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 MRCalderon3D/everything-game-dev-code --skill dialogue-content-pipelinegit clone --depth 1 https://github.com/MRCalderon3D/everything-game-dev-codeWrote 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/mrcalderon3d/everything-game-dev-code/dialogue-content-pipeline)<a href="https://agentmods.dev/skills/mrcalderon3d/everything-game-dev-code/dialogue-content-pipeline"><img src="https://agentmods.dev/badge/skills/mrcalderon3d/everything-game-dev-code/dialogue-content-pipeline.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00331 |
| Opus 5 | $0.00013 | $0.00166 |
| Sonnet 5 | $0.00005 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
dialogue-content-pipeline 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 5d 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.
What it actually says
Dialogue Content Pipeline
Purpose
Manage dialogue and text content so it remains editable, implementable, localizable, and testable.
Use When
- dialogue volume is increasing
- quest and narrative content are branching
- text implementation is brittle
Inputs
- narrative brief
- quest logic
- VO constraints
- localization pipeline
Process
- define content structure and identifiers
- separate speaker, condition, and line content clearly
- track implementation state, review state, and localization state
- test branch logic and fallback lines
- prevent canon drift and naming inconsistency
Outputs
- dialogue content model
- branching rules
- review checklist
- implementation status notes
Quality Bar
- is usable by content creators without tribal knowledge
- respects quality bars and runtime constraints together
- defines validation and ownership for content flow
Common Failure Modes
- style consistency that ignores gameplay readability
- manual pipeline steps that create drift
- content that cannot be validated before release
Related Agents
- narrative-designer
- level-designer
- ui-ux-designer
Related Commands
- quest-design
- update-docs
- verify
Notes
- Keep this skill aligned with the relevant rules layer and current project documentation.
- If engine-specific constraints materially change the workflow, hand off to the matching engine skill or engine-specific reviewer.
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.
- 5d ago First seen · 60 lines · 26 tokens per session scan A 7de3190acf50
dialogue-content-pipeline is a skill published in the GitHub repository MRCalderon3D/everything-game-dev-code (81 stars, last pushed 18d ago), licensed MIT. It adds 26 tokens to every session and 331 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 2026-09-03.
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