FAQ
a-fable-of-codexes is a Claude Code plugin with 1 hand-picked skill for automation work, indexed on Flowy. Install it with the command on its page. It includes campaign-conductor. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
$ npx -y skills add jvogan/a-fable-of-codexes --agent claude-code
Repo: jvogan/a-fable-of-codexes
Claude Code skills that make Claude (Fable, or Opus when Fable is unavailable) the conductor of an AI worker fleet. The conductor surveys and plans, dispatches many parallel OpenAI Codex CLI workers for implementation and Claude Opus agents for design judgment, then integrates, reviews, and verifies what comes back.
One session directs the whole effort: workers spend their own context on implementation while the conductor's stays free for judgment, git worktrees let many writers land in parallel without collisions, and campaign state lives in the repo so any later session resumes mid-campaign without setup.
Runs a project as an orchestrated campaign.
assets/campaign-hq/ into docs/campaign-hq/: CAMPAIGN.md for the plan
and fleet table, LEARNINGS.md for distilled lessons, preferences.md for
worker routing, and schemas/worker-result.json for reports. It also adds a
pointer to the project's CLAUDE.md so later sessions resume from repo state.preferences.md, and persist across sessions.references/ and load only when needed.examples/campaign-hq/ shows the state files
mid-campaign, including a worked worker brief and the report schema.
The panels are worked examples. Any capable worker can lead, integrate, or review, and a campaign composes whatever shape the work needs.
Squads nest the fan-out: a squad lead (Opus or Codex) dispatches its own parallel workers, integrates their branches, and hands the conductor one verified branch. Tested end to end both ways: a spawned Opus lead ran Codex workers in parallel worktrees, each landing its own commit, and a Codex lead fanned out its native subagents inside one workspace.
flowchart TD
C[Fable conductor] -->|sub-goal briefs| S1[Squad lead ยท Opus]
C --> S2[Squad lead ยท Codex]
S1 --> A1[Codex] & A2[Codex] & A3[Codex]
S2 --> B1[Codex] & B2[Codex] & B3[Codex]
A1 & A2 & A3 --> I1[campaign/search<br>integration branch]
B1 & B2 & B3 --> I2[campaign/billing<br>integration branch]
I1 --> V[Conductor merges,<br>re-verifies]
I2 --> V
V --> M[(main)]
Campaign state lives in the project, so any later session resumes it:
docs/campaign-hq/
โโโ CAMPAIGN.md plan, phases, fleet table
โโโ LEARNINGS.md standing rules + dispatch log
โโโ preferences.md worker routing, permission envelope
โโโ briefs/ one file per dispatch
โโโ out/ collected worker reports
โโโ schemas/ worker-result.json
npx skills add jvogan/a-fable-of-codexes --skill campaign-conductor
or manually:
git clone --depth 1 https://github.com/jvogan/a-fable-of-codexes.git /tmp/afoc
cp -r /tmp/afoc/skills/campaign-conductor ~/.claude/skills/
Install the skill, then say in any project:
start a campaign
Claude bootstraps docs/campaign-hq/, sizes the plan to the project, and
begins dispatching workers. From then on, every session in that repo picks up
the campaign automatically. Direct it in plain language:
preferences.md)Claude Code. The skill uses the Agent and Workflow tools.
OpenAI Codex CLI (github.com/openai/codex).
Install with npm install -g @openai/codex (or brew install codex), then
run codex login. ChatGPT-plan auth consumes plan usage and limits vary by
plan; API-key auth is token-priced. Size worker waves to your available
limits and spend tolerance. Set the default worker model and reasoning
effort in ~/.codex/config.toml, for example:
model = "gpt-5.6-sol"
model_reasoning_effort = "high"
Reasoning runs a ladder (low, medium, high, xhigh, max, ultra),
and the model ships in frontier, balanced, and fast variants. high on the
frontier model is a sound default; reserve max/ultra for the hardest
architecture and debugging. Override per task in plain language ("use ultra
Codex for this wave", "send the mechanical refactor to the fast model"): the
conductor writes the request to preferences.md, where it persists.
Without Codex installed, the skill runs Claude-only fleets: Sonnet workers take the implementation role, Opus keeps design and squad-lead duty, and the briefs, worktrees, squads, and reports stay the same.
Codex plugin for Claude Code (optional,
github.com/openai/codex-plugin-cc).
Adds /codex:review, /codex:adversarial-review, and background-delegation
slash commands for single interactive tasks. Install inside Claude Code:
/plugin marketplace add openai/codex-plugin-cc
/plugin install codex@openai-codex
python3 scripts/validate.py
npx --yes skills add . --list
Checks every skill against the
Agent Skills spec: frontmatter
fields, name format, and description length, plus this repo's 500-line body
limit and relative-link integrity. The skills command verifies that the
package is discoverable by the installer. CI runs both commands on every push
and pull request.
MIT
.github/
workflows/
validate.yml
.gitignore
AGENTS.md
assets/
banner.png
patterns.svg
social-preview.jpg
CLAUDE.md
CONTRIBUTING.md
examples/
campaign-hq/
briefs/
result-highlighting.md
CAMPAIGN.md
LEARNINGS.md
out/
.gitkeep
ranking.json
preferences.md
schemas/
worker-result.json
LICENSE
README.md
scripts/
validate.py
skills/
campaign-conductor/
assets/
campaign-hq/
briefs/
.gitkeep
CAMPAIGN.md
LEARNINGS.md
out/
.gitkeep
preferences.md
schemas/
worker-result.json
references/
codex-dispatch.md
fleet-operations.md
review-gates.md
squads.md
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