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Analyze

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Blevene
analyze

Conduct structured analysis on any problem using CIA/IC analytic techniques — assess competing hypotheses, challenge assumptions, stress-test judgments, and produce defensible evidence-based assessments with full citations. Supports 18 techniques including ACH, Key Assumptions Check, What-If, Premortem, Cross-Impact Matrix, Contrasting Narratives, Devil's Advocacy, Red Hat Analysis, Alternative Futures, and Deception Detection.

Overview

PublisherBlevene
Repositorystructured-analysis-skill
Skill nameanalyze
Stars
66
Forks
14
Bundled files
51
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 51 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Blevene on GitHub. Read the source before you install it.

Installation

Install the Analyze AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Blevene/structured-analysis-skill/tree/main/plugin/skills/analyze
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Blevene/structured-analysis-skill.git /tmp/structured-analysis-skill
mkdir -p .claude/skills
cp -r /tmp/structured-analysis-skill/plugin/skills/analyze .claude/skills/analyze
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyze on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyze is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Structured Analysis Skill

Apply CIA/IC Structured Analytic Techniques to produce defensible, evidence-based analytical assessments. Every claim must be cited. Every judgment must trace to technique outputs.

Invocation

/structured-analysis:analyze                          → Adaptive mode (auto-select techniques)
/structured-analysis:analyze <technique>              → Direct mode (run one technique)
/structured-analysis:analyze --guided                 → Guided mode (walk through all phases)
/structured-analysis:analyze --resume <analysis-id>   → Resume or update existing analysis
/structured-analysis:analyze --iterate <analysis-id>                → Re-run full analysis with new evidence
/structured-analysis:analyze --iterate <analysis-id> <technique>    → Re-run specific technique(s)
/structured-analysis:analyze --lean                   → Lean mode (abbreviated technique set)
/structured-analysis:analyze --comprehensive          → Comprehensive mode (full rubric, adversarial + deception checks)
/structured-analysis:analyze --no-osint               → Disable web research

Commands use the plugin (namespaced) form /structured-analysis:analyze. If the skill is loaded un-namespaced, drop the prefix and use the bare /analyze.

Techniques: customer-checklist, issue-redefinition, restatement, brainstorm, kac, ach, inconsistencies, cross-impact, what-if, premortem, counterfactual, narratives, bowtie, opportunities, devils-advocacy, red-hat, alt-futures, deception

Flags combine: /structured-analysis:analyze --guided --no-osint is valid.

Execution

You MUST read the orchestrator protocol before proceeding. It contains mode routing, technique selection logic, and the technique routing table.

Step 0 — Context Inference

Before parsing explicit arguments, scan the conversation history for implicit inputs. Users often invoke /structured-analysis:analyze mid-conversation after discussing a problem, providing data, or sharing links.

Extract from conversation context:

  • Problem statement: What is the user trying to analyze? Look for questions, concerns, scenarios, or decisions under discussion.
  • Implicit technique hints: Did the user mention assumptions, hypotheses, competing explanations, risks, or scenarios? Map these to techniques (e.g., "I'm not sure which explanation is right" → ACH, "what could go wrong" → Premortem).
  • Implicit flags: Did the user indicate they want something quick (→ --lean), don't want web research (→ --no-osint), or want to walk through everything (→ --guided)?
  • Prior analysis: Are there existing analyses in analyses/ for the same topic? (→ suggest --resume or --iterate)
  • Evidence already provided: Files shared, URLs pasted, data discussed — these become Tier 1/2 evidence.

Step 0.1 — Validate Assumptions

If context inference produced any results, present them to the user for confirmation before proceeding:

Based on our conversation, here's what I'm picking up:

**Problem**: [inferred problem statement]
**Mode**: [inferred mode + rationale]
**Techniques**: [inferred techniques, if any]
**Flags**: [inferred flags, if any]
**Prior context**: [files, data, or evidence already in conversation]

Does this look right? Adjust anything before I proceed.

If the user provided explicit arguments, those always take precedence — but still surface any useful context (e.g., "You asked for ACH. I also noticed you shared [file] earlier — I'll include that as evidence.").

If no conversation context exists and no arguments were provided, proceed directly to Adaptive mode (the orchestrator will prompt for a problem statement).

Steps 1–6 — Main Execution

  1. Read protocols/orchestrator.md (relative to this skill's directory)
  2. Parse explicit arguments → determine mode and flags (merge with Step 0 inferences, explicit args win)
  3. Follow the orchestrator's instructions for the detected mode
  4. For technique execution, follow the orchestrator's Technique Execution Contract:
    • 1 technique (Direct mode): Execute in-context — read protocol, read template, execute SETUP → PRIME → EXECUTE → ARTIFACT → FINDINGS → HANDOFF, write artifact to analyses/<id>/working/
    • 2+ techniques: Dispatch to background subagents in dependency-aware tiers — each subagent reads protocol/template, executes the technique, writes the artifact, and returns only a compact findings summary. Main context accumulates summaries and file paths, not full technique work.
  5. For evidence gathering: read and execute protocols/evidence-collector.md
  6. For report synthesis: dispatch per protocols/report-generator.md Phase A/B architecture

Self-Correction (3 Layers)

  • Layer 1 (after each technique, silent): Protocol compliance check — all steps completed? All template sections filled? No unfilled {{PLACEHOLDER}} tokens?
  • Layer 2 (before report, silent): Analytical self-critique — 8 checks:
    • 3a. Assumption audit
    • 3b. Evidence balance
    • 3c. Confidence calibration
    • 3d. Alternative check
    • 3e. Missing voices
    • 3f. Internal consistency audit (cross-artifact validation)
    • 3g. Analytical bias scan (sycophancy, anchoring, vividness, completion, authority)
    • 3h. Quality score (quantitative 1-5 with pass/fail threshold)
  • Layer 3 (before finalization): Human review gate — present summary (including quality score), incorporate feedback
  • Auto-Remediation Gate (between Phase A and Phase B): HIGH-severity Layer 2 flags (evidence imbalance >2:1, unstated critical premises, strong counter-arguments, sycophancy/anchoring bias, quality score < 3.0) trigger automatic remediation — the orchestrator invokes the iteration handler to collect targeted evidence, re-run flagged techniques (max 3), and regenerate the report before the user sees it. Capped at 1 cycle. Zero overhead when no HIGH flags exist.
  • Critique-to-Iteration Bridge (after results): Remaining MEDIUM/LOW flags from Layer 1 and Layer 2 are mapped to specific technique re-runs and evidence collection focuses, presented as ready-to-run /structured-analysis:analyze --iterate commands. Only fires when actionable flags exist beyond what auto-remediation already addressed. All flags and their statuses are written to next-steps.md in the analysis root — a standalone ledger tracking OPEN, REMEDIATED, RESOLVED, and DEFERRED items across iterations. The --iterate handler reads this file as its primary input.

Citation Requirement

Every claim in every artifact must be cited. No exceptions. Citation methods:

  • OSINT: [Source](URL) — Retrieved: YYYY-MM-DD
  • FILE: [filename:line_range]
  • USER: [User-provided, session context]
  • ANALYSIS: [Derived via technique_name]
  • PRIOR-ITERATION: [PRIOR-v{N}: technique_name]

OSINT is never presented as fact — always "according to [source]".

Reference Library

For deep background on any technique, read docs/library/00-prime.md and the specific library files referenced in each protocol. The library contains the full theoretical foundation, axioms, selection matrices, and empirical critiques underlying this skill.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyze AI skill do?

Conduct structured analysis on any problem using CIA/IC analytic techniques — assess competing hypotheses, challenge assumptions, stress-test judgments, and produce defensible evidence-based assessments with full citations. Supports 18 techniques including ACH, Key Assumptions Check, What-If, Premortem, Cross-Impact Matrix, Contrasting Narratives, Devil's Advocacy, Red Hat Analysis, Alternative Futures, and Deception Detection.

Why use Analyze on TypingMind?

Because you install it once and use it with any model. Analyze is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyze in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Blevene/structured-analysis-skill/tree/main/plugin/skills/analyze. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyze?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyze?

As many as you like. As long as a model supports skills, you can use Analyze with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyze AI skill free?

Yes. It is published on GitHub by Blevene under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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