hierarchical-recursive-brainstorm — E2E Action Skill

Perform controlled hierarchical research end to end: take a broad research question, produce a pruned and synthesized Markdown tree of findings, and prove it worked before reporting success.

1. Preconditions (input contract)

• The user has provided a clear research topic or question.
• You have reviewed the composition contract and examples in references/research-application.md.

2. Procedure (the E2E steps)

Execute the following hierarchical research protocol:

1. Decompose: Break the initial topic into 2-5 distinct sub-topics (branches).
2. Expand: Recursively explore each branch. Stop expanding when you reach the configured max_depth (default: 3) or when a branch is sufficiently detailed.
3. Prune: Evaluate the leaves of the tree and prune the bottom quartile (the least relevant, least feasible, or weakest ideas).
4. Synthesize: Moving from the leaves up to the root, write a brief synthesis paragraph for every surviving parent node that summarizes its children.
5. Output: Generate the final output as a self-explanatory Markdown tree.
6. Action: Conclude the output with a "Next Actions" paragraph detailing the most promising paths forward.

Tunable Parameters (Agent Overrides)

These limits apply unless you explicitly decide to override them based on the task:

• max_depth: (configurable, determine dynamically based on topic breadth)
• max_children: (configurable, determine dynamically based on topic breadth)
• prune_quartile: (configurable, determine dynamically based on leaf density)

CRITICAL RULE: Do not invent or hallucinate external knowledge. Rely on your existing knowledge and any provided context or searches.

3. Output contract (postconditions — what "done" means)

• A final Markdown tree is produced containing the surviving ideas.
• Synthesis is present for every surviving parent node.
• A "Next Actions" paragraph exists at the end.
• The bottom quartile of ideas has been demonstrably pruned.
• The depth and branch limits were respected.

4. Failure handling

• On failure (e.g., if the topic is too broad to decompose meaningfully), report the specific issue and ask the user to refine the scope.
• Do not produce a partial or hallucinated tree.

5. Validation gate (before declaring success)

Subjective skill validation: There is no honest scripted gate for the quality of research.

• Run structural only (python scripts/validate_skill.py --skill . --tier structural) to keep the metadata/triggering honest.
• Self-check against explicit, concrete criteria:
  1. Limits Respected: Max depth and branch limits were not exceeded.
  2. Pruning Applied: The bottom quartile of leaves was absent from the final output.
  3. Synthesis Present: Every parent node has a synthesis of its children.
  4. Next Actions Present: The output concludes with a "Next Actions" paragraph.
  5. No Hallucinations: No external knowledge was invented.

6. Examples

See references/research-application.md for concrete examples of applying this skill to agent-evaluation research.