emotion-sensing

emotion-sensing is a skill for Claude Code, Codex from acnlabs/OpenPersona. It costs 0 tokens per session (820 once invoked), scanned B, original, MIT.

A communication skill that notices emotional signals in text, such as word choice, sentence rhythm, explicit feelings, and sudden topic changes. It uses those signals to adjust the assistant’s tone, not to make medical diagnoses.

In plain words
What is it for?
Use it to make conversations more empathetic by adapting replies to written language and, when enabled, voice or facial signals.
Why use it?
It helps responses fit the user’s apparent stress, uncertainty, urgency, or emotional state. It keeps that interpretation separate from clinical assessment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to make conversations more empathetic by adapting replies to written language and, when enabled, voice or facial signals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/acnlabs/openpersona/emotion-sensing
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 acnlabs/OpenPersona --skill emotion-sensing
Clone the repo
git clone --depth 1 https://github.com/acnlabs/OpenPersona

Made for: Claude Code, 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 emotion-sensing

README.md
[![agentmods](https://agentmods.dev/badge/skills/acnlabs/openpersona/emotion-sensing.svg)](https://agentmods.dev/skills/acnlabs/openpersona/emotion-sensing)
Your own site
<a href="https://agentmods.dev/skills/acnlabs/openpersona/emotion-sensing"><img src="https://agentmods.dev/badge/skills/acnlabs/openpersona/emotion-sensing.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 820 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00000 $0.00820
Opus 5 $0.00000 $0.00410
Sonnet 5 $0.00000 $0.00164
Haiku 4.5 $0.00000 $0.00082

Measured 8d ago against content hash 82febb62dad5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade B, and why

emotion-sensing scanned grade B with 1 finding 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 8d 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.

Subtle steeringmediumPrompt injection

Instructions that bias recommendations or shape behaviour without the user noticing.

Emotion-sensing informs *how* you respond — it does not produce a clinical label. Never tell the user "you are depressed" or "you are having a panic attack." Instead, respond to what you perceive: "It sounds like this ha
layers/faculties/emotion-sensing/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Emotion-Sensing Faculty — Sense

Read emotional signals from the way users communicate — tone, word choice, sentence rhythm, and declared context — and use that perception to calibrate your empathy and response quality. This faculty makes you a more attuned presence, not a clinical tool.


What You Perceive

Text-layer signals (always available)

  • Word choice: hedging language ("I guess", "maybe", "I don't know"), intensifiers ("really", "so", "completely"), negation clusters
  • Sentence rhythm: short fragmented sentences (distress, urgency), long run-on sentences (anxious processing), ellipses and trailing off
  • Explicit disclosure: "I'm stressed", "I feel lost", "this is exhausting"
  • Topic shift patterns: abrupt subject changes may signal avoidance

Modality-extended signals (when declared in body.runtime.modalities)

  • Voice tone (when emotion modality active): pitch variation, pace, pauses, vocal strain
  • Facial expression (when vision + emotion modalities active): micro-expressions, eye contact, posture

Perception Principles

Calibrate, don't diagnose

Emotion-sensing informs how you respond — it does not produce a clinical label. Never tell the user "you are depressed" or "you are having a panic attack." Instead, respond to what you perceive: "It sounds like this has been weighing on you."

Signal strength awareness

Treat emotional signals on a spectrum: ambient (background tone) → notable (worth acknowledging) → acute (requires direct response). Most signals are ambient — do not over-respond to every emotional cue.

Context over pattern-matching

A user saying "I'm dying" is almost always hyperbole. Read the full conversational context before interpreting emotional signals literally. When ambiguous, err toward acknowledging tone rather than content: "That sounds really frustrating."

Do not perform empathy

Avoid formulaic empathy responses ("I hear you", "That must be so hard", "I understand"). Respond naturally from your persona's character — empathy expressed in your own voice is always more effective than scripted compassion.

Read the full file on GitHub · 61 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. 8d ago First seen · 61 lines · 0 tokens per session scan B 82febb62dad5

Subscribe to this mod's changes

emotion-sensing is a skill published in the GitHub repository acnlabs/OpenPersona (49 stars, last pushed 28d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 820 tokens. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

officecli-academic-paper

Use this skill to build academic-style .docx output: journal / conference / thesis chapters carrying formal citation style (APA, Chicago, IEEE, MLA), numbered equations, figure & table cross-references, footnotes/endnotes, bibliography, or multi-column journal layout. Trigger on: 'research paper', 'journal paper'…

iOfficeAI/OfficeCLI · 141 tokens

officecli-word-form

Use this skill to create fillable Word forms (.docx) with real Content Controls (SDT) + legacy FormField checkboxes + MERGEFIELD mail-merge placeholders + document protection. Trigger on: 'fillable form', 'form fields', 'content controls', 'SDT', 'word form', 'fill in', 'only editable fields', 'protect document'…

iOfficeAI/OfficeCLI · 224 tokens

officecli-data-dashboard

Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to…

iOfficeAI/OfficeCLI · 157 tokens

officecli

Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.

iOfficeAI/OfficeCLI · 56 tokens

Smart Code Review

Review a PR diff: triage its severity, then produce a depth-appropriate review with structured findings, fix suggestions, and a merge decision. Use for code review, review PR, and severity triage requests.

AgentEra/Agently · 47 tokens

Security Audit Reporter

Triage raw security-scan findings (hardcoded secrets, injection patterns, vulnerable dependencies) into a prioritized, actionable security audit report. Use for security audit, code audit, vulnerability triage, and risk review.

AgentEra/Agently · 47 tokens