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/liam-hq/liam/create-issuegit clone --depth 1 https://github.com/liam-hq/liamWhat 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 | $0.00007 | $0.00404 |
| Opus 5 | $0.00003 | $0.00202 |
| Sonnet 5 | $0.00001 | $0.00081 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
create-issue 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 2d 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
Task
Create a new issue in a GitHub repository using the GitHub CLI.
Process
- Analyze the request: First, understand the context and technical implications
- Gather information: If the issue involves technical implementation, think through:
- Current state vs desired state
- Technical requirements and dependencies
- Potential implementation approaches
- Impact and risks
- Structure the issue: Create a well-structured issue with:
- Clear title
- Detailed body with background, requirements, and technical considerations
- Use proper markdown formatting
Arguments
$ARGUMENTS
Argument Handling:
- When arguments are provided: Create an issue based on the given content
- When arguments are empty: Detect technical discussions from recent conversation and suggest creating an issue based on that context
- When instructed to "create from conversation": Analyze conversation history to generate an issue
Best Practices
- Argument validation: When arguments are empty, first analyze available conversation context
- Conversation history utilization: Auto-detect technical investigations, bug discoveries, refactoring proposals
- Research integration: Use code investigation and search results as evidence for the issue
- Structured issues: Include the following sections:
- Overview (problem summary)
- Current state (technical current situation)
- Investigation results (detailed research findings)
- Action items (specific work to be done)
- Impact analysis (risks and benefits)
- Technical considerations (implementation notes)
- Evidence documentation: Include specific file paths, line numbers, and search results
- Cross-repository references: When referencing PRs or issues from repositories other than the target repository, use the full format
repository#number(e.g.,liam-hq/liam#2991) instead of just#numberto ensure proper GitHub linking
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.
- 2d ago First seen · 40 lines · 7 tokens per session scan A ad832ecc6b11
create-issue is a command published in the GitHub repository liam-hq/liam (5,100 stars, last pushed 4d ago), licensed Apache-2.0. It adds 7 tokens to every session and 404 once invoked, about $0.0000 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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