interpreting-culture-index

Name: interpreting-culture-index
Author: trailofbits

Data Community

Repo stars 5,723
Forks 499
Author updated Jun 15, 2026, 04:05 PM
Author repo skills

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: Data
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @trailofbits · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: Python
Permissions: Read-only
Write / modify
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview interpreting-culture-index.preview

---
name: interpreting-culture-index
description: Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Sup…
category: data
runtime: Python
---

# interpreting-culture-index output preview

## PART A: Task fit
- Use case: 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..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Use / When NOT to Use” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “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.”.
- **02** When the source has headings, the agent prioritizes “When to Use / When NOT to Use” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: interpreting-culture-index
description: Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Sup…
category: data
source: trailofbits/skills
---

# interpreting-culture-index

## When to use
- Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profi…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “When to Use / When NOT to Use” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "interpreting-culture-index" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> When to Use / When NOT to Use
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Python | read files, write/modify files | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profile interpr…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “When to Use”, “When NOT to Use”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name interpreting-culture-index directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “When to Use / When NOT to Use” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Culture Index measures behavioral traits, not intelligence or skills. There is no "good" or "bad" profile.

**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?

**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.

Top graph (Survey Traits): Hardwired by age 12-16. Does not change. Writing with your dominant hand.
Bottom graph (Job Behaviors): Adaptive behavior at work. Can change. Writing with your non-dominant hand.

Large differences between graphs indicate behavior modification, which drains energy and causes burnout if sustained 3-6+ months.

**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.

**L (Logic) and I (Ingenuity) use absolute values.**

Unlike A, B, C, D, you CAN compare L and I scores directly between people:

Logic 8 means "High Logic" regardless of arrow position
Ingenuity 2 means "Low Ingenuity" for anyone

Only these two traits break the "no absolute comparison" rule.

When to Use

Interpreting Culture Index survey results (individual or team)
Analyzing CI profiles from PDF or JSON data
Assessing team composition using Gas/Brake/Glue framework
Detecting burnout risk by comparing Survey vs Job graphs
Defining hiring profiles based on CI trait patterns
Coaching managers on how to work with specific CI profiles
Predicting CI traits from interview transcripts
Mediating team conflict using CI profile data

When NOT to Use

For non-CI behavioral assessments (DISC, Myers-Briggs, StrengthsFinder, Predictive Index, Enneagram)
For clinical psychological assessments or diagnoses
As the sole basis for hiring/firing decisions — CI is one data point among many

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:

Check if JSON already exists (same directory as PDF, or ask user)

If not, run extraction with verification:

uv run {baseDir}/scripts/extract_pdf.py --verify /path/to/file.pdf [output.json]

Visually confirm the verification summary matches the PDF
Use the extracted JSON for interpretation

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.

Step 0: Do you have JSON or PDF?

If JSON provided or found: Use it directly (skip extraction)
- Check same directory as PDF for .json file with matching name
- Check if user provided JSON path

If only PDF: Run extraction script with --verify flag

uv run {baseDir}/scripts/extract_pdf.py --verify /path/to/file.pdf [output.json]

If extraction fails: Report error, do NOT fall back to vision

Step 1: What data do you have?

CI Survey JSON → Proceed to Step 2
CI Survey PDF → Extract first (Step 0), then proceed to Step 2
Interview transcript only → Go to option 8 (predict traits from interview)
No data yet → "Please provide Culture Index profile (PDF or JSON) or interview transcript"

Step 2: What would you like to do?

Profile Analysis:

Interpret an individual profile - Understand one person's traits, strengths, and challenges
Analyze team composition - Assess gas/brake/glue balance, identify gaps
Detect burnout signals - Compare Survey vs Job, flag stress/frustration
Compare multiple profiles - Understand compatibility, collaboration dynamics
Get motivator recommendations - Learn how to engage and retain someone

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.

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.

After every interpretation, verify:

Did you use relative positions? Never stated "A is 8" without context
Did you reference the arrow? All trait interpretations relative to arrow
Did you compare Survey vs Job? Identified any behavior modification
Did you avoid value judgments? No traits called "good" or "bad"
Did you check EU? Energy utilization calculated if both graphs present

Report to user:

"Interpretation complete"
Key findings (2-3 bullet points)
Recommended actions

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, archetypes

Archetype 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 type
team-composition.md - Gas, brake, glue framework
anti-patterns.md - Common interpretation mistakes
conversation-starters.md - How to engage each pattern and trait type
interview-trait-signals.md - Signals for predicting traits from interviews

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

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

A well-interpreted Culture Index profile:

Uses relative positions (distance from arrow), never absolute values alone
Identifies the archetype/pattern correctly
Highlights 2-3 key strengths based on leading traits
Notes 2-3 challenges or development areas
Compares Survey vs Job if both are available
Provides actionable recommendations
Avoids value judgments ("good"/"bad")
Acknowledges Culture Index is one data point, not a complete picture

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add trailofbits/skills/plugins/culture-index/skills/interpreting-culture-index -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

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未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

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