A workflow for turning a research direction into one specific research proposal with a method and a way to test whether it is wrong. It grounds the proposal in recent machine-learning research papers.

Developing one research idea, checking its novelty, diagnosing a research bottleneck, and shaping a paper proposal.

It narrows vague brainstorming into a research idea that can be implemented, evaluated, and defended against reviewer criticism.

idea-spark — Skill by microsoft

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/microsoft/researchstudio/idea_spark

Any agent

npx skills add microsoft/ResearchStudio --skill idea_spark

Clone the repo

git clone --depth 1 https://github.com/microsoft/ResearchStudio

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 13,848 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00065	$0.13848
Opus 5	$0.00032	$0.06924
Sonnet 5	$0.00013	$0.02770
Haiku 4.5	$0.00006	$0.01385

Measured 2d ago against content hash 5dfb79c52a00, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

idea-spark scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ResearchStudio-Idea/skills/idea_spark/SKILL.md · 272 lines

How it starts

The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Idea Spark Skill

Convert an under-specified research direction into ONE reviewer-defensible Oral-level research proposal — grounded in 1947 ICLR/ICML/NeurIPS papers (2021-2025) — via a 5-phase workflow: retrieve recent literature, diagnose the bottleneck, select + generate a candidate using corpus-derived ideation pattern cards, run it through a quality gauntlet, expand into an idea card.

This file is the operational runbook. Design rationale (the 7 design principles, why each contract is shaped this way, removed-check history) lives in references/design-notes.md — read it only when modifying or evaluating the skill, never needed to run it. When MODIFYING the skill, also replay the cross-shape regression set in references/regression-directions.md (deterministic subset: python3 "$SKILL_DIR/scripts/regression_check.py" <run_dir>; routing/merger branch fixtures — including every guard/retry branch that real runs rarely exercise: python3 "$SKILL_DIR/scripts/selftest_routing.py"; unit fixtures for the helpers every phase sits on — the multi-query round-robin and the tolerant LLM-JSON loader: python3 "$SKILL_DIR/scripts/selftest_units.py"). First-time installation lives in references/setup.md.

When to use

"Give me a research idea in {area} I could pursue." / "What's the most impactful next step in this direction?"
"Help me sharpen this vague direction into an Oral-level proposal."
"What's the bottleneck of this problem?" / "Run a novelty audit on this idea."

When NOT to use

Code review, debugging, refactoring. Summarizing one paper. Cross-decade survey writing.
Free-association brainstorming with no research context. Engineering integration tasks ("ship this feature in our system").
Pure benchmark / dataset construction work — the 15-pattern vocabulary handles benchmark audit (controlled_diagnostic_design) but not benchmark construction.

Setup (first use only)

Read the full file on GitHub · 272 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 272 lines · 65 tokens per session scan A 5dfb79c52a00

Subscribe to this mod's changes

idea-spark is a skill published in the GitHub repository microsoft/ResearchStudio (2,614 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 13,848 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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