matters, prefer speech.
- Output specificity. output specificity: speech is clearly stronger (4.0 vs 4.5). For workloads where this dimension matters, prefer speech.
- Scope precision. scope precision: evaluation-methodology and speech score essentially the same (4.5 vs 4.5). Neither has an edge here.
- Self-containment. self-containment: speech is clearly stronger (4.0 vs 4.5). For workloads where this dimension matters, prefer speech.
- Reusability. reusability: speech is clearly stronger (3.5 vs 4.0). For workloads where this dimension matters, prefer speech.
Which to pick
When to choose evaluation-methodology
- You weight community adoption — evaluation-methodology's upstream repo has 35,544 stars vs 19,581.
- The methodology skill convention you're working in matches evaluation-methodology's scope.
When to choose speech
- Your workload emphasizes trigger clarity — speech scores 4.5 vs 5.0 here.
- Your workload emphasizes output specificity — speech scores 4.0 vs 4.5 here.
- Your workload emphasizes self-containment — speech scores 4.0 vs 4.5 here.
- You prefer the official source — speech comes from github:openai/skills, evaluation-methodology from skillsmp.com.
Scenario by scenario
| Scenario | Winner | Why |
|---|---|---|
| Agent must auto-select between many methodology skills | speech | Trigger clarity decides — clearer triggers reduce routing errors. |
| Output must be a specific file format or structured data | speech | Output specificity determines whether downstream tools can rely on the result. |
| Skill must be readable and complete out of the box | speech | Self-containment matters when you're not the original author. |
| Cross-team or cross-project reuse expected | speech | Reusability separates one-off scripts from durable building blocks. |
Common questions
- Which is better, evaluation-methodology or speech?
- speech ranks higher overall (3.6 vs 3.1 on our 0–5 rubric). That said, the better choice depends on which dimensions matter most for your use case.
- Are evaluation-methodology and speech both free to use?
- Both skills are free and open-source (or freely licensed). evaluation-methodology: See source repo. speech: See source repo. Installation has no cost; usage costs depend on the underlying LLM tokens consumed when you invoke the skill.
- Can I install both evaluation-methodology and speech at the same time?
- Yes. Agent skills are not exclusive — an agent runtime (Claude Code, Codex, etc.) can have many skills installed and route to whichever matches the current task. Installing both is a low-cost way to keep your options open.
- Where do these skills come from?
- evaluation-methodology is sourced from skillsmp.com (curated marketplace). speech is sourced from github:openai/skills (official). We verify each skill across multiple sources where possible; evaluation-methodology appears in 1 source, speech in 1.