ysskrishna/ai-agent-skills

analytical-thinking

Use this skill when the user asks for analytical thinking (including naming it or directing use/apply/run with obvious misspellings; decisive) or wants a structured breakdown—decomposing the problem, defining metrics and hypotheses, organizing evidence, and synthesizing findings with explicit uncertainty. Use for quant-style reasoning framing, root-cause trees, decision tables, or comparable structure, including informal or incomplete data asks. Skip when they want open-ended idea spray with no…

First seen May 23, 2026

Installation

$ npx skills add ysskrishna/ai-agent-skills --skill analytical-thinking

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
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Repository health

Stars 8
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version2026.5.17
LicenseMIT
More metadata
author
ysskrishna
version
2026.5.17

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,337 B
  • docs SUMMARY.md 613 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 43 installs

SKILL.md

Analytical Thinking

Clarity beats cleverness. End with answers tied to structure and stated confidence.

How to run it with this skill: one clearly headed section per step in this order: Frame → Decompose → Hypotheses → Evidence → Synthesis. Insert Options matrix only when Setup calls for it (after Evidence, before Synthesis).


Setup (run before starting)

In one short block:

  1. Analytical question — precise, ideally falsifiable
  2. Default pass — Frame → Decompose → Hypotheses → Evidence → Synthesis (state this line)

If data availability or definitions are missing, ask at most 3 questions in one message, then proceed. Note any remaining gaps or working guesses in plain language (no bracket tags in Setup).

If the user is choosing among concrete alternatives, after Evidence insert Options matrix: rows = options, columns = criteria (state weights if any), qualitative scores (− / 0 / +) with one-line justification per cell — then finish with Synthesis.


The Steps

Frame

Question type (estimate, compare, explain, predict, optimize). Unit of analysis and baseline (even if hypothetical).

Decompose

Tree or table: factors, drivers, or workstreams. Each child node should be MECE-ish (mutually exclusive where it matters; collectively exhaustive enough for the decision).

Hypotheses

Ranked H1, H2, H3 — what would we expect to observe if each were true? What would falsify each?

Evidence

For each hypothesis: Observation: … — Strength note: one short sentence on how much this observation supports or undermines the hypothesis and the main limit (no Strong/Moderate/Weak labels). Caveat:

If no real data, run a thought experiment section instead — label bullets [THEORETICAL].

Synthesis

  1. Answer — direct response to the analytical question
  2. Key uncertainty — what single unknown swings the answer most
  3. Next data / step — what to collect or run next

Execution Rules

  1. Do not conflate Hypotheses and Evidence in the same bullet list.
  2. Numbers: if inputs are guessed, show ranges and label [ESTIMATED].
  3. Prefer structure over long prose.

Checklist (verify before responding)

  • Setup: analytical question + default pass (note if Options matrix used)
  • Frame states question type and baseline
  • Decompose is scannable (tree or table)
  • Hypotheses have falsifiers
  • Evidence (or [THEORETICAL]) mapped to hypotheses
  • Synthesis: answer, uncertainty, next step