Agent-Enhanced Council Execution

Run one Workflow of parallel Claude analyst agents for deeper analysis. Each analyst queries its provider, evaluates response quality, can ask follow-up questions, and returns a structured analysis that the workflow enforces against the schema.

Step 1: Resolve Providers and Write the Questions

One shell call resolves what the workflow needs — each provider's model, its role, and the question file it will send — with the same helpers the standard flow uses. Paste the final question into the heredoc verbatim: the quoted marker means the shell does NOT interpret quotes, backticks or $() in it. The question is emitted once; each provider's role-injected variant is built in shell, not pasted again.

source "${CLAUDE_PLUGIN_ROOT}/scripts/lib/providers.sh"
source "${CLAUDE_PLUGIN_ROOT}/scripts/lib/roles.sh"
PROVIDERS=(<the selected providers, space separated>)
ROLES="<the --roles value, or empty>"
RUN=$(date +%s)                                  # names this run's files; Step 6 reuses it
Q="$PWD/.claude/council-cache/.agents-$RUN"
mkdir -p "$PWD/.claude/council-cache"
# Self-ignoring, as cache.sh and run-council.sh keep it: these files carry the
# question and any --file contents, and must never land in a commit.
[[ -f "$PWD/.claude/council-cache/.gitignore" ]] || printf '*\n' > "$PWD/.claude/council-cache/.gitignore"
cat > "$Q.txt" <<'COUNCIL_Q_EOF'
<the question, verbatim>
COUNCIL_Q_EOF
# --file / auto-context: append the context to the question file here, e.g.
#   { printf '\n\nHere is the content of %s:\n\n```\n' "<path>"; cat "<path>"; printf '```\n'; } >> "$Q.txt"
# An unknown role is refused, as the standard flow refuses it; assigning it
# would hand that provider the bare question under a role heading.
[[ -z "$ROLES" ]] || validate_roles "$ROLES" || exit 1
# The model the ANALYST agents run on — distinct from the provider models below,
# which are what actually answer the question. Pinned rather than inherited: an
# omitted model makes every analyst run on whatever model the user's session
# happens to use, so the cost of a mode that already fans out one agent per
# provider varies by a factor of several for no stated reason. Sonnet handles
# the analyst's work — run a query, judge the answer, emit a structured object.
ANALYST_MODEL="${COUNCIL_AGENT_MODEL:-sonnet}"
case "$ANALYST_MODEL" in
    sonnet|opus|haiku|fable) ;;
    *) echo "COUNCIL_AGENT_MODEL must be one of: sonnet, opus, haiku, fable (got '$ANALYST_MODEL')" >&2; exit 1 ;;
esac
echo "analyst model $ANALYST_MODEL"
ASSIGNMENTS=""
[[ -n "$ROLES" ]] && ASSIGNMENTS=$(assign_roles_to_providers "$ROLES" "${PROVIDERS[@]}")
echo "run $RUN"
for p in "${PROVIDERS[@]}"; do
    role=""
    [[ -n "$ASSIGNMENTS" ]] && role=$(get_provider_role "$p" "$ASSIGNMENTS")
    qf="$Q.txt"
    if [[ -n "$role" ]]; then
        qf="$Q-$p.txt"
        build_prompt_with_role "$(cat "$Q.txt")" "$role" > "$qf"
    fi
    printf '%s\t%s\t%s\n' "$p" "$(get_model "$p")" "$qf"
done

It prints the run id, then the analyst model, then one line per provider: name, model (shown in the Step 4 header), and the absolute path of that provider's question file. Pass the analyst model to the workflow as analystModel; the workflow script cannot read the environment itself.

Step 2: Run the Analyst Workflow

Agent mode is one Workflow: one analyst agent per provider, in parallel, each returning its analysis through schema-enforced structured output. The user asked for agent mode (--agents, or yes to the prompt in ask.md Step 1.5), which is the opt-in the Workflow tool requires.

If the Workflow tool is not available in this session, stop here: tell the user that --agents needs a Claude Code with the Workflow tool, and offer to run the same question in standard mode instead. Do not fall back to another way of spawning agents.

Read ${CLAUDEPLUGINROOT}/schemas/agent-analysis.schema.json with the Read tool, then call the Workflow tool with this script, verbatim, via script:

export const meta = {
  name: 'council-agents',
  description: 'One analyst per council provider: query it, judge the answer, follow up, return a structured analysis',
  phases: [{ title: 'Analyze', detail: 'one analyst agent per provider, in parallel' }],
}
// The tool's schema validator does not know the draft-2020-12 dialect the
// file declares; without the declaration it validates the same keywords fine.
const schema = { ...args.schema }
delete schema.$schema
const template = `${args.pluginRoot}/skills/deep-execution/agent-prompt-template.md`
// Single stage: there is no later step for a finished analyst to move on to,
// so the barrier costs nothing.
const results = await parallel(args.providers.map(p => () =>
  agent(
    `You are the council analyst for the provider "${p.name}".\n` +
    `Read ${template} and carry out every step in it, with these values:\n` +
    `- {PROVIDER} = ${p.name}\n` +
    `- {PLUGIN_ROOT} = ${args.pluginRoot}\n` +
    `- {QUESTION_FILE} = ${p.questionFile}\n` +
    `Your final answer is the Round 3 analysis object, returned through the structured output tool.`,
    { label: p.name, phase: 'Analyze', schema, agentType: 'general-purpose',
      model: args.analystModel })))
// parallel() keeps a dead or skipped analyst's slot as null, index-aligned with args.providers.
const failed = args.providers.filter((_, i) => !results[i]).map(p => p.name)
if (failed.length) log(`no analysis from: ${failed.join(', ')}`)
return {
  // The label goes last so an analyst that emits its own "provider" key cannot rename itself.
  analyses: results.map((a, i) => a && { ...a, provider: args.providers[i].name }).filter(Boolean),
  failed,
}

and these args (real JSON values, not a string; pluginRoot is the real path of ${CLAUDEPLUGINROOT}, questionFile the path Step 1 printed):

{
  "pluginRoot": "<CLAUDE_PLUGIN_ROOT>",
  "analystModel": "<the model Step 1 printed>",
  "schema": { "...the parsed schema file..." },
  "providers": [
    { "name": "gemini", "questionFile": "<absolute path from Step 1>" }
  ]
}

The workflow returns { analyses, failed }. Every object in analyses satisfies the schema; failed names the providers whose analyst died or was skipped. A provider that returned an error is not in failed: its analyst reports it as a quality: poor, confidence: low analysis whose full_response is the error text (the template says so). Step 5 treats both as the same thing — a provider that did not answer.

Step 3: Read the Result

Nothing to validate: use each analysis's fields directly in Steps 4-5, and carry failed into Step 5's provider failures.

Step 4: Display Results

For each analysis, display it using this format. {MODEL} is the Step 1 model: a model-fallback re-run inside an analyst cannot change this header, and the displacement is visible only in the analysis text.

## {EMOJI} {PROVIDER} ({MODEL}) — Agent Analysis

**Quality**: {quality} | **Confidence**: {confidence} | **Retried**: {retried}

### Key Recommendations
{recommendations}

### Unique Perspective
{unique_perspective}

### Blind Spots
{blind_spots}

---

<details>
<summary>Full {PROVIDER} Response</summary>

{full_response}

</details>

Provider emojis (ALWAYS use emoji + space):

• 🟦 Gemini
• 🔳 OpenAI
• 🟥 Grok
• 🟩 Perplexity

Step 5: Enhanced Synthesis

With pre-analyzed responses, generate a richer synthesis than the standard mode. The calibration rules in ${CLAUDEPLUGINROOT}/prompts/synthesis.md apply here too. Its "returned an error" case covers the providers in failed AND every quality: poor analysis whose full_response is a provider error: name them under failures and keep them out of consensus, whatever weight their confidence field would give them.

Confidence-Weighted Consensus

Weight agreement by each provider's confidence level. High-confidence agreement is stronger signal than low-confidence agreement — but only about the reasoning, never about the premises. Every provider read the same description of a system none of them can inspect, so confident unanimity can equally mean the question asserted something false and each provider reasoned from it correctly. When agreement is both broad and confident, say so and then name the premise the whole answer rests on, and whether anyone was in a position to check it.

Blind Spot Analysis

Cross-reference each provider's blind spots against other providers' recommendations. Flag risks that NO provider considered.

Divergence with Context

Where providers disagree, explain WHY they likely diverge (different assumptions, different optimization targets, different risk tolerance).

Recommendation

Synthesize the strongest approach, noting which providers support it and at what confidence level.

Step 6: Save Output

Save the complete output (all provider analyses + synthesis) to .claude/council-cache/council-agents-{RUN}.md, where RUN is the run id Step 1 printed (the directory exists since Step 1). Then remove the run's question files, which nothing prunes:

rm -f .claude/council-cache/.agents-{RUN}*

Tell the user:

---
Full agent analysis saved to .claude/council-cache/council-agents-{RUN}.md

Error Handling

• If a provider's analyst fails (it is listed in failed), say so and continue with the others
• If ALL analysts fail, report clearly and suggest falling back to standard mode
• If only one provider was selected and its analyst fails, suggest retrying without --agents
• A killed or interrupted workflow can be resumed: relaunch with the same args and the

scriptPath and resumeFromRunId from the tool result; the finished analysts return from cache