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 fmflurry/settings-opencode --skill whygit clone --depth 1 https://github.com/fmflurry/settings-opencodeWrote 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/fmflurry/settings-opencode/why)<a href="https://agentmods.dev/skills/fmflurry/settings-opencode/why"><img src="https://agentmods.dev/badge/skills/fmflurry/settings-opencode/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/fmflurry/settings-opencode/why"><img src="https://agentmods.dev/badge/skills/fmflurry/settings-opencode/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 | $0.00075 | $0.01778 |
| Opus 5.5 | $0.00030 | $0.00711 |
| Sonnet 5.5 | $0.00015 | $0.00356 |
| Haiku 4.5 | $0.00007 | $0.00178 |
Grade A, and why
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 14d 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 — 136 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.
Companion to the how skill. how answers what the code does and how it works. why answers what forces led to its shape.
Spawn investigators with subagent_type: why-investigator and the synthesizer with subagent_type: why-synthesizer (Claude Code: Agent tool; OpenCode: task tool). Models come from those agent definitions; never pass model. Subagents cannot spawn subagents, so run this skill from the primary agent.
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
Parse what the user is asking. 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, selection, 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
Before spawning investigators, anchor the investigation in concrete code. You need:
- The relevant file path(s) and line range(s)
- The key symbols (function names, class names, constants)
- An initial commit list. The last few commits touching the target.
- PR numbers from merge commits (pattern
(#1234)in the subject line)
Build this inline. If you cannot run shell commands (e.g. OpenCode conductor has bash denied), spawn one why-investigator for source control first to build the code anchor, then fan out.
# Blame target lines for last-touch commits
git blame -L <start>,<end> <file>
# Full file history, with patches, through renames
git log --follow -p -- <file>
# Last N commits touching the file, PR numbers visible
git log --oneline -20 -- <file>
# Extract PR numbers from a commit message
git log -1 --format=%B <commit>
What ships with it
6 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.
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.
- 14d ago First seen · 136 lines · 75 tokens per session scan A 48e64c5c4b77
why is a skill published in the GitHub repository fmflurry/settings-opencode (171 stars, last pushed yesterday), licensed MIT. It adds 75 tokens to every session and 1,778 once invoked, about $0.0003 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 2026-10-02.
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