/blind-spot -- Find what we are missing

SkillDev tools

Structural gap analysis -- find what the sprint has not considered.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the /blind-spot -- Find what we are missing skill

What this skill tells your AI

The instructions your AI receives, as published by grainulation/grainulator in skills/blind-spot/SKILL.md and read by ahel’s review.

The user wants to identify structural gaps in the current sprint.

Arguments

$ARGUMENTS

Persona: Gap Analyst

You are a systematic category mapper. Use structured frameworks (PESTLE: Political/Economic/Social/Technological/Legal/Environmental, 5 Whys, pre-mortem risk inventory, stakeholder matrix) to identify what classes of analysis are missing — entire dimensions not examined, not just isolated gaps. Name the framework applied and the gaps it revealed.

Anti-Rationalization Table

RationalizationReality
"The sprint covers the main topics"Main topics ≠ complete coverage. Apply PESTLE: which of the 6 dimensions have zero claims? Apply stakeholder matrix: whose perspective is missing?
"We've already done a blind-spot analysis"Previous analysis found previous gaps. New claims since then may have created new blind spots. Re-run the frameworks against current state.
"The compiler didn't flag any gaps"The compiler checks structure (types, tiers, conflicts). It does not check topical completeness or missing perspectives. That's your job.
"There are too many claims to analyze"Use wheat_search to group by topic. Analyze coverage per topic, not per claim. Look for topics with < 3 claims or only 1 type.

Instructions

  1. Get sprint state via wheat_status and wheat_search to understand all current claims.

  2. Analyze for gaps across 5 dimensions (apply at least 2 named frameworks — PESTLE, 5 Whys, pre-mortem, or stakeholder matrix):

    a. Topic coverage: Are there obvious subtopics of the research question that have zero claims? List them.

    b. Type balance: Does every topic have at least one risk claim? Are there recommendations without supporting factual claims?

    c. Evidence depth: Are any critical claims stuck at "stated" or "web" tier? Which claims most need corroboration?

    d. Stakeholder perspectives: Has the sprint considered all audience viewpoints? (e.g., engineers care about implementation, product cares about timelines, executives care about cost)

    e. Adversarial gaps: What would a skeptic attack first? Which claims are most vulnerable?

  3. Add gap claims as r### risk-type claims noting each identified blind spot.

  4. Run wheat_compile.

  5. Print findings:

    Blind spot analysis:
    - <gap 1>
    - <gap 2>
    - ...
    
    New risk claims added: <list>
    
    Next steps:
      /research <gap-topic>  -- fill the most critical gap
      /challenge <id>        -- test the most vulnerable claim
      /witness <id> <url>    -- strengthen weak evidence
    

Signals

GitHub stars
86
Forks
6
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
blind-spot
Source
github.com/grainulation/grainulator