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 skills add dmae97/omk --skill whygit clone --depth 1 https://github.com/dmae97/omkWrote 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/dmae97/omk/why)<a href="https://agentmods.dev/skills/dmae97/omk/why"><img src="https://agentmods.dev/badge/skills/dmae97/omk/why/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/skills/dmae97/omk/why"><img src="https://agentmods.dev/badge/skills/dmae97/omk/why.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 | $0.00092 | $0.02177 |
| Opus 5.5 | $0.00037 | $0.00871 |
| Sonnet 5.5 | $0.00018 | $0.00435 |
| Haiku 4.5 | $0.00009 | $0.00218 |
Grade A, and why
pstack-why 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Why
Investigate the motivation and intent behind code. The companion how skill answers what the code does and how it works. why answers what forces led to its shape.
Each spawn below names a role line in the pstack settings file (~/.cursor/rules/pstack-models.mdc in Cursor, ~/.claude/rules/pstack-models.md in Claude Code, ~/.agents/pstack-models.md in other harnesses) and a default. Set model to that line's value, or to the default if the file or the line is missing. Leave model unset when the value is auto or inherit-parent. If your subagent tool rejects a slug, use the default and say so. If it rejects the default, use the closest valid slug of the same family from its error message or your harness's model list. Pick each subagent's reasoning level and fast or standard speed for the job, per the Subagents section of the poteto-mode skill.
Every spawn is generalPurpose with readonly: false (agent mode). Do not use readonly/Ask mode. It strips MCP access, which disables the MCP-backed investigators and the synthesizer's citation spot-checks. Investigators still shouldn't write anything.
Operating Posture
Operate as a careful, cautious, and precise investigator. Be honest about what you know vs what you're inferring. Read references/epistemics.md for the full confidence framework and phrasing guide. The synthesizer must follow it.
Step 1. Understand the Target and the Question
The target is usually a chunk of code, a pattern, a feature, or a named design decision. The question is usually a design rationale, a tradeoff, a motivating edge case, an external constraint, dead code, or a broad history sweep.
If the target is vague ("why do we do it this way?" with no clear referent), make your best guess from conversation context (open files, recent edits, cursor location, what was just discussed). State your interpretation briefly so the user can redirect if you're off, then proceed.
Step 2. Establish the Code Anchor
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/epistemics.md 6.6 KB
- references/investigator-prompt.md 5.4 KB
- references/source-playbook.md 1.3 KB
- references/sources/code-archaeology.md 1.4 KB
- references/sources/databricks.md 6.8 KB
- references/sources/datadog.md 4.9 KB
- references/sources/incident-postmortem.md 372 B
- references/sources/linear.md 2.9 KB
- references/sources/notion.md 2.8 KB
- references/sources/sentry.md 2.0 KB
- references/sources/slack.md 1.3 KB
- references/synthesizer-prompt.md 7.0 KB
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 First seen · 101 lines · 92 tokens per session scan A c9520f5237c9
pstack-why is a skill published in the GitHub repository dmae97/omk (149 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 2,177 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-27.
Other skills, from other repositories
repo-hygiene
Use when the scheduled repo-hygiene workflow runs from GitHub Actions (or an operator dry-run) to scan the repository for small, certain docs/test/code hygiene issues and fix them as one batched branch.
codew-release-qa-sweep
Use before claiming Codewhale release work is done: run the full gate sweep and list the manual QA targets.
gh-file-issue
Use when filing a new Codewhale GitHub issue: turn a bug or idea into a well-formed, actionable issue with repro, acceptance criteria, labels, and milestone.
gh-treasure-hunt
Hunt the issue/PR queue for highest value-over-risk wins: clean focused community PRs, already-implemented issues to close, safe quick-fixes.
test-failure-explorer
Import and query an existing Vitest 3.2 JSON report to explore test failures, file-level errors and original diagnostic evidence.
money
Skill "money" from Hmbown/Codewhale, covering money, when to use, setup, workflow and non-goals.