external/trailofbits-security/culture-index/skills/interpreting-culture-index/SKILL.md
Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profile interpretation, team composition analysis (gas/brake/glue), burnout detection, profile comparison, hiring profiles, manager coaching, interview transcript analysis for trait prediction, candidate debrief, onboarding planning, and conflict mediation. Accepts extracted JSON or PDF input via OpenCV extraction script.
npx skillsauth add seikaikyo/dash-skills interpreting-culture-indexInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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<essential_principles>
Culture Index measures behavioral traits, not intelligence or skills. There is no "good" or "bad" profile.
<principle name="never-compare-absolutes"> **Never compare absolute trait values between people.**The 0-10 scale is just a ruler. What matters is distance from the red arrow (population mean at 50th percentile). The arrow position varies between surveys based on EU.
Why the arrow moves: Higher EU scores cause the arrow to plot further right; lower EU causes it to plot further left. This does not affect validity—we always measure distance from wherever the arrow lands.
Wrong: "Dan has higher autonomy than Jim because his A is 8 vs 5" Right: "Dan is +3 centiles from his arrow; Jim is +1 from his arrow"
Always ask: Where is the arrow, and how far is the dot from it? </principle>
<principle name="survey-vs-job"> **Survey = who you ARE. Job = who you're TRYING TO BE.**"You can't send a duck to Eagle school." Traits are hardwired—you can only modify behaviors temporarily, at the cost of energy.
Large differences between graphs indicate behavior modification, which drains energy and causes burnout if sustained 3-6+ months. </principle>
<principle name="distance-interpretation"> **Distance from arrow determines trait strength.**| Distance | Label | Percentile | Interpretation | |----------|-------|------------|----------------| | On arrow | Normative | 50th | Flexible, situational | | ±1 centile | Tendency | ~67th | Easier to modify | | ±2 centiles | Pronounced | ~84th | Noticeable difference | | ±4+ centiles | Extreme | ~98th | Hardwired, compulsive, predictable |
Key insight: Every 2 centiles of distance = 1 standard deviation.
Extreme traits drive extreme results but are harder to modify and less relatable to average people. </principle>
<principle name="l-and-i-exception"> **L (Logic) and I (Ingenuity) use absolute values.**Unlike A, B, C, D, you CAN compare L and I scores directly between people:
Only these two traits break the "no absolute comparison" rule. </principle>
</essential_principles>
<input_formats>
JSON (Use if available)
If JSON data is already extracted, use it directly:
import json
with open("person_name.json") as f:
profile = json.load(f)
JSON format:
{
"name": "Person Name",
"archetype": "Architect",
"survey": {
"eu": 21,
"arrow": 2.3,
"a": [5, 2.7],
"b": [0, -2.3],
"c": [1, -1.3],
"d": [3, 0.7],
"logic": [5, null],
"ingenuity": [2, null]
},
"job": { "..." : "same structure as survey" },
"analysis": {
"energy_utilization": 148,
"status": "stress"
}
}
Note: Trait values are [absolute, relative_to_arrow] tuples. Use the relative value for interpretation.
Check same directory as PDF for matching .json file, or ask user if they have extracted JSON.
PDF Input (MUST EXTRACT FIRST)
⚠️ NEVER use visual estimation for trait values. Visual estimation has 20-30% error rate.
When given a PDF:
uv run {baseDir}/scripts/extract_pdf.py --verify /path/to/file.pdf [output.json]
If uv is not installed: Stop and instruct user to install it (brew install uv or pip install uv). Do NOT fall back to vision.
PDF Vision (Reference Only)
Vision may be used ONLY to verify extracted values look reasonable, NOT to extract trait scores.
</input_formats>
<intake>Step 0: Do you have JSON or PDF?
.json file with matching name--verify flag
uv run {baseDir}/scripts/extract_pdf.py --verify /path/to/file.pdf [output.json]
Step 1: What data do you have?
Step 2: What would you like to do?
Profile Analysis:
Hiring & Candidates: 6. Define hiring profile - Determine ideal CI traits for a role 7. Coach manager on direct report - Adjust management style based on both profiles 8. Predict traits from interview - Analyze interview transcript to estimate CI traits 9. Interview debrief - Assess candidate fit based on predicted traits
Team Development: 10. Plan onboarding - Design first 90 days based on new hire and team profiles 11. Mediate conflict - Understand friction between two people using their profiles
Provide the profile data (JSON or PDF) and select an option, or describe what you need.
</intake> <routing>| Response | Workflow |
|----------|----------|
| "extract", "parse pdf", "convert pdf", "get json from pdf" | workflows/extract-from-pdf.md |
| 1, "individual", "interpret", "understand", "analyze one", "single profile" | workflows/interpret-individual.md |
| 2, "team", "composition", "gaps", "balance", "gas brake glue" | workflows/analyze-team.md |
| 3, "burnout", "stress", "frustration", "survey vs job", "energy", "flight risk" | workflows/detect-burnout.md |
| 4, "compare", "compatibility", "collaboration", "multiple", "two profiles" | workflows/compare-profiles.md |
| 5, "motivate", "engage", "retain", "communicate" | Read references/motivators.md directly |
| 6, "hire", "hiring profile", "role profile", "recruit", "what profile for" | workflows/define-hiring-profile.md |
| 7, "manage", "coach", "1:1", "direct report", "manager" | workflows/coach-manager.md |
| 8, "transcript", "interview", "predict traits", "guess", "estimate", "recording" | workflows/predict-from-interview.md |
| 9, "debrief", "should we hire", "candidate fit", "proceed", "offer" | workflows/interview-debrief.md |
| 10, "onboard", "new hire", "integrate", "starting", "first 90 days" | workflows/plan-onboarding.md |
| 11, "conflict", "friction", "mediate", "not working together", "clash" | workflows/mediate-conflict.md |
| "conversation starters", "how to talk to", "engage with" | Read references/conversation-starters.md directly |
After reading the workflow, follow it exactly.
</routing><verification_loop>
After every interpretation, verify:
Report to user:
</verification_loop>
<reference_index>
Domain Knowledge (in references/):
Primary Traits:
primary-traits.md - A (Autonomy), B (Social), C (Pace), D (Conformity)Secondary Traits:
secondary-traits.md - EU (Energy Units), L (Logic), I (Ingenuity)Patterns:
patterns-archetypes.md - Behavioral patterns, trait combinations, archetypesArchetype Deep Profiles (archetype-*.md):
archetype-administrator.md - The Administrator (High A, High B, Low C, Mid D)archetype-coordinator.md - The Coordinator (Low A, High B, Mid C, Low D)archetype-craftsman.md - The Craftsman (Low A, Low B, High C, High D)archetype-daredevil.md - The Daredevil (High A, Low B, Low C, Low D)archetype-debater.md - The Debater (Mid A, Mid-High B, Low C, High D)archetype-facilitator.md - The Facilitator (Low A, Mid B, Mid C, Low D)archetype-influencer.md - The Influencer (Low A, High B, Low C, Low D)archetype-operator.md - The Operator (Low A, Low B, High C, Mid-High D)archetype-persuader.md - The Persuader (High A, High B, Low C, Low D)archetype-philosopher.md - The Philosopher (Low A, Low B, High C, Low D)archetype-rainmaker.md - The Rainmaker (High A, High B, Low C, Low D)archetype-scholar.md - The Scholar (High A, Low B, Low C, High D)archetype-socializer.md - The Socializer (Low A, High B, Low C, Low D)archetype-specialist.md - The Specialist (Low A, Low B, High C, Mid D)archetype-technical-expert.md - The Technical Expert (Low A, Low B, High C, Low D)archetype-traditionalist.md - The Traditionalist (Low A, Low B, High C, High D)archetype-trailblazer.md - The Trailblazer (High A, Mid B, Mid C, Low D)Application:
motivators.md - How to motivate each trait typeteam-composition.md - Gas, brake, glue frameworkanti-patterns.md - Common interpretation mistakesconversation-starters.md - How to engage each pattern and trait typeinterview-trait-signals.md - Signals for predicting traits from interviews</reference_index>
<workflows_index>
Workflows (in workflows/):
| File | Purpose |
|------|---------|
| extract-from-pdf.md | Extract profile data from Culture Index PDF to JSON format |
| interpret-individual.md | Analyze single profile, identify archetype, summarize strengths/challenges |
| analyze-team.md | Assess team balance (gas/brake/glue), identify gaps, recommend hires |
| detect-burnout.md | Compare Survey vs Job, calculate EU utilization, flag risk signals |
| compare-profiles.md | Compare multiple profiles, assess compatibility, collaboration dynamics |
| define-hiring-profile.md | Define ideal CI traits for a role, identify acceptable patterns and red flags |
| coach-manager.md | Help managers adjust their style for specific direct reports |
| predict-from-interview.md | Analyze interview transcripts to predict CI traits before survey |
| interview-debrief.md | Assess candidate fit using predicted traits from transcript analysis |
| plan-onboarding.md | Design first 90 days based on new hire profile and team composition |
| mediate-conflict.md | Understand and address friction between team members using their profiles |
</workflows_index>
<quick_reference>
Trait Colors: | Trait | Color | Measures | |-------|-------|----------| | A | Maroon | Autonomy, initiative, self-confidence | | B | Yellow | Social ability, need for interaction | | C | Blue | Pace/Patience, urgency level | | D | Green | Conformity, attention to detail | | L | Purple | Logic, emotional processing | | I | Cyan | Ingenuity, inventiveness |
Energy Utilization Formula:
Utilization = (Job EU / Survey EU) × 100
70-130% = Healthy
>130% = STRESS (burnout risk)
<70% = FRUSTRATION (flight risk)
Gas/Brake/Glue: | Role | Trait | Function | |------|-------|----------| | Gas | High A | Growth, risk-taking, driving results | | Brake | High D | Quality control, risk aversion, finishing | | Glue | High B | Relationships, morale, culture |
Score Precision: | Value | Precision | Example | |-------|-----------|---------| | Traits (A,B,C,D,L,I) | Integer 0-10 | 0, 1, 2, ... 10 | | Arrow position | Tenths | 0.4, 2.2, 3.8 | | Energy Units (EU) | Integer | 11, 31, 45 |
</quick_reference>
<success_criteria>
A well-interpreted Culture Index profile:
</success_criteria>
development
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
Reference for writing and editing agent skills well — the vocabulary and principles that make a skill predictable. Consult when authoring, reviewing, or pruning a SKILL.md.