culture-interview-profile-prediction

culture-interview-profile-prediction is a skill for Codex from OutlineDriven/outline-driven-development. It costs 38 tokens per session (1,360 once invoked), scanned A, original, Apache-2.0.

An evidence-based prediction of a person's Culture Index traits from an interview transcript before they complete the assessment. It reports confidence, supporting quotes, likely patterns, and uncertainty.

In plain words
What is it for?
Use it to review interview evidence, estimate all six Culture Index traits, and identify areas that need verification.
Why use it?
It provides a structured provisional view when no completed survey exists, while making clear that the result is a prediction rather than a measured assessment.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to review interview evidence, estimate all six Culture Index traits, and identify areas that need verification.

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Install with agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add OutlineDriven/outline-driven-development --skill culture-interview-profile-prediction
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for culture-interview-profile-prediction

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction/github.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for culture-interview-profile-prediction

Your own site · 80×15
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/culture-interview-profile-prediction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,360 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.01360
Opus 5 $0.00019 $0.00680
Sonnet 5 $0.00008 $0.00272
Haiku 4.5 $0.00004 $0.00136

Measured 4d ago against content hash b4d02ab3c355, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

culture-interview-profile-prediction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.devin/skills/culture-interview-profile-prediction/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Culture interview profile prediction

Contract

Field Bound contract
Trigger An interview transcript needs a caveated, confidence-scored prediction of Culture Index traits before a survey exists.
Authority Read-only. No file, VCS, credential, paid, published, deployed, or remote mutation. Analyzes supplied transcript text only.
Side effect Chat output: per-trait predictions, confidence levels, supporting quotations, likely pattern, uncertainty areas, and caveats.
Done All six traits have evidence and confidence, weak evidence is labeled, and the output clearly distinguishes prediction from survey result.

Inputs

  • Required: An interview transcript with interviewer questions and candidate responses distinguishable. Multiple interviews increase confidence.
  • Optional: Timestamps or durations. Candidate name and interview metadata for the report header.

Procedure

  1. Load the transcript. Confirm interviewer questions and candidate responses are distinguishable. If they are not, stop and request a separated transcript. Done when: this step's stated action, evidence, and checks are complete.

  2. Initial read-through. Note overall communication style, energy level, topics that engage the candidate, and default communication mode before detailed analysis. Done when: this step's stated action, evidence, and checks are complete.

  3. Analyze A (Autonomy). Search the transcript for autonomy signals. High A: first-person ownership ("I decided", "I built"), takes personal credit, reframes or pushes back on questions, acted without being asked, assertive tone. Low A: collective language ("we decided", "our team"), deflects credit to team, asks for clarification, waited for direction, tentative tone. Record position (High / Low / Normative), confidence (High / Medium / Low), and 2-3 supporting quotes. Done when: this step's stated action, evidence, and checks are complete.

  4. Analyze B (Social). Search for social signals. High B: builds rapport, asks about the interviewer, people-centric narratives, verbose responses, animated energy, asks about team and social activities. Low B: gets straight to business, task-centric descriptions, brief direct answers, reserved energy, asks about work and tools. Record position, confidence, and 2-3 quotes. Done when: this step's stated action, evidence, and checks are complete.

Read the full file on GitHub · 54 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago Changed · -5 tokens per session b4d02ab3c355
  2. 7d ago First seen · 54 lines · 43 tokens per session scan A 39685edd9e7e

Subscribe to this mod's changes

culture-interview-profile-prediction is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed 5d ago), licensed Apache-2.0. It adds 38 tokens to every session and 1,360 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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