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/rjmurillo/ai-agentsWrote 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/commands/rjmurillo/ai-agents/artifact-insight-scan)<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/artifact-insight-scan"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/artifact-insight-scan/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/commands/rjmurillo/ai-agents/artifact-insight-scan"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/artifact-insight-scan.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 | $0.00000 | $0.00776 |
| Opus 5 | $0.00000 | $0.00388 |
| Sonnet 5 | $0.00000 | $0.00155 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
artifact-insight-scan 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 today.
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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Artifact Insight Scanner
Analyze the provided project artifacts for missed insights, action items, and follow-ups that should become tracked issues.
What to Look For
1. Untracked TODOs
TODO:orFIXME:comments without linked issues- "We should..." or "Need to..." statements
- Checkbox items that were never checked (
- [ ]) - "Later" or "future work" mentions
2. Lessons Not Captured
- Patterns discovered during debugging
- Workarounds that should be documented
- "Next time..." observations
- Root cause insights that could prevent recurrence
3. Blocked Work
- Items waiting on external dependencies
- Work paused due to other priorities
- "Once X is done..." statements
- Deferred scope items
4. Process Improvements
- Repeated friction points across sessions
- Automation opportunities mentioned
- Documentation gaps identified
- Workflow inefficiencies noted
5. Follow-up Tasks
- "After this PR..." commitments
- Review feedback not yet addressed
- Deferred scope items from PRDs
- Testing or validation that was skipped
Output Format
For each actionable finding, output this exact format:
FINDING:
TYPE: [TODO|LESSON|BLOCKED|IMPROVEMENT|FOLLOWUP]
TITLE: [Concise issue title, 50-70 chars, conventional commit style]
BODY: [Issue body with context, 2-4 sentences]
PRIORITY: [P0|P1|P2|P3]
LABELS: [comma-separated labels from: enhancement, bug, documentation, automation, area-workflows, area-prompts, area-infrastructure, area-installation]
SOURCE: [file path and line/section reference]
---
Priority Guidelines
- P0: Security issues, data loss risks, critical blockers
- P1: Important functionality gaps, significant user impact
- P2: Improvements, process enhancements, nice-to-haves
- P3: Minor polish, optional enhancements
Rules
- Only report actionable items that should become issues
- Skip items that are clearly completed or superseded
- Do not duplicate existing tracked work
- Use conventional commit prefixes in titles (feat:, fix:, docs:, chore:)
- Keep issue bodies concise but informative
- Include enough context for someone unfamiliar with the session
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.
- today Changed c2ef8e2ce057
- 3d ago First seen · 109 lines · 0 tokens per session scan A 5baf7fedfbcd
artifact-insight-scan is a command published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 776 tokens. 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 2026-09-06.
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