Baoyu Youtube Transcript
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Downloads YouTube video transcripts/subtitles and cover images by URL or video ID.
Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair…
MITAuto-check passed
Install Call Apology Effectiveness Auditor
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-apology-effectiveness-auditor .claude/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.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/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .claude/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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 install https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditorType 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.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ 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-apology-effectiveness-auditor .agents/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .agents/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ 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-apology-effectiveness-auditor .cursor/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .cursor/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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 https://github.com/CALLE-AI/awesome-phone-call-agents.git --path skills/call-apology-effectiveness-auditor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ 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-apology-effectiveness-auditor .gemini/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.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/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .gemini/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditorInstalls 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).
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ 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-apology-effectiveness-auditor .github/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.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/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .github/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-apology-effectiveness-auditor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ 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-apology-effectiveness-auditor .opencode/skills/call-apology-effectiveness-auditor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "call-apology-effectiveness-auditor" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-apology-effectiveness-auditor into .opencode/skills/call-apology-effectiveness-auditor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-apology-effectiveness-auditor", 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-apology-effectiveness-auditor- GitHub stars
- 107
- Token cost
- ~1.3k tokens
- SKILL.md length
- 607 words
- Files
- 10 (incl. scripts, references)
- Skills in repo
- 101
- Repo updated
- First seen
- Licence
- MIT
At a glance
Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair…
- SKILL.md covers When To Use, When Not To Use, Workflow and Scientific Foundation, plus 1 more section
- Runs Python scripts from its folder; calls python3
What it does
Call Apology Effectiveness Auditor is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair, explanation, regret, forbearance, forgiveness request) with rote/empathic/explanatory typology, plus an apology-protocol goal template. It is not a sincerity measure, relationship counseling, or authorization to act automatically.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts and reference files (for example `references/example-transcript-non-apology.json`, `references/example-transcript-rote.json` and `references/example-transcript-unaddressed.json`).
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-apology-effectiveness-auditor”
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 2 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 Apology Effectiveness Auditor loads about 1.3k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 607 words of instructions outside code blocks.
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). 607 words, ~1,337 tokens.
Download SKILL.mdSave it as
.claude/skills/call-apology-effectiveness-auditor/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- call-apology-effectiveness-auditor
- description
- Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair, explanation, regret, forbearance, forgiveness request) with rote/empathic/explanatory typology, plus an apology-protocol goal template. It is not a sincerity measure, relationship counseling, or authorization to act automatically.
- license
- MIT
call-apology-effectiveness-auditor
"I'm sorry you feel that way" is not an apology. It is a complaint about the person who had one.
Apology effectiveness is component-decomposable: research on real conflict apologies shows that a working apology is not one utterance but a stack of parts - acknowledgment of responsibility, concrete repair, brief explanation, expressed regret, forbearance, and (optionally) a request for forgiveness - and that acknowledgment carries the most weight. When a callee raises a grievance on a call, an agent that says only "I'm sorry about that" and moves on to scheduling has produced a rote apology: audible, and empty. This skill detects the grievance and grades the recovery response against that component stack.
When To Use
- after support, collections, or clinic calls where the callee may have raised a grievance (delay, broken promise, repeated contact)
- in QA pipelines, to find calls where the recovery was rote, deflecting, or missing entirely
- before recovery callbacks, to craft an apology-protocol goal that names the miss and offers concrete repair
When Not To Use
- as a measure of sincerity or relationship health; the components are surface-lexical markers - an agent can say "that's on us" with no feeling behind it
- to force apologies on every failure; sometimes the right posture is no apology at all, because the agent cannot own fault it does not have
- during a call; strictly post-call analysis plus pre-call goal crafting
- on non-English transcripts; the lexicons are English-only
Workflow
Audit a finished call
python3 scripts/apology_effectiveness_auditor.py analyze \
--transcript path/to/call-result.jsonReads the real get_call_run result shape ({status, result: {transcript}})
or the flat fixture shape used by sibling skill fixtures. Emits a card:
grievance_turn_index/grievances_total/grievance_evidence: where the first grievance was voiced (callee turns only), how many grievance-bearing callee turns exist, and the masked evidence sentenceapology_detected/apology_evidence: whether any agent turn from the grievance onward contains an apology, and the masked sentencecomponents_present: the six-component markers found in the graded window (the apology sentence plus the following agent turn, since explanations often arrive one turn late)typology:rote/empathic/explanatory(empathic > explanatoryrote)
verdict:EFFECTIVE_APOLOGY(acknowledgment plus repair or explanation) /PARTIAL_APOLOGY/NON_APOLOGY(deflection override) /GRIEVANCE_UNADDRESSED/NO_GRIEVANCE, plusunclearpaths (empty transcript, fewer than two turns)
Only the FIRST grievance's response window is graded; later grievances
are counted in grievances_total but their responses are not separately
graded.
Show full SKILL.md (230 more words)Show less
Craft the apology-protocol goal
python3 scripts/apology_effectiveness_auditor.py craft --scenario apology-protocolEmits the plan_call inputs JSON whose goal implements the protocol: acknowledge the specific miss, offer concrete repair, explain briefly only after acknowledging, and never use "sorry you feel that way" constructions.
Scientific Foundation
| Research | Relevance |
|---|---|
| An Exploration of the Structure of Effective Apologies (Lewicki, Polin & Lount, Negotiation and Conflict Management Research 9(1), 2016, doi 10.1111/ncmr.12073) | Empirically ranks six apology components; acknowledgment of responsibility carries the most weight - our EFFECTIVE threshold requires it |
| A Critical Review of Apology in AI Systems (Harland et al., arXiv 2412.15787, 2024) | First synthesis of AI apology research: apologies are routine in chatbots but rarely designed - motivates auditing them on calls |
| Who's Sorry Now: User Preferences Among Rote, Empathic, and Explanatory Apologies from LLM Chatbots (Ashktorab et al., arXiv 2507.02745, 2025) | Users distinguish apology TYPES; preference data grounds our rote/empathic/explanatory typology |
Citation notes recorded during verification: all three web-verified 2026-10-01. CORRECTION recorded: the frequently cited "2014 component structure of interpersonal apologies" title does not exist - the empirical six-component study is the 2016 NCMR paper by Lewicki, Polin & Lount (not "Polite").
Differences from sibling skills
call-disfluency-stress-profilermeasures stress markers as they happen; this skill grades the recovery RESPONSE after a grievance is voiced.call-repair-sequence-auditorscores micro-level conversational repair (huh/repeat/rephrase); this skill scores macro-level relational recovery.call-agent-commitment-trackertracks future obligations; a repair offer is graded for FORM here and tracked as an OBLIGATION there.
© CALLE-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (scripts, references) in skills/call-apology-effectiveness-auditor of CALLE-AI/awesome-phone-call-agents.
- SKILL.md
- references/example-goal.txt
- references/example-transcript-non-apology.json
- references/example-transcript-rote.json
- references/example-transcript-unaddressed.json
- references/example-transcript.json
- references/examples.md
- references/safety.md
- scripts/apology_effectiveness_auditor.py
- scripts/test_apology_effectiveness_auditor.py
Open the folder on GitHubat commit 38d4118
Compare with similar skills
Call Apology Effectiveness Auditor 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Call Apology Effectiveness Auditor this skillCALLE-AI/awesome-phone-call-agents | 107 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Baoyu Youtube TranscriptJimLiu/baoyu-skills | 27k | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Youtube Transcriptbrowser-act/skills | 6.1k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Youtube Transcriptsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Transcription0xsline/OpenChatCut | 2.2k | 1 repos | ~1.1k | Automated safety check: Pass | AGPL-3.0 | |
| Threat Detectionalirezarezvani/claude-skills | 28k | — | ~3.5k | Automated safety check: Pass | MIT |
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Questions about Call Apology Effectiveness Auditor
What does Call Apology Effectiveness Auditor do?
Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair…. Call Apology Effectiveness Auditor is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline heuristic CALL-E transcript skill that detects callee grievances and grades the agent's response against the six-component apology effectiveness taxonomy (acknowledgment, repair, explanation, regret, forbearance, forgiveness request) with rote/empathic/explanatory typology, plus an apology-protocol goal template.
How do I install Call Apology Effectiveness Auditor in Claude Code?
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a claude-code`. Or copy the skill folder (skills/call-apology-effectiveness-auditor in CALLE-AI/awesome-phone-call-agents) into .claude/skills/call-apology-effectiveness-auditor in your project. Claude Code loads it when a task matches its description.
How do I install Call Apology Effectiveness Auditor in Codex?
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-apology-effectiveness-auditor -a codex`. Or copy the skill folder (skills/call-apology-effectiveness-auditor in CALLE-AI/awesome-phone-call-agents) into .agents/skills/call-apology-effectiveness-auditor in your project. Codex loads it when a task matches its description.
Can I use Call Apology Effectiveness Auditor 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-apology-effectiveness-auditor -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-apology-effectiveness-auditor, .gemini/skills/call-apology-effectiveness-auditor, .github/skills/call-apology-effectiveness-auditor and .opencode/skills/call-apology-effectiveness-auditor in your project.
What does Call Apology Effectiveness Auditor need to run?
Going by SKILL.md and its folder, Call Apology Effectiveness Auditor needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Call Apology Effectiveness Auditor 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 Apology Effectiveness Auditor 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 Apology Effectiveness Auditor use?
Call Apology Effectiveness Auditor 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 Apology Effectiveness Auditor use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Call Apology Effectiveness Auditor?
Skills that share tags, products or a category with Call Apology Effectiveness Auditor: 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 Transcription (0xsline/OpenChatCut, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Call Apology Effectiveness Auditor?
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.