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 agentmods add skills/sillsdev/fieldworks/convert-dialognpx skills add sillsdev/FieldWorks --skill convert-dialoggit clone --depth 1 https://github.com/sillsdev/FieldWorksWrote 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/sillsdev/fieldworks/convert-dialog)<a href="https://agentmods.dev/skills/sillsdev/fieldworks/convert-dialog"><img src="https://agentmods.dev/badge/skills/sillsdev/fieldworks/convert-dialog.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.04323 |
| Opus 5 | $0.00030 | $0.02161 |
| Sonnet 5 | $0.00012 | $0.00865 |
| Haiku 4.5 | $0.00006 | $0.00432 |
Grade A, and why
convert-dialog 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 3d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 3d ago First seen · 344 lines · 59 tokens per session scan A 17ade84da51d
convert-dialog is a skill published in the GitHub repository sillsdev/FieldWorks (111 stars, last pushed today), with no licence file. It adds 59 tokens to every session and 4,323 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.
Other skills, from other repositories
zh-article-analyzer
繁體中文文章深度分析技能。對任何中文文章進行多維度科學化剖析，產出精確到行號與段落的分析報告。 涵蓋：文體指紋（Stylometrics）、語言節奏、詞彙豐富度、引用與典故圖譜、主題動態、情感弧線、 修辭力道、文白比、成語密度等。結合 Python 量化腳本與 LLM 質性分析，產出完整的「文章指紋報告」。 當使用者提到「分析文章」、「文章風格」、「寫作分析」、「文體分析」、「文章指紋」、「語言風格」、 「修辭分析」、「文章比較」、「作者風格」、「寫法分析」，或上傳中文文章要求任何形式的語言學或 文體學分析時，務必觸發此技能。即使使用者只是問「這篇文章寫得怎樣」也應觸發。.
argument-mapping
Use this Skill to extract and visualize argument structure: Toulmin reconstruction, support/attack graph, circularity detection, argument scheme classification, and NLP-based premise extraction.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.