Agent skill · Audited from source
brainstorming-research-ideas
skill · orchestra-research/ai-research-skillsMIT licenceAudited 31 Oct 2026 · source 6c04b84d00a4
Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 6c04b84d00a4 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.
Cite
Cite this page
ModelsAtlas. “brainstorming-research-ideas (orchestra-research/ai-research-skills)”. Retrieved 31 Oct 2026. https://modelsatlas.com/skills/orchestra-research/brainstorming-research-ideas
2 skills are called “brainstorming-research-ideas”. You are viewing orchestra-research/ai-research-skills.
- orchestra-research/ai-research-skills★ 14k✓SAFE
- OpenRaiser/NanoResearch★ 1.3k✓SAFE
Trust audit
Audit 0.4.1 · source read 31 Oct 2026
SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.
What the source does
- FilesystemNone observedNo reads or writes in the source
- NetworkNone observedNo outbound calls in the source
- ShellNone observedNo commands run in the source
- DependenciesPinnedNothing floats
- SecretsNone foundNo keys in source
Five audit layers
| Layer | What we check | Result | Findings |
|---|---|---|---|
L0 Provenance | Repo owner, licence, archive status, activity | PASS | 0 |
L1 Static source | Secrets, path traversal, supply chain, hidden code | NA | 0 |
L2 Instructions | Prompt injection, authority framing, hidden directives | PASS | 0 |
L3 Inventory | The files and declarations match the source | PASS | 0 |
L4 Sandbox | Run in isolation and watch behaviour | SKIPPED why | 0 |
Gates applied: no behavioural pass.
Findings (0)
No findings at any severity. We re-audit when the source changes.
Audit 0.4.1 · source sha 6c04b84d00a4 · 31 Oct 2026Report an issue or request a re-scan
Provenance
Who published it, and what the verdict is pinned to
- Publisherorchestra-research GitHub organizationOwner of the repository this skill is read from
- Source folderorchestra-research/ai-research-skills/21-research-ideation/brainstorming-research-ideasThe exact folder we audited
- LicenceMITAs the repository states it
- Commit pinned for this verdict6c04b84d00a4A new audit runs when the source changes
- Repository statusNot archivedLast push 20 days ago
- Sandboxed runNot runSkills are read, not executed; layer L4 is skipped
What it tells the agent
Full source on GitHub ↗Its description: Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.
--- name: brainstorming-research-ideas description: Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work. version: 1.0.0 author: Orchestra Research license: MIT tags: [Research Ideation, Brainstorming, Problem Discovery, Creative Thinking, Research Strategy] dependencies: [] --- # Research Idea Brainstorming Structured frameworks for discovering the next research idea. This skill provides ten complementary ideation lenses that help researchers move from vague curiosity to concrete, defensible research proposals. Each framework targets a different cognitive mode—use them individually or combine them for comprehensive exploration. ## When to Use This Skill - Starting a new research direction and need structured exploration - Feeling stuck on a current project and want fresh angles - Evaluating whether a half-formed idea has real potential - Preparing for a brainstorming session with collaborators - Transitioning between research areas and seeking high-leverage entry points - Reviewing a field and looking for underexplored gaps **Do NOT use this skill when**: - You already have a well-defined research question and need execution guidance - You need help with experimental design or methodology (use domain-specific skills) - You want a literature review (use `scientific-skills:literature-review`) --- ## Core Ideation Frameworks ### 1. Problem-First vs. Solution-First Thinking Research ideas originate from two distinct modes. Knowing which mode you are in prevents a common failure: building solutions that lack real problems, or chasing problems without feasible approaches. **Problem-First** (pain point → method): - Start with a concrete failure, bottleneck, or unmet need - Naturally yields impactful work because the motivation is intrinsic - Risk: may converge on incremental fixes rather than paradigm shifts **Solution-First** (new capability → application): - Start with a new tool, insight, or technique seeking application - Often drives breakthroughs by unlocking previously impossible approaches - Risk: "hammer looking for a nail"—solution may lack genuine demand **Workflow**: 1. Write down your idea in one sentence 2. Classify it: Is this problem-first or solution-first? 3. If problem-first → verify the problem matters (who suffers? how much?) 4. If solution-first → identify at least two genuine problems it addresses 5. For either mode, articulate the gap: what cannot be done today that this enables? **Self-Check**: - [ ] Can I name a specific person or community who needs this? - [ ] Is the problem I am solving actually unsolved (not just under-marketed)? - [ ] If solution-first, does the solution create new capability or just replicate existing ones? --- ### 2. The Abstraction Ladder Every research problem sits at a particular level of abstraction. Deliberately moving up or down the ladder reveals ideas invisible at your current level. | Direction | Action | Outcome | |-----------|--------|---------| | **Move Up** (generalize) | Turn a specific result into a broader principle | Framework papers, theoretical contributions | | **Move Down** (instantiate) | Test a general paradigm under concrete constraints | Empirical papers, surprising failure analyses | | **Move Sideways** (analogize) | Apply same abstraction level to adjacent domain | Cross-pollination, transfer papers | **Workflow**: 1. State your current research focus in one sentence 2. Move UP: What is the general principle behind this? What class of problems does this belong to? 3. Move DOWN: What is the most specific, constrained instance of this? What happens at the extreme? 4. Move SIDEWAYS: Where else does this pattern appear in a different field? 5. For each new level, ask: Is this a publishable contribution on its own? **Example**: - **Current**: "Improving retrieval accuracy for RAG systems" - **Up**: "What makes context selection effective for any augmented generation system?" - **Down**: "How does retrieval accuracy degrade when documents are adversarially perturbed?" - **Sideways**: "Database query optimization uses similar relevance ranking—what can we borrow?" --- ### 3. Tension and Contradiction Hunting Breakthroughs often come from resolving tensions between widely accepted but seemingly conflicting goals. These contradictions are not bugs—they are the research opportunity. **Common Research Tensions**: | Tension Pair | Research Opportunity | |-------------|---------------------| | Performance ↔ Efficiency | Can we match SOTA with 10x less compute? | | Privacy ↔ Utility | Can federated/encrypted methods close the accuracy gap? | | Generality ↔ Specialization | When does fine-tuning beat prompting, and why? | | Safety ↔ Capability | Can alignment improve rather than tax capability? | | Interpretability ↔ Performance | Do mechanistic insights enable better architectures? | | Scale ↔ Accessibility | Can small models replicate emergent behaviors? | **Workflow**: 1. Pick your research area 2. List the top 3-5 desiderata (things everyone wants) 3. Identify pairs that are commonly treated as trade-offs 4. For each pair, ask: Is this trade-off fundamental or an artifact of current methods? 5. If artifact → the reconciliation IS your research contribution 6. If fundamental → characterizing the Pareto frontier is itself valuable **Self-Check**: - [ ] Have I confirmed this tension is real (not just assumed)? - [ ] Can I point to papers that optimize for each side independently? - [ ] Is my proposed reconciliation technically plausible, not just aspirational? --- ### 4. Cross-Pollination (Analogy Transfer) Borrowing structural ideas from other disciplines is one of the most generative research heuristics. Many foundational techniques emerged this way—attention mechanisms draw from cognitive science, genetic algorithms from biology, adversarial trai
Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.
Install
Pinned to the audited commit 6c04b84
git clone https://github.com/orchestra-research/ai-research-skills git -C ai-research-skills checkout 6c04b84d00a4
The author documents no install command, so this uses the repository directly. Our verdict covers commit 6c04b84d00a4 only.
Works in
The author has not said which agents this skill supports, and we have not tested it in any.
Audit history
Every audit, every source change
- ✓SAFE B 89 / 100
first audit · source
6c04b84d00a4
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- github.com/orchestra-research/ai-research-skills/tree/main/21-re — the audited source at commit 6c04b84d00a4 and every finding aboveObserved · 31 Oct 2026
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- What does the brainstorming-research-ideas skill do?
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