Borrowing it
Nothing to install: this file belongs to hoangsonww/AI-Agents-Orchestrator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hoangsonww/AI-Agents-Orchestrator/main/.agents/skills/generate-reports/SKILL.mdgit clone --depth 1 https://github.com/hoangsonww/AI-Agents-OrchestratorWrote 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/hoangsonww/ai-agents-orchestrator/generate-reports)<a href="https://agentmods.dev/skills/hoangsonww/ai-agents-orchestrator/generate-reports"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/generate-reports/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/hoangsonww/ai-agents-orchestrator/generate-reports"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/generate-reports.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 | $0.00041 | $0.00288 |
| Opus 5 | $0.00020 | $0.00144 |
| Sonnet 5 | $0.00008 | $0.00058 |
| Haiku 4.5 | $0.00004 | $0.00029 |
Grade A, and why
generate-reports 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 13d 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 reports for the AI Coding Tools Orchestrator.
Generate all reports
python3 -c "
import yaml
from orchestrator.observability.report_generator import ReportGenerator
with open('orchestrator/config/agents.yaml') as f:
config = yaml.safe_load(f)
gen = ReportGenerator(reports_dir='./reports')
paths = gen.seed_reports(config=config)
for p in paths:
print(f' Generated: {p}')
print(f'\n{len(paths)} reports generated in reports/')
"
Report types
- perf_*.json — Agent performance: success rates, call counts, task type distribution
- workflow_*.json — Workflow analytics: per-workflow runs, success rates, avg iterations
- health_*.json — System health: Python version, disk, memory, dependencies
- config_*.json — Config audit: agent availability, workflow structure, settings
- dashboard_*.html — Interactive HTML dashboard with Chart.js (4 charts + KPI cards)
After generating
Report which files were created and their sizes. Mention the HTML dashboard can be opened in a browser.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 34 lines · 41 tokens per session scan A d2dbb8e52e35
generate-reports is a skill published in the GitHub repository hoangsonww/AI-Agents-Orchestrator (84 stars, last pushed 4d ago), licensed MIT. It adds 41 tokens to every session and 288 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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