Iron Proxy Gateway for NanoClaw
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
Offline experimental spoken-code coordination illustration for CALL-E workflows.
Install Call Attest Challenge Auth
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill call-attest-challenge-auth -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-attest-challenge-auth --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-attest-challenge-auth .claude/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .claude/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-authType 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-attest-challenge-auth -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-attest-challenge-auth --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-attest-challenge-auth .agents/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .agents/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-auth -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-attest-challenge-auth --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-attest-challenge-auth .cursor/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .cursor/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-auth--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-attest-challenge-auth -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents call-attest-challenge-auth --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-attest-challenge-auth .gemini/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .gemini/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-authInstalls 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-attest-challenge-auth -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-attest-challenge-auth .github/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .github/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-auth -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-attest-challenge-auth --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-attest-challenge-auth .opencode/skills/call-attest-challenge-auth && 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-attest-challenge-auth" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/call-attest-challenge-auth into .opencode/skills/call-attest-challenge-auth/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "call-attest-challenge-auth", 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-attest-challenge-auth- GitHub stars
- 107
- Token cost
- ~1.1k tokens
- SKILL.md length
- 496 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 101
- Repo updated
- First seen
- Licence
- MIT
At a glance
Offline experimental spoken-code coordination illustration for CALL-E workflows.
- Tasks that involve Secrets management
- SKILL.md covers When To Use, When Not To Use, Workflow and Why a spoken code and not an…, plus 2 more sections
- Runs Python scripts from its folder; calls python3; needs CALL_ATTEST_SECRET
What it does
Call Attest Challenge Auth is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental spoken-code coordination illustration for CALL-E workflows. Generates a nonce and HMAC-derived short code from an environment-variable secret, then fuzzy-matches a supplied transcript against the supplied expected code. An optional local JSONL ledger flags recorded nonce reuse. This is not identity authentication, a secure replay guarantee or permission to disclose sensitive information.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/example-transcript-mismatch.json`, `references/example-transcript.json` and `references/examples.md`).
It sits in DevOps & Cloud, covering Secrets management. The repository describes itself as: Portable phone-call Agent Skills, apps, examples, adapters, and scheduler recipes for AI agents. The licence is MIT.
When your agent uses it
- Tasks that involve Secrets management
Example prompts
- “/call-attest-challenge-auth”
Requirements
- Python 3
- A credential in CALL_ATTEST_SECRET
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 these keys or tokens, usually read from environment variables:
CALL_ATTEST_SECRET
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Call Attest Challenge Auth loads about 1.1k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 110 tokens; SKILL.md has 496 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). 496 words, ~1,139 tokens.
Download SKILL.mdSave it as
.claude/skills/call-attest-challenge-auth/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- call-attest-challenge-auth
- description
- Offline experimental spoken-code coordination illustration for CALL-E workflows. Generates a nonce and HMAC-derived short code from an environment-variable secret, then fuzzy-matches a supplied transcript against the supplied expected code. An optional local JSONL ledger flags recorded nonce reuse. This is not identity authentication, a secure replay guarantee or permission to disclose sensitive information.
- license
- MIT
call-attest-challenge-auth
An offline spoken-code coordination experiment.
This companion to dialtone-handshake generates an illustrative short code
derived from a pre-shared secret and checks a supplied transcript for a
fuzzy match. A matching code is only a text-level coordination signal;
recorded nonce reuse may indicate replay or an operator error. Neither
result authenticates a counterparty or authorizes sensitive disclosure.
When To Use
- to rehearse a coordination exchange between consenting test participants
- to flag a challenge recorded in the optional local nonce ledger
- to generate the challenge goal for
plan_calland the expected code to verify against
When Not To Use
- to recognize whether the other end is AI at all; use
dialtone-handshake - to authenticate humans; spoken codes leak through the audio channel to anyone listening
- against a determined man-in-the-middle who can hear and relay the code; this protocol does not defend against that (see safety.md)
- to authorize sensitive disclosure or any financial, medical, employment, safety or other consequential operation, even when the label is VERIFIED
Workflow
Craft the challenge
CALL_ATTEST_SECRET=<shared secret> python3 scripts/attest_auth.py craft --scenario attestation-call --language enReads the secret from the environment (never the command line), generates a nonce, derives the 4-token code (2 colors + 1 number word + 2 digits) from HMAC-SHA256(secret, nonce), and emits the plan_call goal that speaks the nonce. The expected code travels in the craft output only - keep it local.
Verify a finished call
python3 scripts/attest_auth.py verify --transcript path/to/call-result.json --nonce <nonce> --expected-code "BLUE ORANGE SEVEN 42" --ledger nonce-ledger.jsonlChecks that an agent turn spoke the nonce and a callee turn replied; normalizes tokens (digit strings expand to digit words, FOR/TO/WON confusables fold) and fuzzy-matches with edit distance <= 1 per token in order. Emits a card:
attestation: VERIFIED / FAILED_NO_RESPONSE (reason challenge_not_spoken or no_response_after_challenge) / FAILED_MISMATCH / REPLAY_SUSPECTEDevidence: masked spans with kinds challenge_spoken and response_heardrecommended_action: accept_and_continue / reject_caller / investigate_replay- With
--ledger: a verified nonce is appended to the JSONL ledger; a nonce already present yields REPLAY_SUSPECTED.
VERIFIED and accept_and_continue are legacy output labels for an advisory
fuzzy match, not authentication decisions. Without a ledger reuse is not
checked. The local ledger is sequential-only, not a durable or concurrent
replay defense. Inputs must come from a trusted operator; empty values and
altered transcripts are not a security boundary.
Show full SKILL.md (151 more words)Show less
Why a spoken code and not an audio watermark
This example uses text-level spoken-code matching because it needs no audio model. It does not benchmark watermarking or spoken codes over telephone networks, and makes no claim that AudioSeal or SilentCipher necessarily fails on the PSTN. Audio quality and transcription errors remain limitations.
Scientific Foundation
| Research | Relevance |
|---|---|
| Proactive Detection of Voice Cloning with Localized Watermarking / AudioSeal (ICML 2024, arXiv 2401.17264) | Background on localized audio watermarking; not implemented or evaluated here |
| SilentCipher: Deep Audio Watermarking (Interspeech 2024, arXiv 2406.03822) | Background on deep audio watermarking; not implemented or evaluated here |
Neither watermarking scheme is used here. These references do not validate this short-code design or establish telephone-band performance.
Differences from sibling skills
dialtone-handshakeproposes an agent-to-agent handshake; this skill illustrates a separate offline spoken-code check without switching modes.call-fraud-shielddetects scam patterns in conversations; this skill provides an advisory coordination signal, not counterparty authentication.
© 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 6 other files (scripts, references) in skills/call-attest-challenge-auth of CALLE-AI/awesome-phone-call-agents.
- SKILL.md
- references/example-transcript-mismatch.json
- references/example-transcript.json
- references/examples.md
- references/safety.md
- scripts/attest_auth.py
- scripts/test_attest_auth.py
Open the folder on GitHubat commit 38d4118
Compare with similar skills
Call Attest Challenge Auth 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 Attest Challenge Auth this skillCALLE-AI/awesome-phone-call-agents | 107 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.5k | Automated safety check: Notes | Apache-2.0 | |
| Env Var Conventionssgl-project/sglang | 37k | 2 repos | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Mac Fleet Maintenancesteipete/agent-scripts | 7.3k | — | ~4.8k | Automated safety check: Pass | MIT | |
| Add Config Env Varbaserow/baserow | 6.1k | — | ~1.1k | Automated safety check: Pass | Custom licence |
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Related
Categories
Questions about Call Attest Challenge Auth
What does Call Attest Challenge Auth do?
Offline experimental spoken-code coordination illustration for CALL-E workflows. Call Attest Challenge Auth is an agent skill from CALLE-AI/awesome-phone-call-agents. Offline experimental spoken-code coordination illustration for CALL-E workflows.
When should I use Call Attest Challenge Auth?
Call Attest Challenge Auth fits situations like: tasks that involve Secrets management.
How do I install Call Attest Challenge Auth in Claude Code?
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-attest-challenge-auth -a claude-code`. Or copy the skill folder (skills/call-attest-challenge-auth in CALLE-AI/awesome-phone-call-agents) into .claude/skills/call-attest-challenge-auth in your project. Claude Code loads it when a task matches its description.
How do I install Call Attest Challenge Auth in Codex?
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill call-attest-challenge-auth -a codex`. Or copy the skill folder (skills/call-attest-challenge-auth in CALLE-AI/awesome-phone-call-agents) into .agents/skills/call-attest-challenge-auth in your project. Codex loads it when a task matches its description.
Can I use Call Attest Challenge Auth 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-attest-challenge-auth -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-attest-challenge-auth, .gemini/skills/call-attest-challenge-auth, .github/skills/call-attest-challenge-auth and .opencode/skills/call-attest-challenge-auth in your project.
What does Call Attest Challenge Auth need to run?
Going by SKILL.md and its folder, Call Attest Challenge Auth needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named CALL_ATTEST_SECRET. Our summary lists: Python 3; A credential in CALL_ATTEST_SECRET.
Does Call Attest Challenge Auth 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 Attest Challenge Auth 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 Attest Challenge Auth use?
Call Attest Challenge Auth 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 Attest Challenge Auth use?
About 1.1k tokens (SKILL.md is roughly 4.6k 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 1.9k tokens, read only when the agent opens those files.
What are the alternatives to Call Attest Challenge Auth?
Skills that share tags, products or a category with Call Attest Challenge Auth: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), LangBot Deployment Guide (langbot-app/LangBot, 18k stars), Env Var Conventions (sgl-project/sglang, 37k stars) and Mac Fleet Maintenance (steipete/agent-scripts, 7.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Call Attest Challenge Auth?
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.