glimmer-delegation

SkillProductivity

Delegates tasks to a locally served Muse Glimmer via ollama. Use when delegation-core selects glimmer or the prompt must not leave the machine.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the glimmer-delegation skill

What this skill tells your AI

The instructions your AI receives, as published by athola/claude-night-market in plugins/conjure/skills/glimmer-delegation/SKILL.md and read by ahel’s review.

Table of Contents

  • Overview
  • When To Use
  • When NOT To Use
  • Prerequisites
  • Quick Start
  • Smart Delegation
  • Glimmer-Specific Details
  • Exit Criteria

Glimmer Delegation

Overview

Glimmer is Meta's Muse Glimmer served locally through ollama, so a delegation to it spends no quota and sends no prompt off the machine. It is the last entry in the candidate order for the same reason it is the safe one: a local 30B model is slower and weaker than any of the network providers ahead of it.

When To Use

  • delegation-core selected glimmer for the task
  • Every network provider is exhausted and the work still has to happen
  • The prompt must not leave the machine, whatever the cost in quality

When NOT To Use

  • The task needs the strongest available model. Glimmer is the floor, not a peer of the network providers
  • ollama list shows no muse-glimmer:30b. A registered provider whose model was never pulled fails at the first delegation, not at registration

Prerequisites

Installation

curl -fsSL https://ollama.com/install.sh | sh
ollama pull muse-glimmer:30b

Both steps are required. Installing ollama registers the binary and pulls nothing, so ollama --version answering is not evidence that a delegation will succeed.

Authentication

None. auth_method is "none" and the auth probe is empty, because a local server has no credential to check.

Quick Start

Using the shared delegation executor

uv run python scripts/delegation_executor.py glimmer "Summarize" \
  --files src/

Through the Makefile

make -C plugins/conjure delegate-glimmer PROMPT='Summarize' FILES='src/'

Direct CLI usage

ollama run muse-glimmer:30b "Explain this module"

Smart Delegation

glimmer carries priority=80, the highest number in the registry, which places it last in the candidate order. It declares no model ids, because the model is fixed by the subcommand rather than chosen per call.

Glimmer-Specific Details

PropertyValue
Binaryollama
Headless formollama run muse-glimmer:30b
Prompt deliverystdin
File contextinlined into the prompt
Version probeollama --version
Auth probenone
Output format flag--format
Model flagnone

Read off ollama run --help at 0.13.1: the usage line is ollama run MODEL [PROMPT] [flags], so the model is positional and is carried by the subcommand. The flag list has no --model, which is why this service declares model_flag=None; passing one exits 1 on an unknown flag. --format string is documented there and is the reason output_format_flag is --format rather than the registry default --output-format, which the same CLI rejects.

No temperature flag is declared. ollama run --help documents none, and inventing one is the error class install_hint and login_hint already guard against.

Exit Criteria

  • ollama resolves on PATH and answers ollama --version
  • ollama list includes muse-glimmer:30b before a task is delegated; an absent model stops execution with the pull command rather than failing inside the delegation
  • The built command is ollama run muse-glimmer:30b with the prompt on stdin and no prompt flag
  • No --model flag appears in the built command
  • Output saved to delegations/glimmer/YYYYMMDD_HHMMSS.md
  • This skill ran because delegation-core selected glimmer, or because the prompt was required to stay local

Signals

GitHub stars
337
Forks
34
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
glimmer-delegation
Source
github.com/athola/claude-night-market