How do I install the Capacity Backfill Cascade skill?

Run npx skillmds@latest add calle-ai/capacity-backfill-cascade in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Capacity Backfill Cascade safe to use?

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Which AI agents work with Capacity Backfill Cascade?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Capacity Backfill Cascade free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Capacity Backfill Cascade?

CALLE-AI (@calle-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Capacity Backfill Cascade by calle-ai

Name: Capacity Backfill Cascade
Author: CALLE-AI

Capacity Backfill Cascade

Confirm bookings and backfill freed capacity from a waitlist using CALL-E phone calls. Use when an agent needs to recover cancelled reservations, fill released slots, or run consent-based confirm-then-cascade call workflows safely.

CALLE-AI Updated Sep 17, 2026

File contents

capacity-backfill-cascade

A phone-call workflow pattern for capacity recovery: confirm upcoming bookings, and when a guest cancels, offer the freed slot to waitlist candidates in priority order until one accepts. Works for restaurants, tours, classes, and any booking system with a waitlist.

When to use

An upcoming booking list where cancellations free capacity
A waitlist of guests who consented to receive offers
A need to recover lost capacity without staff dialing

Prerequisites

Python 3.10+ with the reference app installed: cd apps/python/table-rescue && pip install -e .
CALL-E CLI installed and logged in (live mode only): calle auth login --base-url https://seleven-mcp-sg.airudder.com --channel openagent_oauth

Workflow

Prepare two JSONL inputs (schemas in references/io-schemas.md): reservations and waitlist. Every record needs an explicit consent flag; non-consented records are never dialled.
Run a dry-run first and inspect the audit and report: python scripts/run_cascade.py --data-dir <dir> --state-dir <dir>
Only when the plan looks right, place real calls with an explicit budget: python scripts/run_cascade.py --data-dir <dir> --state-dir <dir> --live --max-calls 6
Review the masked staff report at state/runs/<run-id>/report.md; escalate no-answer and error targets manually.

Safety rules

Dry-run is the default; live requires --live.
Never exceed the call budget; the engine stops before dialing when the budget is out.
Never dial a record without consent.
The call goals instruct the agent to identify itself as an automated assistant at the start of every call (disclosure by design).
Reruns with the same run id skip already-dialled targets (duplicate prevention).
Cancel a run with table-rescue cancel --run-id <id>; later runs refuse to dial.
Mask phone numbers in any output you produce; never log full numbers or tokens.
Live destinations must pass region-aware E.164 validation and appear in the operator's authorized_destinations.jsonl allowlist; the run prints a manifest and requires confirmation before the first call.
The MCP origin is pinned; --base-url cannot point anywhere else.
Uncertain outcomes (no answer, unparseable or wrong-family tokens, provider failures) mark the target NEEDS_REVIEW and stop the run; use table-rescue resume after human review.
Out of scope: medical, legal, financial, and emergency content.

References

references/flow.md - phase diagram and decision table
references/io-schemas.md - input and output schemas, OUTCOME protocol
references/calle-cli-mapping.md - how each step maps to CALL-E auth and MCP calls

---name: capacity-backfill-cascadedescription: Confirm bookings and backfill freed capacity from a waitlist using CALL-E phone calls. Use when an agent needs to recover cancelled reservations, fill released slots, or run consent-based confirm-then-cascade call workflows safely.---# capacity-backfill-cascadeA phone-call workflow pattern for capacity recovery: confirm upcoming bookings, and whena guest cancels, offer the freed slot to waitlist candidates in priority order until oneaccepts. Works for restaurants, tours, classes, and any booking system with a waitlist.## When to use- An upcoming booking list where cancellations free capacity- A waitlist of guests who consented to receive offers- A need to recover lost capacity without staff dialing## Prerequisites- Python 3.10+ with the reference app installed: `cd apps/python/table-rescue && pip install -e .`- CALL-E CLI installed and logged in (live mode only): `calle auth login --base-url https://seleven-mcp-sg.airudder.com --channel openagent_oauth`## Workflow1. Prepare two JSONL inputs (schemas in `references/io-schemas.md`): reservations and waitlist. Every record needs an explicit `consent` flag; non-consented records are never dialled.2. Run a dry-run first and inspect the audit and report: `python scripts/run_cascade.py --data-dir <dir> --state-dir <dir>`3. Only when the plan looks right, place real calls with an explicit budget: `python scripts/run_cascade.py --data-dir <dir> --state-dir <dir> --live --max-calls 6`4. Review the masked staff report at `state/runs/<run-id>/report.md`; escalate no-answer and error targets manually.## Safety rules- Dry-run is the default; live requires `--live`.- Never exceed the call budget; the engine stops before dialing when the budget is out.- Never dial a record without consent.- The call goals instruct the agent to identify itself as an automated assistant at the start of every call (disclosure by design).- Reruns with the same run id skip already-dialled targets (duplicate prevention).- Cancel a run with `table-rescue cancel --run-id <id>`; later runs refuse to dial.- Mask phone numbers in any output you produce; never log full numbers or tokens.- Live destinations must pass region-aware E.164 validation and appear in the operator's `authorized_destinations.jsonl` allowlist; the run prints a manifest and requires confirmation before the first call.- The MCP origin is pinned; `--base-url` cannot point anywhere else.- Uncertain outcomes (no answer, unparseable or wrong-family tokens, provider failures) mark the target NEEDS_REVIEW and stop the run; use `table-rescue resume` after human review.- Out of scope: medical, legal, financial, and emergency content.## References- `references/flow.md` - phase diagram and decision table- `references/io-schemas.md` - input and output schemas, OUTCOME protocol- `references/calle-cli-mapping.md` - how each step maps to CALL-E auth and MCP calls

Frequently asked questions