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 skills/smallnest/pigo/to-issuesnpx skills add smallnest/pigo --skill to-issuesgit clone --depth 1 https://github.com/smallnest/pigoWrote 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/skills/smallnest/pigo/to-issues)<a href="https://agentmods.dev/skills/smallnest/pigo/to-issues"><img src="https://agentmods.dev/badge/skills/smallnest/pigo/to-issues.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 | $0.00092 | $0.01929 |
| Opus 5 | $0.00046 | $0.00964 |
| Sonnet 5 | $0.00018 | $0.00386 |
| Haiku 4.5 | $0.00009 | $0.00193 |
Grade A, and why
to-issues 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 4d 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
to-issues — PRD/SPEC to Issues
Decompose a PRD and/or technical SPEC into small, independent, implementable Issues, then create them in your chosen platform. Works standalone — you don't need to have run /prd first.
The Job
- Locate input — find a PRD or SPEC file (auto-detect or user-specified)
- Decompose into Issues — break User Stories into implementable tickets
- Review with user — present Issue list for approval and adjustment
- Choose platform — GitHub / Local / Baidu iCafe
- Create Issues — create all tickets and print summary
Step 1: Locate Input
Find the input document:
What should I base the Issues on?
A. Auto-detect: scan tasks/ for recent PRDs and SPECs
B. Specific PRD file (e.g., tasks/prd-priority-system.md)
C. Specific SPEC file (e.g., tasks/spec-priority-system.md)
D. Both PRD and SPEC (best: PRD for requirements, SPEC for technical contracts)
E. Paste requirements directly
If auto-detecting, list available files and let the user choose.
If both PRD and SPEC are available, use the SPEC's Section 10.2 (Issue Mapping) as the primary guide, supplemented by PRD's User Stories. If only PRD is available, generate Issues directly from User Stories.
Step 2: Decompose into Issues
Based on the input document(s), generate a list of Issues. Follow these rules:
- One Issue per User Story — each US-XXX becomes at least one Issue
- Split large stories — if a US has 5+ acceptance criteria or spans frontend + backend, split into 2-3 smaller Issues with clear dependencies
- Merge tiny stories — if a US has only 1-2 trivial criteria, merge it with a related US into a single Issue
- Each Issue must be independently implementable — a single agent session should be able to complete it
- Number Issues sequentially starting from 1
- If SPEC is available — enrich Issues with SPEC references (API endpoints, data model sections, error handling contracts)
Issue format:
Issue #N: [Title]
---
Description: [From US description, with context]
Acceptance Criteria:
- [ ] [From US acceptance criteria]
- [ ] ...
Dependencies: [None / Issue #X]
Type: [backend / frontend / fullstack / ui / infra]
Priority: [high / medium / low]
SPEC Reference: [Section X.Y — only if SPEC available]
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.
- 4d ago First seen · 230 lines · 92 tokens per session scan A cd0863b14fb6
to-issues is a skill published in the GitHub repository smallnest/pigo (419 stars, last pushed 4d ago), licensed MIT. It adds 92 tokens to every session and 1,929 once invoked, about $0.0005 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.
Other skills, from other repositories
wayfinder
Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
ask-matt
Ask which skill or flow fits your situation. A router over the skills in this repo.
teach
Teach the user a new skill or concept, within this workspace.
writing-for-agents
Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
diagnosing-bugs
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
setup-matt-pocock-skills
Configure this repo for the engineering skills: set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.