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 dandye/ai-runbooks --skill generate-reportgit clone --depth 1 https://github.com/dandye/ai-runbooksWrote 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/dandye/ai-runbooks/generate-report)<a href="https://agentmods.dev/skills/dandye/ai-runbooks/generate-report"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/generate-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/dandye/ai-runbooks/generate-report"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/generate-report.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00038 | $0.00611 |
| Opus 5.5 | $0.00015 | $0.00244 |
| Sonnet 5.5 | $0.00008 | $0.00122 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
generate-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 2mo 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Report Skill
Save generated report content to a markdown file with standardized naming convention.
Inputs
REPORT_CONTENT- The full markdown content of the reportREPORT_TYPE- Short identifier for the report type:alert_triage- Alert triage reportsioc_enrichment- IOC enrichment reportscase_investigation- Case investigation reportshunt_summary- Threat hunt reportsincident_report- Incident response reports
REPORT_NAME_SUFFIX- Descriptive suffix (e.g., case ID, IOC value, hunt name)- (Optional)
TARGET_DIRECTORY- Directory to save in (default:./reports/)
Workflow
Step 1: Construct Filename
Generate standardized filename:
{TARGET_DIRECTORY}/{REPORT_TYPE}_{REPORT_NAME_SUFFIX}_{YYYYMMDD_HHMM}.md
Examples:
./reports/alert_triage_case_1234_20250115_1430.md./reports/ioc_enrichment_198.51.100.10_20250115_0900.md./reports/hunt_summary_APT29_20250115_1200.md
Step 2: Write File
Use the Write tool to save REPORT_CONTENT to the constructed path.
Outputs
| Output | Description |
|---|---|
REPORT_FILE_PATH |
Full path to the saved report file |
WRITE_STATUS |
Success/failure status of the write operation |
Report Template Structure
# [Report Type]: [Subject]
**Generated:** [timestamp]
**Runbook:** [runbook name that generated this]
**Case/Alert ID:** [if applicable]
## Summary
[Brief overview of findings]
## Details
[Detailed findings, enrichment data, etc.]
## Assessment
[Risk assessment, classification]
## Recommendations
[Next steps, actions to take]
## Appendix
[Raw data, tool outputs, diagrams]
Naming Convention
| Report Type | Suffix Example | Full Example |
|---|---|---|
| alert_triage | case_1234 | alert_triage_case_1234_20250115_1430.md |
| ioc_enrichment | evil.com | ioc_enrichment_evil.com_20250115_0900.md |
| hunt_summary | APT29 | hunt_summary_APT29_20250115_1200.md |
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.
- 2mo ago First seen · 84 lines · 38 tokens per session scan A fe995efc75bf
generate-report is a skill published in the GitHub repository dandye/ai-runbooks (132 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 611 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 2026-08-30.
generate-report compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| generate-reportdandye/ai-runbooks | Skill | 132 | 2mo ago | Apache-2.0 | A | 38 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 315k | 5d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |