call-advisor

name

call-advisor

description

Call the premium Fable advisor through Claude Code CLI from Codex for hard judgment, architecture, product thinking, frontend/design critique, and high-stakes decisions. Treat the advisor as the smartest and most expensive local AI. Use when the user asks to call an advisor, consult Fable/Claude, get a second opinion, compare another agent's output, improve design quality, reason through a hard problem, start or resume an advisor session, reuse advisor/Fable session cache, use high thinking/effort, or manage Claude Code background agents while controlling cost. Prefer call-worker for routine implementation, fast code edits, tests, and mechanical cleanup.

Call Advisor

Overview

Use the local claude CLI to call the Fable model as an external advisor with --model fable and an explicit effort level. Keep prompts scoped, set --max-budget-usd, capture the session_id, and resume existing sessions instead of restarting context-heavy work.

Model Role

Treat the advisor as the expensive senior judgment model in this setup:

• Best for hard judgment, ambiguous strategy, architecture tradeoffs, product direction, deep debugging hypotheses, security-sensitive reasoning, prompt/agent design, and frontend/design critique.
• Strong for design taste: visual direction, UX critique, interaction polish, hierarchy, layout, product feel, and "does this look right?" questions.
• Use when being wrong is expensive, when the main Codex agent wants a serious second opinion, or when a design/architecture choice will shape a lot of downstream work.
• Avoid for routine implementation, file-by-file cleanup, straightforward test fixes, bulk edits, or cheap verification. Prefer call-worker for fast worker tasks.

Ask the advisor for advice, critique, options, or a plan more often than for direct edits. When the advisor does produce code, treat it as a proposal and have Codex verify and integrate it.

Quick Start

Prefer the bundled wrapper because it applies the Fable defaults and handles Claude CLI argument ordering:

python3 /path/to/call-advisor/scripts/advisor.py run \
  "Answer in three bullets: what is the narrow next step here?"

Equivalent raw CLI:

claude -p "Answer in three bullets: what is the narrow next step here?" \
  --model fable \
  --effort high \
  --max-budget-usd 0.50 \
  --output-format json \
  --tools ""

Keep the prompt before --tools. In Claude Code --tools is variadic, so flags or prompts placed after it can be consumed as tool names.

Workflow

1. Check availability cheaply:

claude --version
claude --help

If a run returns Not logged in - Please run /login, stop and report that Claude Code auth is missing. Do not spend time debugging the task prompt until authentication is fixed.

2. Start with a narrow, low-budget Fable run:

python3 /path/to/call-advisor/scripts/advisor.py run \
  --max-budget-usd 0.25 \
  "Inspect this issue conceptually. Return: finding, confidence, next action."

3. Read the returned session_id, total_cost_usd, and output_path. Save the session id and output path in your notes or final answer when the user may want continuation.

4. Resume instead of replaying context:

python3 /path/to/call-advisor/scripts/advisor.py run \
  --resume SESSION_ID \
  "Continue from the previous answer. Only expand the second bullet."

Use saved-session resume to reuse cache without remembering the id:

python3 /path/to/call-advisor/scripts/advisor.py last
python3 /path/to/call-advisor/scripts/advisor.py run \
  --resume-last \
  "Continue from the saved advisor session. Check only the naming question."

Use --continue-latest only when the current directory has exactly the recent Claude session you intend to continue. Use --fork-session with --resume or --resume-last when the continuation should branch from the old context without mutating that session.

Effort And Thinking

Claude Code exposes "thinking size" through --effort. Default to high for Fable unless the user asks for a different size.

• low or medium: cheap smoke tests, formatting, tiny checks.
• high: normal Fable sub-agent work.
• xhigh or max: use only for hard reasoning tasks or when the user explicitly asks; raise the budget deliberately.

The wrapper accepts both names:

python3 /path/to/call-advisor/scripts/advisor.py run --thinking high "..."
python3 /path/to/call-advisor/scripts/advisor.py run --effort high "..."

Tools And Permissions

Default to no Claude tools for pure analysis:

--tools ""

For codebase work, explicitly choose the smallest tool surface and directory access required:

python3 /path/to/call-advisor/scripts/advisor.py run \
  --tools "Read,Grep,Glob" \
  --add-dir "$PWD" \
  "Find the likely source file for this bug. Do not edit files."

Allow edits only when the user wants Claude Code to make changes and the worktree can tolerate another agent editing files. State the write scope in the prompt. Do not use --dangerously-skip-permissions unless the user explicitly requests that risk.

Background Agents

Start a Claude Code background agent only for work that can continue independently:

claude --bg "Investigate the failing test and report the smallest fix." \
  --model fable \
  --effort high \
  --max-budget-usd 1.00 \
  --name fable-test-investigation

List agents for the current workspace:

python3 /path/to/call-advisor/scripts/advisor.py agents --cwd "$PWD"

Use background agents sparingly: they are easy to forget and Fable can become expensive.

Output Handling

With --output-format json, capture:

• result: Claude's answer.
• session_id: the id to pass to --resume; the wrapper also saves the latest id.
• total_cost_usd: actual spend reported by Claude Code.
• is_error and api_error_status: error handling.
• output_path: a durable artifact with full stdout/stderr and compact metadata.

If the wrapper prints an error with total_cost_usd: 0 and a login message, report the auth issue. If cost is near or above the budget cap, summarize what was learned and ask before rerunning with a higher cap.

Output Artifacts

Treat wrapper output as an artifact, not just terminal text. By default each non-dry run writes:

$CODEX_HOME/external-agent-outputs/advisor/<timestamp-session-id>/
  summary.json
  stdout.txt
  stderr.txt

Use summary.json after context compaction to recover the command, cwd, return code, compact summary, and raw output paths. Use stdout.txt for the full Claude payload. Override the artifact root with AI_AGENT_OUTPUT_DIR; disable saving with --no-save-output only for throwaway smoke tests.

Bundled Script

Use scripts/advisor.py for repeatable runs, dry runs, saved-session resume, output artifact capture, and agent listing. It stores the most recent advisor session in $AI_AGENT_SESSIONS_PATH when set, otherwise $CODEX_HOME/external-agent-sessions.json or ~/.codex/external-agent-sessions.json. It can still read the previous claude-fable state key for migration. Read or patch the script if the installed Claude CLI changes flags.