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/quay/ai-helpersWrote 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/quay/ai-helpers/estimate-issue)<a href="https://agentmods.dev/commands/quay/ai-helpers/estimate-issue"><img src="https://agentmods.dev/badge/commands/quay/ai-helpers/estimate-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 5.1 | $0.00009 | $0.01785 |
| Opus 5 | $0.00005 | $0.00892 |
| Sonnet 5 | $0.00002 | $0.00357 |
| Haiku 4.5 | $0.00001 | $0.00178 |
Grade A, and why
estimate-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.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Estimate Issue Complexity
Analyze a JIRA issue and provide a comprehensive complexity estimate with size, effort, and risk metrics for a senior developer with Claude assistance.
Issue Key
The JIRA issue to estimate: $ARGUMENTS
Phase 1: Gather Issue Information
Step 1: Fetch Issue Details
Retrieve the full issue information from JIRA:
acli jira workitem view $ARGUMENTS
Extract and note:
- Issue type (Bug, Story, Task, Epic, etc.)
- Summary and full description
- Component(s) affected
- Priority
- Labels
- Acceptance criteria (if present)
- Comments with additional context
- Linked issues (blockers, dependencies)
Phase 2: Codebase Impact Analysis
Step 2: Identify Affected Areas
Based on the issue description, search the codebase to understand scope:
For UI issues:
- Search
web/src/for related components - Check routing in
web/src/routes/ - Look for existing tests in
web/cypress/e2e/
For Backend issues:
- Search
endpoints/for related API routes - Check
data/model/for affected business logic - Look at
data/database.pyfor schema impacts - Check
workers/if background jobs are involved
For both:
- Count files likely to be modified
- Identify test files that need updates
- Check for migration requirements
Step 3: Analyze Dependencies
- Are there linked/blocking issues?
- Does this require coordination with other teams?
- Are there external API or service dependencies?
- Does this require database migrations?
- Does this require configuration changes?
Phase 3: Complexity Assessment
Complexity Dimensions
Evaluate each dimension on a scale of 1-5:
| Dimension | 1 (Low) | 3 (Medium) | 5 (High) |
|---|---|---|---|
| Code Scope | 1-2 files | 3-5 files | 6+ files |
| Logic Complexity | Simple CRUD | Business rules | Algorithmic/Distributed |
| Testing Effort | Update existing | New unit tests | New e2e + integration |
| Risk Level | Isolated change | Touches shared code | Core system change |
| Uncertainty | Clear requirements | Some ambiguity | Needs spike/research |
| Dependencies | None | Internal deps | External/blocking |
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 · 214 lines · 9 tokens per session scan A 2d7bb426d9fc
estimate-issue is a command published in the GitHub repository quay/ai-helpers (3 stars, last pushed 19d ago), licensed MIT. It adds 9 tokens to every session and 1,785 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 2026-09-04.
Other commands, from other repositories
template
Manage issue templates for streamlined issue creation.
sync-linear
Sync current work with Linear ticket status.
add-note
Add an internal or external note to a ConnectWise PSA ticket.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
dispatcher
Pick the next-best repo to work on across the portfolio — rank free repos, recommend one, claim its lease atomically, and route to the entry command.
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.