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 savedpixel/ai-agent-rules-generator --skill reportgit clone --depth 1 https://github.com/savedpixel/ai-agent-rules-generatorWrote 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/savedpixel/ai-agent-rules-generator/report)<a href="https://agentmods.dev/skills/savedpixel/ai-agent-rules-generator/report"><img src="https://agentmods.dev/badge/skills/savedpixel/ai-agent-rules-generator/report/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/savedpixel/ai-agent-rules-generator/report"><img src="https://agentmods.dev/badge/skills/savedpixel/ai-agent-rules-generator/report.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 | $0.00042 | $0.00442 |
| Opus 5.5 | $0.00017 | $0.00177 |
| Sonnet 5.5 | $0.00008 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
report 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 1mo 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
Generate Report
Generate a structured report saved as a permanent markdown file in docs/reports/.
CRITICAL — Voice & Authorship: Write in the user's voice. Never reference yourself (agent, Copilot, AI). Use "I" or neutral professional voice.
Steps
1. Gather Context
- Scan conversation for changes made.
- Check recent task logs in
docs/task/logs/. - Read relevant documentation.
- Read observation logs in
docs/agent-observations/.
2. Determine Report Type
| Type | When |
|---|---|
work-summary |
Summarizing completed work |
feature-report |
Deep dive on a feature |
audit |
Quality, security, performance |
architecture |
Decisions, patterns, tech debt |
incident |
Bug investigation, root cause |
status |
Sprint/project status |
custom |
Anything else |
3. Generate the Report File
File path: docs/reports/{YYYY-MM-DD}-{slug}.md
4. Report Structure
# {Report Title}
> **Type:** {type}
> **Date:** YYYY-MM-DD
> **Scope:** {Brief scope}
---
## Summary
## Context
## Details
### Files Involved
| File | Role |
|---|---|
## Findings / Outcomes
## Recommendations / Next Steps
5. Capture Observations (MANDATORY)
Scan findings for unresolved items. Cross-post to docs/agent-observations/ logs. If none: "Observations: none."
6. Save & Confirm
Rules
- Always save to
docs/reports/. Never inline-only. - Be thorough but concise.
- Date-prefix filenames.
- Write in the user's voice.
- Cross-post observations to observation logs.
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.
- 1mo ago First seen · 74 lines · 42 tokens per session scan A 031d94dc154e
report is a skill published in the GitHub repository savedpixel/ai-agent-rules-generator (8 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 442 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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