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thought-based-reasoning

Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques (Zero-shot CoT, Self-Consistency, Tree of Thoughts, Least-to-Most, ReAct, PAL, Reflexion) with templates, decision matrices, and research-backed patterns

Quality

69%

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./plugins/customaize-agent/skills/thought-based-reasoning/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%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 skill is a thorough, well-structured catalog of CoT prompting techniques with genuinely useful prompt templates, but it is significantly over-long for SKILL.md and explains background Claude already knows. Splitting per-technique detail into reference files and trimming conceptual exposition would materially improve it.

Suggestions

Move each technique's full template/strengths/limitations into separate reference files (e.g. references/self-consistency.md) and keep SKILL.md as a concise overview with one-line pointers, improving both conciseness and progressive disclosure.

Cut the "How It Works" conceptual explanations and paper citation counts, which restate knowledge Claude already has; retain only the trigger conditions, prompt templates, and the decision matrix.

Make Python examples fully executable by either providing the helper functions (llm.generate, extract_answer, generate_thoughts, evaluate) or marking the snippets explicitly as illustrative pseudocode with a note justifying the flexibility.

DimensionReasoningScore

Conciseness

The 640-line body extensively explains concepts Claude already knows (per-technique "How It Works", strengths, limitations for CoT/ReAct/PAL etc.) and pads with time-sensitive citation counts ("Citations: 14,255+"), making it noticeably verbose despite accuracy.

2 / 5

Actionability

Provides copy-paste-ready prompt templates for each technique and runnable-shape Python examples, but the Python relies on undefined helpers (llm.generate, extract_answer, generate_thoughts, evaluate) so it is not fully executable, capping it below 5.

4 / 5

Workflow Clarity

Two-stage techniques (Zero-shot CoT, Least-to-Most) and the Reflexion attempt-reflect-retry loop are sequenced, but as a reference catalog there are no validation checkpoints and the selection "workflow" relies on an ASCII decision matrix rather than explicit ordered steps.

3 / 5

Progressive Disclosure

Headers organize the content well, but the body is monolithic (no bundle files exist) and per-technique detail that clearly belongs in separate reference files is all inlined; the References section is academic citations, not skill-internal navigation.

3 / 5

Total

12

/

20

Passed

Description

75%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.

The description is well-constructed with an explicit "Use when" trigger, a clear statement of what the skill provides, and good keyword coverage of natural reasoning-related terms. It is held back from top marks by slight vagueness in a few action phrases and missing common trigger synonyms.

DimensionReasoningScore

Specificity

Lists several concrete actions ("provides comprehensive guide to Chain-of-Thought...with templates, decision matrices, and research-backed patterns") alongside the reasoning domains, though "research-backed patterns" is somewhat abstract, keeping it below a 5.

4 / 5

Completeness

Explicitly answers both "what" (guide to CoT and related techniques with templates/matrices) and "when" ("Use when tackling complex reasoning tasks..."), but the "when" could be slightly more specific about concrete trigger phrases.

4 / 5

Trigger Term Quality

Includes natural phrases users would say ("complex reasoning tasks", "step-by-step logic", "multi-step arithmetic", "commonsense reasoning", "Chain-of-Thought") with good coverage, but omits common variants like "thinking step by step" or "reasoning step by step".

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (Chain-of-Thought and named related prompting techniques) that is mostly distinct from other skills, with only minor overlap risk with general reasoning skills.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (659 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository

NeoLabHQ/context-engineering-kit

Path

plugins/customaize-agent/skills/thought-based-reasoning/SKILL.md

Reviewed

Table of Contents

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