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engineer-prompts-for-reasoning

Write or fix a prompt for a reasoning model (Gemini Pro, GPT-4o, Claude Sonnet) so it holds context across a multi-step task. Use for any request to draft, structure or debug such a prompt. Not for fast models (use engineer-prompts-for-instant).

65

Quality

82%

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SKILL.md
Quality
Evals
Security

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body delivers a usable template, a concrete worked example, and a validation checklist — genuinely actionable for its purpose. Its main weakness is token efficiency: conceptual padding, re-explanations of things Claude already knows, and hard-coded model version numbers that will age.

Suggestions

Trim conceptual padding: cut the "briefing a senior colleague" analogy in section 1 and the explanation of what XML tags do in section 3A — Claude already knows these; keep only the instruction to use them.

Remove hard-coded model versions ("Gemini 1.5 Pro", "Claude 3.5 Sonnet", "GPT-4o") or move them to a maintained list; the model landscape changes and these will silently go stale.

DimensionReasoningScore

Conciseness

Mostly efficient but several passages re-explain what Claude already knows ("Think of it like briefing a senior colleague... you explain the Background, the Goal, and the Constraints"; section 3A explaining what XML tags are for) and the body carries dated version numbers ("Gemini 1.5 Pro", "Claude 3.5 Sonnet") that will go stale. Not a 4: the padding is more than minor trimmings.

3 / 5

Actionability

The beginner template and the worked code-refactoring example are copy-paste-ready, and techniques include concrete directives ("Draft a plan in <plan> tags, then write the code"); bracketed placeholders are justified for a template. Not a 5: only one fully worked case is shown and some guidance stays abstract ("Define Success Criteria" lists example sentences but no template slot for them).

4 / 5

Workflow Clarity

Clear sequenced progression (core concept → template → techniques → example → end-of-prompt checklist) with the checklist serving as an explicit validation checkpoint; no risky batch/destructive operations so no validation cap applies. Not a 5: techniques A/B/C are presented as a flat list rather than integrated into when-to-apply decision points within the workflow.

4 / 5

Progressive Disclosure

No bundle files exist, and the ~128-line body is well organized with numbered sections, code fences, and a closing checklist. Not a 5: the body exceeds the under-50-line simple-skill exception, and the worked example section is a candidate for a separate examples file if the skill grows.

4 / 5

Total

15

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete actions, explicit use-when trigger guidance, named model keywords, and an explicit negative boundary against a sibling skill. Only minor gaps in synonym coverage and action breadth keep it from perfect marks on two dimensions.

DimensionReasoningScore

Specificity

Lists several concrete actions ("Write or fix a prompt", "draft, structure or debug such a prompt", "holds context across a multi-step task"), but write/draft and fix/debug are near-synonym pairs, leaving minor gaps in coverage compared to the comprehensive-action anchor.

4 / 5

Completeness

Explicitly answers both what ("Write or fix a prompt for a reasoning model... so it holds context across a multi-step task") and when ("Use for any request to draft, structure or debug such a prompt"), matching the both-answered-with-concrete-triggers anchor.

5 / 5

Trigger Term Quality

Good natural keyword coverage ("prompt", "reasoning model", "draft", "structure", "debug", "multi-step task") plus model names users actually say (Gemini Pro, GPT-4o, Claude Sonnet); a few common phrases like "prompt engineering" or "improve my prompt" are missing.

4 / 5

Distinctiveness Conflict Risk

Clear niche (prompt engineering for reasoning models) with an explicit disambiguation clause ("Not for fast models (use engineer-prompts-for-instant)") that actively routes away from the sibling skill, giving minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

korchasa/flowai-plugins

Path

plugins/flowai-engineering/skills/engineer-prompts-for-reasoning/SKILL.md

Reviewed

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