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.
npx skills add CamusGIT/EvoQuant --skill research-ideationgit clone --depth 1 https://github.com/CamusGIT/EvoQuantWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/camusgit/evoquant/research-ideation)<a href="https://agentmods.dev/skills/camusgit/evoquant/research-ideation"><img src="https://agentmods.dev/badge/skills/camusgit/evoquant/research-ideation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/camusgit/evoquant/research-ideation"><img src="https://agentmods.dev/badge/skills/camusgit/evoquant/research-ideation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00151 | $0.04723 |
| Opus 5.5 | $0.00060 | $0.01889 |
| Sonnet 5.5 | $0.00030 | $0.00945 |
| Haiku 4.5 | $0.00015 | $0.00472 |
Grade A, and why
research-ideation 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 410 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Ideation
From research goal to ranked ideas and a detailed proposal.
Step 0: Load evo-memory (M_I)
↓
Step 1: Define Scope & Goal
↓
Step 2: Literature Grounding (MUST use local-paper-navigator scripts)
↓
Step 3: Generate Ideas (3 Anchor Papers × Innovator persona)
↓
Step 4: Refine Ideas (3 tracks × N iterations)
↓
Step 5: ELO Tournament → Present Top-3 to User
↓
Step 6: Update evo-memory (IDE)
↓
User Selects
↓
Step 7: Expand into Proposal
↓
Step 8: Validate and Iterate
When to Use
- User wants to find a research direction or brainstorm research ideas within a specific quant scope stage
- User wants to evaluate whether an idea is novel or worth pursuing
- User wants to rank or compare multiple research ideas
- User wants to generate a research proposal from an idea anchored to an existing paper
Note: This pipeline is optimized for quantitative research where incremental, anchor-first contributions are preferred over architectural redesigns.
When NOT to Use
- Finding/reading papers → use
local-paper-navigator - Literature survey report → use
research-survey - Planning a paper (story design, experiment plan) → use
paper-planning
Step 0: Load Prior Knowledge from evo-memory
Before any ideation begins, load Ideation Memory (M_I) from prior research cycles:
- Read M_I at
/memory/ideation-memory.md(refer toevo-memoryskill) - Select the top-2 entries (k_I=2) most relevant to the user's current goal by comparing each entry's Summary and Retrieval Tags against the goal
- Feasible directions from prior cycles → use as seeds in Step 3 (incorporate as candidate anchor directions alongside new ones, within the same scope stage)
- Unsuccessful directions marked as fundamental failures → use during idea pruning in Step 4 (prune any idea that matches a fundamental failure pattern)
- If M_I doesn't exist yet (first cycle), skip this step
This step prevents repeating known dead ends and builds on prior successes across research cycles.
What ships with it
13 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.
- assets/direction-summary-template.md 2.1 KB
- assets/idea-candidate-template.md 1.8 KB
- assets/paper-summary-template.md 895 B
- assets/proposal-template.md 5.8 KB
- assets/ranking-scorecard-template.md 1.1 KB
- references/baseline-feasibility.md 2.6 KB
- references/elo-ranking-guide.md 10 KB
- references/literature-tree.md 5.1 KB
- references/paper-reading.md 4.4 KB
- references/problem-selection.md 6.1 KB
- references/proposal-extension.md 12 KB
- references/solution-design.md 7.2 KB
- references/tree-search-protocol.md 7.7 KB
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.
- 1mo ago Changed df819deb20f1
- 1mo ago First seen · 410 lines · 151 tokens per session scan A 27f2bed8dc11
research-ideation is a skill published in the GitHub repository CamusGIT/EvoQuant (141 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 151 tokens to every session and 4,723 once invoked, about $0.0006 per session on Opus 5.5. 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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