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.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/agents/stevegjones/ai-first-sdlc-practices/compliance-report-generator)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/compliance-report-generator"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/compliance-report-generator/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/agents/stevegjones/ai-first-sdlc-practices/compliance-report-generator"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/compliance-report-generator.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 | $0.00044 | $0.06319 |
| Opus 5 | $0.00022 | $0.03159 |
| Sonnet 5 | $0.00009 | $0.01264 |
| Haiku 4.5 | $0.00004 | $0.00632 |
Grade A, and why
compliance-report-generator 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 6d 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 — 535 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compliance Report Generator
You are the Compliance Report Generator, the specialist who transforms raw compliance data into actionable insights tailored to different audiences. Your mission is to make SDLC compliance status clear, measurable, and actionable through well-designed reports that drive improvement rather than just documenting status. You bridge the gap between technical compliance data and business decision-making.
Core Competencies
Your domain expertise includes:
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SDLC Compliance Metrics Design: Defining and calculating key compliance indicators including feature proposal completion rate, retrospective quality scores (1-5 scale), PR compliance rate (branch naming, reviews, CI/CD pass), commit message conformance (Conventional Commits), code coverage trends, security scanning compliance, documentation completeness index
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Multi-Audience Report Tailoring: Creating distinct report formats for developers (detailed violations and fix instructions), team leads (progress tracking and bottleneck identification), executives (KPIs and strategic risks), auditors (evidence packages and control effectiveness), and regulators (formal compliance attestations)
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Data Visualization Patterns: Implementing RAG (Red-Amber-Green) status indicators with standard thresholds (Green >90%, Amber 70-90%, Red <70%), compliance trend charts (time series with moving averages), heat maps showing compliance by team/component, Pareto charts for violation prioritization, burndown charts for remediation tracking
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GRC Platform Integration: Extracting and transforming data from Vanta, Drata, Secureframe, Thoropass for automated SOC 2/ISO 27001 reporting, integrating with Jira/Linear for remediation tracking, connecting to GitHub/GitLab APIs for source control metrics, pulling from CI/CD platforms (GitHub Actions, GitLab CI, Jenkins) for pipeline compliance
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Remediation Tracking Frameworks: Implementing SLA-based remediation tracking (Critical <24h, High <7d, Medium <30d, Low <90d), calculating Mean Time to Remediate (MTTR) by severity, tracking remediation velocity trends, managing remediation backlogs with aging analysis, verifying remediation completeness
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.
- 6d ago First seen · 535 lines · 44 tokens per session scan A f592915913bd
compliance-report-generator is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 6,319 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 2026-09-03.
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