Ce:ideate

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Generate Improvement Ideas

Note: The current year is 2026. Use this when dating ideation documents and checking recent ideation artifacts.

ce:ideate precedes ce:brainstorm.

• ce:ideate answers: “What are the strongest ideas worth exploring?”
• ce:brainstorm answers: “What exactly should one chosen idea mean?”
• ce:plan answers: “How should it be built?”

This workflow produces a ranked ideation artifact in docs/ideation/. It does not produce requirements, plans, or code.

Interaction Method

Use the platform’s blocking question tool when available (question in OpenCode, request_user_input in Codex, ask_user in Gemini). Otherwise, present numbered options in chat and wait for the user’s reply before proceeding.

Ask one question at a time. Prefer concise single-select choices when natural options exist.

Focus Hint

<focus_hint> #$ARGUMENTS </focus_hint>

Interpret any provided argument as optional context. It may be:

• a concept such as DX improvements
• a path such as plugins/systematic/skills/
• a constraint such as low-complexity quick wins
• a volume hint such as top 3, 100 ideas, or raise the bar

If no argument is provided, proceed with open-ended ideation.

Core Principles

1. Ground before ideating - Scan the actual codebase first. Do not generate abstract product advice detached from the repository.
2. Generate many -> critique all -> explain survivors only - The quality mechanism is explicit rejection with reasons, not optimistic ranking. Do not let extra process obscure this pattern.
3. Route action into brainstorming - Ideation identifies promising directions; ce:brainstorm defines the selected one precisely enough for planning. Do not skip to planning from ideation output.

Execution Flow

Phase 0: Resume and Scope

0.1 Check for Recent Ideation Work

Look in docs/ideation/ for ideation documents created within the last 30 days.

Treat a prior ideation doc as relevant when:

• the topic matches the requested focus
• the path or subsystem overlaps the requested focus
• the request is open-ended and there is an obvious recent open ideation doc
• the issue-grounded status matches: do not offer to resume a non-issue ideation when the current argument indicates issue-tracker intent, or vice versa — treat these as distinct topics

If a relevant doc exists, ask whether to:

1. continue from it
2. start fresh

If continuing:

• read the document
• summarize what has already been explored
• preserve previous idea statuses
• update the existing file instead of creating a duplicate

0.2 Interpret Focus and Volume

Infer three things from the argument:

• Focus context - concept, path, constraint, or open-ended
• Volume override - any hint that changes candidate or survivor counts
• Issue-tracker intent - whether the user wants issue/bug data as an input source

Issue-tracker intent triggers when the argument’s primary intent is about analyzing issue patterns: bugs, github issues, open issues, issue patterns, what users are reporting, bug reports, issue themes.

Do NOT trigger on arguments that merely mention bugs as a focus: bug in auth, fix the login issue, the signup bug — these are focus hints, not requests to analyze the issue tracker.

When combined (e.g., top 3 bugs in authentication): detect issue-tracker intent first, volume override second, remainder is the focus hint. The focus narrows which issues matter; the volume override controls survivor count.

Default volume:

• each ideation sub-agent generates about 8-10 ideas (yielding ~30 raw ideas across agents, ~20-25 after dedupe)
• keep the top 5-7 survivors

Honor clear overrides such as:

• top 3
• 100 ideas
• go deep
• raise the bar

Use reasonable interpretation rather than formal parsing.

Phase 1: Codebase Scan

Before generating ideas, gather codebase context.

Run agents in parallel in the foreground (do not use background dispatch — the results are needed before proceeding):

1. Quick context scan — dispatch a general-purpose sub-agent using the platform’s cheapest capable model (e.g., model: "haiku" in OpenCode) with this prompt:

   Read the project’s AGENTS.md (or AGENTS.md only as compatibility fallback, then README.md if neither exists), then discover the top-level directory layout using the native file-search/glob tool (e.g., Glob with pattern * or */* in OpenCode). Return a concise summary (under 30 lines) covering:

   • project shape (language, framework, top-level directory layout)
   • notable patterns or conventions
   • obvious pain points or gaps
   • likely leverage points for improvement

   Keep the scan shallow — read only top-level documentation and directory structure. Do not analyze GitHub issues, templates, or contribution guidelines. Do not do deep code search.

   Focus hint: {focus_hint}

2. Learnings search — dispatch systematic:research:learnings-researcher with a brief summary of the ideation focus.

3. Issue intelligence (conditional) — if issue-tracker intent was detected in Phase 0.2, dispatch systematic:research:issue-intelligence-analyst with the focus hint. If a focus hint is present, pass it so the agent can weight its clustering toward that area. Run this in parallel with agents 1 and 2.

   If the agent returns an error (gh not installed, no remote, auth failure), log a warning to the user (“Issue analysis unavailable: {reason}. Proceeding with standard ideation.”) and continue with the existing two-agent grounding.

   If the agent reports fewer than 5 total issues, note “Insufficient issue signal for theme analysis” and proceed with default ideation frames in Phase 2.

Consolidate all results into a short grounding summary. When issue intelligence is present, keep it as a distinct section so ideation sub-agents can distinguish between code-observed and user-reported signals:

• Codebase context — project shape, notable patterns, obvious pain points, likely leverage points
• Past learnings — relevant institutional knowledge from docs/solutions/
• Issue intelligence (when present) — theme summaries from the issue intelligence agent, preserving theme titles, descriptions, issue counts, and trend directions

Slack context (opt-in) — never auto-dispatch. Route by condition:

• Tools available + user asked: Dispatch systematic:research:slack-researcher with the focus hint in parallel with other Phase 1 agents. Include findings in the grounding summary.
• Tools available + user didn’t ask: Note in output: “Slack tools detected. Ask me to search Slack for organizational context at any point, or include it in your next prompt.”
• No tools + user asked: Note in output: “Slack context was requested but no Slack tools are available. Install and authenticate the Slack plugin to enable organizational context search.”

Do not do external research in v1.

Phase 2: Divergent Ideation

Generate the full candidate list before critiquing any idea.

Dispatch 3-4 parallel ideation sub-agents on the inherited model (do not tier down — creative ideation needs the orchestrator’s reasoning level). Omit the mode parameter so the user’s configured permission settings apply. Each targets ~8-10 ideas (yielding ~30 raw ideas, ~20-25 after dedupe). Adjust per-agent targets when volume overrides apply (e.g., “100 ideas” raises it, “top 3” may lower the survivor count instead).

Give each sub-agent: the grounding summary, the focus hint, the per-agent volume target, and an instruction to generate raw candidates only (not critique). Each agent’s first few ideas tend to be obvious — push past them. Ground every idea in the Phase 1 scan.

Assign each sub-agent a different ideation frame as a starting bias, not a constraint. Prompt each to begin from its assigned perspective but follow any promising thread — cross-cutting ideas that span multiple frames are valuable.

Frame selection:

• When issue-tracker intent is active and themes were returned: Each high/medium-confidence theme becomes a frame. Pad with default frames if fewer than 3 cluster-derived frames. Cap at 4 total.
• Default frames (no issue-tracker intent): (1) user/operator pain and friction, (2) inversion, removal, or automation of a painful step, (3) assumption-breaking or reframing, (4) leverage and compounding effects.

Ask each sub-agent to return a compact structure per idea: title, summary, why_it_matters, evidence/grounding hooks, optional boldness or focus_fit signal.

After all sub-agents return:

1. Merge and dedupe into one master candidate list.
2. Synthesize cross-cutting combinations — scan for ideas from different frames that combine into something stronger (expect 3-5 additions at most).
3. If a focus was provided, weight the merged list toward it without excluding stronger adjacent ideas.
4. Spread ideas across multiple dimensions when justified: workflow/DX, reliability, extensibility, missing capabilities, docs/knowledge compounding, quality/maintenance, leverage on future work.

After merging and synthesis, read references/post-ideation-workflow.md for the adversarial filtering rubric, presentation format, artifact template, handoff options, and quality bar. Do not load this file before Phase 2 agent dispatch completes.