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 Haohaha-11/Paper-Writing --skill discussion-writergit clone --depth 1 https://github.com/Haohaha-11/Paper-WritingWrote 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/haohaha-11/paper-writing/discussion-writer)<a href="https://agentmods.dev/skills/haohaha-11/paper-writing/discussion-writer"><img src="https://agentmods.dev/badge/skills/haohaha-11/paper-writing/discussion-writer/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/haohaha-11/paper-writing/discussion-writer"><img src="https://agentmods.dev/badge/skills/haohaha-11/paper-writing/discussion-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00602 |
| Opus 5 | $0.00000 | $0.00301 |
| Sonnet 5 | $0.00000 | $0.00120 |
| Haiku 4.5 | $0.00000 | $0.00060 |
Grade A, and why
discussion-writer 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 11d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discussion Writer
Purpose
Write or revise a Discussion section that interprets results, explains practical meaning, connects limitations to evidence, and avoids overstating conclusions.
When To Use
Use this skill when a venue or journal expects a distinct Discussion section, or when Results, Limitations, and Conclusion are too compressed to explain what the findings mean.
Inputs
- Paper context and target venue.
- Main result tables and figures.
- Claim-evidence matrix.
- Limitations and ethics notes.
- Reviewer or redteam concerns if available.
Procedure
- Identify the two or three findings that need interpretation beyond raw numbers.
- For each finding, state what changed, why it may have changed, and what evidence supports that interpretation.
- Separate measured results from hypotheses about mechanism.
- Connect negative, mixed, or boundary-case results to limitations.
- State practical implications only within the study design.
- Add a paragraph on generalization boundaries when the work involves datasets, populations, deployment settings, or clinical/real-world use.
- Remove claims that repeat the abstract without adding interpretation.
Rubric
- Every interpretation is tied to a result, ablation, citation, or stated assumption.
- The section explains implications without creating new unsupported claims.
- Failure cases and limitations are treated as part of the argument, not as a disclaimer.
- The section is distinct from Results and Conclusion.
- Clinical, safety, fairness, privacy, and deployment implications are bounded by evidence.
Venue Adaptation
- ICLR/NeurIPS/ICML: discussion may be folded into Results, Limitations, or Conclusion if space is tight.
- CVPR/ECCV: prioritize visual failure cases, robustness, and dataset shift.
- AAAI: connect implications to broader AI context and responsible use when relevant.
- IEEE TMI: be explicit about clinical scope, validation limits, privacy, and external validity.
- arXiv: preserve venue-specific discussion unless preparing a shortened technical report.
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.
- 11d ago First seen · 75 lines · 0 tokens per session scan A 2fc451465ef9
discussion-writer is a skill published in the GitHub repository Haohaha-11/Paper-Writing (3 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 602 tokens. 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 2026-08-31.
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