Agent skill

Call Cognitive Load Monitor

by CALLE-AI in CALLE-AI/awesome-phone-call-agents

Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive…

MITAuto-check passed

Install Call Cognitive Load Monitor

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/call-cognitive-load-monitor .claude/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .claude/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/call-cognitive-load-monitor .agents/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .agents/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/call-cognitive-load-monitor .cursor/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .cursor/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/CALLE-AI/awesome-phone-call-agents.git --path skills/call-cognitive-load-monitor

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/call-cognitive-load-monitor .gemini/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .gemini/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/call-cognitive-load-monitor .github/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .github/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install CALLE-AI/awesome-phone-call-agents call-cognitive-load-monitor --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/call-cognitive-load-monitor .opencode/skills/call-cognitive-load-monitor && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "call-cognitive-load-monitor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-cognitive-load-monitor into .opencode/skills/call-cognitive-load-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-cognitive-load-monitor", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: call-cognitive-load-monitor
GitHub stars: 107
Token cost: ~2.3k tokens
SKILL.md length: 608 words
Files: 8 (incl. scripts, references)
Skills in repo: 101
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive…

SKILL.md covers Why This Skill Exists, Research Scope, Quick Start and Input, plus 9 more sections
Runs Python scripts from its folder; calls python3

What it does

Call Cognitive Load Monitor is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive assessment or consent determination.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/example-transcript.json`, `references/examples.md` and `references/research-papers.md`).

The repository describes itself as: Portable phone-call Agent Skills, apps, examples, adapters, and scheduler recipes for AI agents. The licence is MIT.

Example prompts

“/call-cognitive-load-monitor”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 38d4118. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Call Cognitive Load Monitor loads about 2.3k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 608 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~64
When it runs · the whole SKILL.md, loaded when a task matches: ~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from CALLE-AI/awesome-phone-call-agents at commit 38d4118, republished under its MIT licence (© CALLE-AI). 608 words, ~2,258 tokens.

Download SKILL.mdSave it as .claude/skills/call-cognitive-load-monitor/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.

name: call-cognitive-load-monitor
description: Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive assessment or consent determination.
license: MIT

call-cognitive-load-monitor

Detect when your caller is overwhelmed — before it costs you the call.

This skill analyzes supplied text for heuristic confusion markers and conversational proxies. It does not measure acoustics, administer a cognitive assessment, or establish consent validity. Reports and suggested script changes require human review; no live integration, message sending or follow-up call is performed.

Why This Skill Exists

Most call-centre quality tools measure whether the agent performed well. This skill measures whether the caller was able to process what was said. When cognitive load peaks — especially at closing, where consent and commitment are given — the validity of that interaction is at risk.

Advisory scope: A CONSENT_AT_RISK label is a suggestion for human review, not a regulatory finding or authorization for a follow-up call. No label establishes that consent is valid or invalid.

Research Scope

The weights and thresholds are unvalidated demonstration choices, not a reproduction of a published acoustic model. Background and claim limitations: references/research-papers.md.

Quick Start

bash

python3 scripts/monitor_cognitive_load.py \
  --transcript path/to/transcript.json \
  --dry-run \
  --out /tmp/load_report.json

Validate output schema

bash

python3 scripts/validate_load_report.py --report /tmp/load_report.json

Input

Standard CALL-E transcript — same two formats as other skills:

Format A — array of turns:

json

[
  {"role": "agent",  "text": "Under the terms of sub-clause 4(b)(ii) of the agreement..."},
  {"role": "callee", "text": "Sorry, could you say that again? I'm not following."},
  {"role": "agent",  "text": "Of course. Regarding the billing section specifically..."},
  {"role": "callee", "text": "I still don't understand. What does that mean for me?"}
]

Output — Overload Report

json

{
  "call_id": "calle-001",
  "analysis_timestamp": "2026-09-17T08:00:00Z",
  "overall_cognitive_load": "HIGH",
  "load_score": 0.78,
  "load_by_phase": {
    "opening":  0.12,
    "middle":   0.45,
    "closing":  0.78
  },
  "peak_phase": "closing",
  "overload_signals": [
    {
      "type": "repetition_request",
      "evidence": "Sorry, could you say that again?",
      "turn": 4,
      "phase": "middle",
      "weight": 0.30
    },
    {
      "type": "confusion_phrase",
      "evidence": "I still don't understand. What does that mean for me?",
      "turn": 6,
      "phase": "middle",
      "weight": 0.25
    },
    {
      "type": "jargon_density_spike",
      "evidence": "sub-clause 4(b)(ii) of the agreement",
      "turn": 3,
      "phase": "middle",
      "weight": 0.18
    }
  ],
  "interaction_dynamics": {
    "turn_imbalance_score": 0.62,
    "avg_silence_gap_ms": 2800,
    "overlap_count": 0,
    "participation_ratio": {"agent": 0.74, "callee": 0.26}
  },
  "script_patches": [
    {
      "original": "Under the terms of sub-clause 4(b)(ii) of the agreement",
      "suggested": "According to our billing rules",
      "rationale": "Legal jargon removed; Flesch-Kincaid grade reduced from 18 to 6"
    }
  ],
  "consent_validity_flag": "AT_RISK",
  "consent_validity_reason": "Load score 0.78 exceeded threshold 0.65 during closing phase where commitment was recorded.",
  "recommended_action": "SEND_WRITTEN_CONFIRMATION",
  "false_positive_disclaimer": "Cognitive load inference is probabilistic. A flagged call does not constitute a legal finding. Human review is required before any adverse action.",
  "flags": ["REQUIRES_HUMAN_REVIEW", "JARGON_DENSITY_HIGH"],
  "analysis_mode": "heuristic",
  "schema_version": "1.0"
}

Cognitive Load Signals

Linguistic Markers

Signal Type	Example	Weight
`repetition_request`	"Could you repeat that?" / "Say that again?"	0.30
`confusion_phrase`	"I don't understand" / "I'm lost" / "What does that mean?"	0.25
`self_correction`	"Wait, I mean... actually..."	0.15
`clarification_request`	"So what you're saying is...?"	0.20
`jargon_density_spike`	Technical / legal terminology per 50-word window	0.18
`hedge_word_cluster`	"I think", "maybe", "I'm not sure" (3+ in one turn)	0.12

Interaction Dynamic Markers

Signal Type	Threshold	Significance
`turn_imbalance`	Agent:Callee ratio > 3:1	Agent dominating — callee cannot process
`long_silence_gap`	> 2 500 ms	Callee processing delay — indicates high extraneous load
`participation_drop`	Callee turns drop ≥ 40% in closing phase	Cognitive withdrawal

Load Levels

Load Score	Level	Recommended Action
< 0.35	`LOW`	`PROCEED`
0.35–0.64	`MEDIUM`	`FLAG_FOR_REVIEW`
0.65–0.84	`HIGH`	`SEND_WRITTEN_CONFIRMATION`
≥ 0.85	`CRITICAL`	`REPEAT_CALL_WITH_SIMPLER_SCRIPT`

Flag	Trigger	Meaning
`CONSENT_VALID`	Load < 0.65 during closing	Caller was processing normally when consenting
`CONSENT_AT_RISK`	Load ≥ 0.65 during closing	Caller may have consented under cognitive strain
`CONSENT_UNKNOWN`	Closing phase not identifiable	Transcript structure too short to assess

[!CAUTION] CONSENT_AT_RISK does not mean consent is invalid. It flags the call for human review and recommends sending written confirmation. Never use this flag as a standalone legal determination.

Show full SKILL.md (241 more words)Show less

Command-Line Reference

usage: monitor_cognitive_load.py [-h] --transcript TRANSCRIPT
                                 [--threshold THRESHOLD]
                                 [--dry-run]
                                 [--out OUT]

options:
  --transcript   Path to the transcript JSON file (required)
  --threshold    Load score above which level is HIGH (default: 0.65)
  --dry-run      Analyse without side effects
  --out          Write report JSON to this path (default: stdout)

Integration with CALL-E

Insert as a post-call QA step in any pipeline where consent or commitment is recorded:

[call ends] → [transcribe] → [monitor_cognitive_load.py]
                                        ↓
                   load=HIGH → send written confirmation email
                   load=CRITICAL → schedule follow-up call with simplified script

Combine with client-persona-profiler: Analytical (C) and Steady (S) callers have lower jargon tolerance — flag their calls at a lower threshold.

Privacy & Safety

Reports contain copied transcript evidence and script-patch text and may contain private data. Keep real-input reports local and access-controlled; use synthetic inputs for examples and tests. Do not publish reports without review.
The separate validate_load_report.py check is not automatically run before writing and is not a complete PII redactor or privacy guarantee.
The consent-validity flag is advisory only. A human must review before any regulatory or legal action.

Full safety reference: references/safety.md

Expected Outcomes & Metrics

The following numbers are unvalidated design targets, not measured results.

Metric	Expected Target	Notes
Latency	< 50ms per transcript	Evaluates locally without LLM dependencies.
TPR (True Positive Rate)	> 85%	Identifies cognitive strain in human-annotated datasets.
FPR (False Positive Rate)	< 10%	Some benign clarification requests may be flagged.

Limitations & Known Constraints

Text-Only Modality: Cannot detect sighs, actual silence duration, or exasperated tone. Silence and load fields are text-based proxies, not acoustic measurements.
Prototype options: --threshold is currently accepted but unused; reported levels use built-in constants. Short transcripts and a CONSENT_VALID label do not prove that a closing phase or consent occurred.
ASR Dependency: If the ASR mistranscribes "I'm lost" as "I boss", the signal is missed.
Language Bias: Heuristics are currently calibrated exclusively for English.

Files

skills/call-cognitive-load-monitor/
├── SKILL.md
├── scripts/
│   ├── monitor_cognitive_load.py      ← Main analysis runner
│   ├── validate_load_report.py        ← Output schema validator
│   └── test_cognitive_load.py         ← Test suite (50+ assertions)
└── references/
    ├── example-transcript.json        ← High-load example transcript
    ├── examples.md                    ← Usage examples
    ├── research-papers.md             ← Full citations
    └── safety.md                      ← Consent-validity ethics guide

Files

SKILL.md and 7 other files (scripts, references) in skills/call-cognitive-load-monitor of CALLE-AI/awesome-phone-call-agents.

SKILL.md
references/example-transcript.json
references/examples.md
references/research-papers.md
references/safety.md
scripts/monitor_cognitive_load.py
scripts/test_cognitive_load.py
scripts/validate_load_report.py

Open the folder on GitHubat commit 38d4118

Compare with similar skills

Call Cognitive Load Monitor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Call Cognitive Load Monitor compared with similar skills
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Call Cognitive Load Monitor this skillCALLE-AI/awesome-phone-call-agents	107	—	~2.3k	Automated safety check: Pass	MIT	yesterday
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Questions about Call Cognitive Load Monitor

What does Call Cognitive Load Monitor do?

Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive…. Call Cognitive Load Monitor is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental CALL-E transcript heuristics for repetition, confusion phrases and conversational proxies, with advisory scores and script suggestions for human review; not a cognitive assessment or consent determination.

How do I install Call Cognitive Load Monitor in Claude Code?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a claude-code`. Or copy the skill folder (skills/call-cognitive-load-monitor in CALLE-AI/awesome-phone-call-agents) into .claude/skills/call-cognitive-load-monitor in your project. Claude Code loads it when a task matches its description.

How do I install Call Cognitive Load Monitor in Codex?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a codex`. Or copy the skill folder (skills/call-cognitive-load-monitor in CALLE-AI/awesome-phone-call-agents) into .agents/skills/call-cognitive-load-monitor in your project. Codex loads it when a task matches its description.

Can I use Call Cognitive Load Monitor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-cognitive-load-monitor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/call-cognitive-load-monitor, .gemini/skills/call-cognitive-load-monitor, .github/skills/call-cognitive-load-monitor and .opencode/skills/call-cognitive-load-monitor in your project.

What does Call Cognitive Load Monitor need to run?

Going by SKILL.md and its folder, Call Cognitive Load Monitor needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Call Cognitive Load Monitor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Call Cognitive Load Monitor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Call Cognitive Load Monitor use?

Call Cognitive Load Monitor is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Call Cognitive Load Monitor use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Call Cognitive Load Monitor?

Skills that share tags, products or a category with Call Cognitive Load Monitor: Baoyu Youtube Transcript (JimLiu/baoyu-skills, 27k stars), Youtube Transcript (browser-act/skills, 6.1k stars), Youtube Transcript (sickn33/agentic-awesome-skills, 47k stars) and Qdrant Monitoring (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Call Cognitive Load Monitor?

CALLE-AI (a GitHub organization) maintains it in CALLE-AI/awesome-phone-call-agents, which has 107 GitHub stars. The repository holds 101 skills in this directory. The repository was last updated on October 10, 2026.

Source: CALLE-AI/awesome-phone-call-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Call Cognitive Load Monitor

Facts

At a glance

What it does

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

call-cognitive-load-monitor

Why This Skill Exists

Research Scope

Quick Start

Validate output schema

Input

Output — Overload Report

Cognitive Load Signals

Linguistic Markers

Interaction Dynamic Markers

Load Levels

Consent Validity Flags

Command-Line Reference

Integration with CALL-E

Privacy & Safety

Expected Outcomes & Metrics

Limitations & Known Constraints

Files

Files

Compare with similar skills

Similar skills

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Questions about Call Cognitive Load Monitor