exception-resolution-calls

exception-resolution-calls is a skill for Claude Code, Codex from CALLE-AI/awesome-phone-call-agents. It costs 77 tokens per session (2,997 once invoked), scanned A, original, MIT.

A bounded phone workflow for obtaining a missing answer from a person when a business process is stuck. It turns the call into structured evidence and lets policy code decide whether the related record or workflow may advance.

In plain words
What is it for?
Use it to confirm purchase orders, delivery windows, technician acceptance, or other defined facts that must update system state and have a real cost if wrong.
Why use it?
A vague call summary can be mistaken for proof and can change an order, delivery, or job record incorrectly. This separates recording what was said from the business decision about what is allowed to happen next.

Skill for Claude CodeCodex

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

Good fit Use it to confirm purchase orders, delivery windows, technician acceptance, or other defined facts that must update system state and have a real cost if wrong.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls
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 CALLE-AI/awesome-phone-call-agents --skill exception-resolution-calls
Clone the repo
git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents

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 exception-resolution-calls

README.md
[![agentmods](https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls/github.svg)](https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls)
Your own site
<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls/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 exception-resolution-calls

Your own site · 80×15
<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/exception-resolution-calls.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,997 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.
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 $0.00077 $0.02997
Opus 5.5 $0.00031 $0.01199
Sonnet 5.5 $0.00015 $0.00599
Haiku 4.5 $0.00008 $0.00300

Measured 1mo ago against content hash 0fa53f2499bc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

exception-resolution-calls 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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/idempotency_key.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/exception-resolution-calls/SKILL.md · 288 lines

How it starts

The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resolving blocked workflows by phone

When to use this

Use it when three things are true at once:

  1. a workflow is stuck on a fact only a person has ("did you get the order?", "will it ship Friday?", "can you take this job?");
  2. the answer has to change system state, not just get logged;
  3. a wrong answer has a real cost, so "we think they said yes" is not good enough.

Do not use it for open-ended conversations, for anything where the caller must negotiate or commit the business to something, or where no bounded set of questions exists. Those are not exception resolution; they are sales, and they need a human.

The shape of the problem

The tempting design is: call, ask the model what happened, update the record. That design fails in production for a reason worth stating plainly.

Extraction and authority are different jobs. A model is good at turning a messy conversation into structured fields. It is not the right thing to decide whether a purchase order may be closed, because when the evidence is thin it will still return something, and that something becomes a business fact nobody chose.

So split them:

CALL-E                          Your policy code
──────                          ────────────────
holds the conversation          decides what the answer means
extracts strict JSON            re-validates the JSON
reports confidence              can refuse to act on low confidence
never touches state             owns every state transition

Build it in this order

1. Model uncertainty before you model success

Write the result schema first, and give every judgment field an unknown value. This is the single highest-leverage decision in the whole design.

{
  "type": "object",
  "additionalProperties": false,
  "required": ["received", "po_status", "needs_human"],
  "properties": {
    "received": {
      "type": "string",
      "enum": ["yes", "no", "unknown"],
      "description": "Use yes ONLY when they clearly confirm receipt. Use unknown when the answer was hedged, second-hand or unclear — for example 'I think someone in logistics has it'."
    },
    "po_status": {
      "type": "string",
      "enum": ["on_time", "delayed", "blocked", "unknown"],
      "description": "Never infer a status from tone or from a polite acknowledgement."
    },
    "needs_human": {
      "type": "string",
      "enum": ["yes", "no", "unknown"],
      "description": "Use yes when they ask for a person, dispute the record, or raise pricing, payment terms or contract changes."
    }
  }
}

Read the full file on GitHub · 288 lines

Files

What ships with it

5 files 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. 1mo ago First seen · 288 lines · 77 tokens per session scan A 0fa53f2499bc

Subscribe to this mod's changes

exception-resolution-calls is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 2,997 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-15.

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