Input Analyst

Transform messy human input into precise, actionable prompts. Catch what the user meant, not just what they typed. [EXPLICIT]

Deterministic Offline Compiler

Use scripts/compile-input-analysis.py when the task needs a reproducible artifact or a stable schema. The compiler reads only local assets/ JSON files and a JSON input file; it never calls APIs, MCP tools, model providers, or the network. [EXPLICIT]

python3 skills/input-analyst/scripts/compile-input-analysis.py \
  --input skills/input-analyst/scripts/fixtures/input-analysis-input.json \
  --output /tmp/input-analysis.md

For machine-readable output, add --json. The stable output sections are: surface_errors, five_whys, seven_so_whats, intent_gap_analysis, ambiguity_register, actionability_score, clarified_prompt, routing_hints, user_safety_privacy_flags, and confidence. [EXPLICIT]

Read assets/source-map.md for the local source map and assets/input-analysis-schema.json for the input/output contract. [EXPLICIT]

When to Activate

This is a pre-processing layer. It runs BEFORE other skills activate. [EXPLICIT]

Do NOT over-analyze simple, well-formed requests. [EXPLICIT]

The Five Passes

Raw Input → SURFACE → 5 WHYS → 7 SO WHATS → INTENT → REFORMULATE → Structured Prompt

Pass 1: Surface Analysis

Detect and catalog surface-level issues. [EXPLICIT]

What to catch:

• Typos and misspellings (including dyslexia patterns: letter reversals, phonetic substitutions, missing vowels)
• Punctuation errors or absence
• Run-on sentences and fragments
• Autocorrect artifacts ("ducking" and similar)
• Mixed languages within a message
• Ambiguous abbreviations

Output: Corrected text + list of corrections made.

Critical rule: Preserve intent when correcting. Fix surface errors only — never change meaning.

For pattern libraries and detection heuristics, read references/analysis-patterns.md. [EXPLICIT]

Pass 2: Five Whys Analysis

Dig beneath the surface request to find the root need. [EXPLICIT]

Protocol:

User says: "I need a presentation about Q4 results"
Why 1: Why a presentation? → Boss asked for a quarterly review
Why 2: Why a review? → Team missed targets, needs realignment
Why 3: Why realignment? → Strategy pivot mid-quarter
Why 4: Why does that matter now? → Budget planning depends on it
Why 5: Why is budget at risk? → Need to justify continued investment

Root need: A persuasive case for continued investment despite Q4 misses,
           formatted as a quarterly review. [EXPLICIT]

Rules:

• Stop before 5 if the root is clear. Do not force all 5.
• Each "why" must be answerable from context or reasonable inference.
• If a "why" requires unavailable information, note it as an open question — do not guess.

For the complete protocol with examples, read references/five-whys-guide.md. [EXPLICIT]

Pass 3: Seven So-Whats Analysis

Trace implications forward. If we solve this, what happens next?

Purpose: Calibrate response depth. A "presentation" that determines budget allocation deserves more investment than a casual summary.

Rules:

• Follow the most impactful chain, not every branch.
• Stop when implications become speculative.
• Use the result to set quality calibration for downstream skills.

For the complete protocol, read references/seven-so-whats-guide.md. [EXPLICIT]

Pass 4: Intent Analysis

Compare what was typed with what was meant. Identify the gap. [EXPLICIT]

Gap types:

Protocol:

1. List explicit statements (what they literally said). [EXPLICIT]
2. List implicit signals (tone, word choice, what they didn't say). [EXPLICIT]
3. Identify gaps between explicit and implicit. [EXPLICIT]
4. Formulate the "real ask" — what they would say with perfect clarity. [EXPLICIT]

For detailed heuristics, read references/intent-detection.md. [EXPLICIT]

Pass 5: Reformulation

Synthesize all passes into a high-quality prompt. [EXPLICIT]

Reformulation targets:

• Clear objective (action verb + measurable outcome)
• Specific constraints (include, exclude, format)
• Context provided (domain, audience, stakes)
• Output format defined (deliverable type, structure, length)

Output template:

[Reformulated prompt]

Context: [From 5 Whys + 7 So Whats]
Intent: [From Pass 4 gap analysis]
Constraints: [Explicit + inferred]
Expected output: [Deliverable format and scope]

Pipeline Integration

[input-analyst] → [task-engine] → [excellence-loop] → User

The reformulated prompt from Pass 5 becomes input for task-engine. Higher quality input raises baseline confidence, reducing iterations downstream. [EXPLICIT]

Assumptions & Limits

• This skill infers intent from textual signals. It cannot read minds. When inference confidence is low, flag the ambiguity rather than committing to a guess.
• Language detection is heuristic. Mixed-language inputs may lose nuance in reformulation.
• The 5 Whys analysis works best when there is enough context in the thread. On cold-start (first message, no history), root-cause depth is limited.
• Reformulation should never add requirements the user didn't express or imply. It clarifies, it does not invent.
• For very short inputs (< 5 words), skip passes 2-3 and focus on intent verification only.

Edge Cases

• Intentionally informal input: Some users write casually on purpose. Don't "fix" tone — correct only objective errors (typos, grammar) and preserve voice.
• Multiple questions in one message: Decompose into separate reformulated prompts, one per distinct question.
• User corrects themselves mid-message: Use the final version as the intent. Ignore crossed-out or contradicted earlier statements.
• Non-text input (images, files): Pass 1 (surface analysis) does not apply. Skip to passes 2-5 using the content's semantics.
• User says "just do X": This is a signal to skip deep analysis. Run Pass 4 (intent) only to confirm, then pass through with minimal reformulation.
• Sarcasm or irony: Flag as uncertain intent. Do not reformulate sarcastically — ask for clarification.

Antipatterns

Validation Gate

Before passing the reformulated prompt downstream, confirm:

• Surface corrections (if any) did not alter meaning
• Root-cause analysis is grounded in available context, not speculation
• The "real ask" differs from the literal ask only where evidence supports it
• Reformulated prompt has: objective, constraints, context, and expected output
• Ambiguities that could not be resolved are explicitly flagged
• Analysis depth matches input quality (no over-analysis on clear inputs)
• If using the offline compiler, routing_policy.offline_only=true and allow_external_apis=false
• Output includes actionability score, routing hints, privacy flags, and confidence

Reference Files

• references/analysis-patterns.md — Dyslexia patterns, common typos, autocorrect artifacts, detection heuristics
• references/five-whys-guide.md — Complete 5 Whys protocol with cross-domain examples
• references/seven-so-whats-guide.md — Complete 7 So Whats protocol with value chain examples
• references/intent-detection.md — Gap analysis framework, signal detection, reformulation strategies
• assets/ — Stable local schema, pattern libraries, taxonomy, quality calibration, and templates
• scripts/ — Offline compiler, deterministic fixtures, and check.sh

Author: toolkit contributors | Last updated: 2026-06-02

Packet

Capas del packet, cargables bajo demanda (disciplina ICM: una capa por vez, nunca todas juntas): references/ guías de profundidad (cargar UNA por etapa) · knowledge/ cuerpo de conocimiento · prompts/ prompts listos · examples/ salida de ejemplo · agents/ subagentes del packet · templates/ plantilla de output · scripts/ automatización local · assets/ recursos estáticos.