Norman-bury/research-writing-skill is an agent skill that turns academic paper writing into a tracked, reusable workflow with planning, drafting, reviews, figures, literature work, and LaTeX outputs. It is intended for undergraduate students, graduate students, and early-career researchers working on theses, coursework papers, or initial submissions. Its catalogue entries are the skills, instructions, plugin, and hook that implement the workflow across coding-agent platforms.
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 Norman-bury/research-writing-skill --skill experiment-results-planninggit clone --depth 1 https://github.com/Norman-bury/research-writing-skillWrote 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/norman-bury/research-writing-skill/experiment-results-planning)<a href="https://agentmods.dev/skills/norman-bury/research-writing-skill/experiment-results-planning"><img src="https://agentmods.dev/badge/skills/norman-bury/research-writing-skill/experiment-results-planning/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/norman-bury/research-writing-skill/experiment-results-planning"><img src="https://agentmods.dev/badge/skills/norman-bury/research-writing-skill/experiment-results-planning.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 | $0.00028 | $0.00899 |
| Opus 5 | $0.00014 | $0.00449 |
| Sonnet 5 | $0.00006 | $0.00180 |
| Haiku 4.5 | $0.00003 | $0.00090 |
Grade A, and why
experiment-results-planning 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 13d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Results Planning
This skill designs the experiment/result layer before final metrics exist. It may generate mock planning data, but never presents mock data as real experimental evidence.
Hard Gate
Before writing Results or Discussion, create:
plan/experiment-protocol.mdplan/review/method-experiment-traceability.mdtables/table-schema.mdfigures/data-manifest.md- real data files or clearly labeled
mock_*files
Experiment Protocol
The protocol must include:
- Dataset and split strategy.
- Baselines and why each is fair.
- Metrics and imbalance handling.
- Main comparison.
- Efficiency evaluation.
- Ablation studies for each claimed module.
- Generalization or robustness checks.
- Explainability evaluation if XAI is a contribution.
Each contribution in Introduction must map to at least one experiment or limitation note.
Recommended Experiment Gates
Use these gates in plan/stage-gates.md for result-heavy papers:
- Gate D0: Experiment Protocol Locked
- Required: datasets, split rules, Non-IID construction, seeds, baselines, metrics, hardware/software, log schema.
- Gate D1: Method-Experiment Traceability
- Required:
plan/review/method-experiment-traceability.md. - Map each contribution to method modules, experiments, tables/figures, and allowed claims.
- Required:
- Gate D2: Table/Figure Data Contract
- Required:
tables/table-schema.md,figures/data-manifest.md, and data files.
- Required:
- Gate D3: Main/Efficiency/Ablation/Generalization/XAI Results
- Each result family needs raw logs, aggregation rule, table update, figure script, and prose update.
- Gate D4: Result Chapter Decontamination
- No "实验目的", "表位", "回填模板", "讨论提示", or planning notes in the chapter body.
- Gate D5: Peer Review Pass
- Required:
plan/review/<section>-peer-review.md.
- Required:
Method-Experiment Traceability
Create:
| Contribution | Method module | Experiment | Table/Figure | Allowed claim | Evidence status |
|---|---|---|---|---|---|
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.
- 13d ago First seen · 113 lines · 28 tokens per session scan A a4442c07e884
experiment-results-planning is a skill published in the GitHub repository Norman-bury/research-writing-skill (3,195 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 899 once invoked, about $0.0001 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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