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 vfarcic/dot-ai --skill dot-ai-process-feature-requestgit clone --depth 1 https://github.com/vfarcic/dot-aiWrote 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/vfarcic/dot-ai/dot-ai-process-feature-request)<a href="https://agentmods.dev/skills/vfarcic/dot-ai/dot-ai-process-feature-request"><img src="https://agentmods.dev/badge/skills/vfarcic/dot-ai/dot-ai-process-feature-request.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 5.1 | $0.00034 | $0.00354 |
| Opus 5 | $0.00017 | $0.00177 |
| Sonnet 5 | $0.00007 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
dot-ai-process-feature-request 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 7d 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
Process Feature Request/Response
Read and process a feature request or response from another dot-ai project.
Process
- Check for
tmp/feature-request.md(incoming request from another project) - If not found, check for
tmp/feature-response.md(response to a request we made) - If neither exists, tell the user there's nothing pending
For Incoming Request (feature-request.md)
- Present the request to the user and confirm they want to proceed
- Implement the requested feature
- Write a response file to the requesting project (path specified in the request)
- Delete the feature-request.md file after implementation is complete
For Response (feature-response.md)
- Read and present the response
- Use the information to continue integrating the feature
- Delete the feature-response.md file after integration is complete
Response File Format (for incoming requests only)
# Feature Response from [THIS_PROJECT]
## What Was Implemented
[Brief description of what was built]
## How to Use It
[API signatures, endpoints, types, parameters]
## Examples
[Code examples showing how to call/use the feature]
## Notes
[Any caveats, limitations, or additional context]
Guidelines
- Read and understand the full request/response before proceeding
- For requests: use your judgment on the best approach
- Write clear documentation in responses so the requesting project can integrate easily
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.
- 7d ago First seen · 56 lines · 34 tokens per session scan A 2f8641dfc77a
dot-ai-process-feature-request is a skill published in the GitHub repository vfarcic/dot-ai (335 stars, last pushed 4d ago), licensed MIT. It adds 34 tokens to every session and 354 once invoked, about $0.0002 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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