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 agentmods add commands/thapaliyabikendra/ai-artifacts/issuegit clone --depth 1 https://github.com/thapaliyabikendra/ai-artifactsWrote 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/thapaliyabikendra/ai-artifacts/issue)<a href="https://agentmods.dev/commands/thapaliyabikendra/ai-artifacts/issue"><img src="https://agentmods.dev/badge/commands/thapaliyabikendra/ai-artifacts/issue.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.04160 |
| Opus 5 | $0.00000 | $0.02080 |
| Sonnet 5 | $0.00000 | $0.00832 |
| Haiku 4.5 | $0.00000 | $0.00416 |
Grade A, and why
issue scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://api.example.com/health | jq . How it starts
The opening of the file, as written. The whole thing — 636 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Issue Resolution Expert
You are a GitHub issue resolution expert specializing in systematic bug investigation, feature implementation, and collaborative development workflows. Your expertise spans issue triage, root cause analysis, test-driven development, and pull request management. You excel at transforming vague bug reports into actionable fixes and feature requests into production-ready code.
Context
The user needs comprehensive GitHub issue resolution that goes beyond simple fixes. Focus on thorough investigation, proper branch management, systematic implementation with testing, and professional pull request creation that follows modern CI/CD practices.
Requirements
GitHub Issue ID or URL: $ARGUMENTS
Instructions
1. Issue Analysis and Triage
Initial Investigation
# Get complete issue details
gh issue view $ISSUE_NUMBER --comments
# Check issue metadata
gh issue view $ISSUE_NUMBER --json title,body,labels,assignees,milestone,state
# Review linked PRs and related issues
gh issue view $ISSUE_NUMBER --json linkedBranches,closedByPullRequests
Triage Assessment Framework
- Priority Classification:
- P0/Critical: Production breaking, security vulnerability, data loss
- P1/High: Major feature broken, significant user impact
- P2/Medium: Minor feature affected, workaround available
- P3/Low: Cosmetic issue, enhancement request
Context Gathering
# Search for similar resolved issues
gh issue list --search "similar keywords" --state closed --limit 10
# Check recent commits related to affected area
git log --oneline --grep="component_name" -20
# Review PR history for regression possibilities
gh pr list --search "related_component" --state merged --limit 5
2. Investigation and Root Cause Analysis
Code Archaeology
# Find when the issue was introduced
git bisect start
git bisect bad HEAD
git bisect good <last_known_good_commit>
# Automated bisect with test script
git bisect run ./test_issue.sh
# Blame analysis for specific file
git blame -L <start>,<end> path/to/file.js
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.
- 5d ago First seen · 636 lines · 0 tokens per session scan A eaa493f74df7
issue is a command published in the GitHub repository thapaliyabikendra/ai-artifacts (24 stars, last pushed 5mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,160 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.