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 me2resh/apexyard --skill decidegit clone --depth 1 https://github.com/me2resh/apexyardWrote 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/me2resh/apexyard/decide)<a href="https://agentmods.dev/skills/me2resh/apexyard/decide"><img src="https://agentmods.dev/badge/skills/me2resh/apexyard/decide/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/me2resh/apexyard/decide"><img src="https://agentmods.dev/badge/skills/me2resh/apexyard/decide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 131 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00020 | $0.01791 |
| Opus 5.5 | $0.00008 | $0.00716 |
| Sonnet 5.5 | $0.00004 | $0.00358 |
| Haiku 4.5 | $0.00002 | $0.00179 |
Grade A, and why
decide 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing: read docs/skills/shared/writing-rule.md before you write a durable artifact.
/decide — Technical Decision Gate
Forces structured decision-making and creates an auditable Agent Decision Record (AgDR).
Activated role
When /decide runs, activate the Tech Lead role — they own technical decisions within their domain. For decisions that cross the architecture-review threshold (new service, new tech stack, new external integration, major data model change), escalate to the Head of Engineering before creating the AgDR.
If the decision touches auth / crypto / secrets / PII, also involve the Security Auditor for sign-off on the security implications before finalising the choice.
See .claude/rules/role-triggers.md for the full activation protocol.
Process
1. Parse the Decision Topic
Extract the decision topic from $ARGUMENTS. If unclear, ask:
What technical decision do you need to make?
2. Gather Context
Identify decision-relevant context only:
- What problem are we solving?
- What constraints exist?
- What's already in the codebase?
3. List Options
Present 2–4 options in a table:
| Option | Pros | Cons |
|--------|------|------|
| Option A | … | … |
| Option B | … | … |
4. Make the Decision
State the chosen option with justification.
5. Generate the AgDR
Create file at {project-root}/docs/agdr/AgDR-{NNNN}-{slug}.md.
After writing the file, source .claude/hooks/_lib-review-markers.sh from the ops fork and run review_validate_body agdr <path-to-new-AgDR>. Repair any missing title or required section before reporting the decision. This local check does not approve the decision or write a review marker.
Important: AgDRs live in the current project's repository, not centralised. Each project has its own docs/agdr/ folder and its own ID sequence.
What ships with it
2 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.
- 4d ago Changed · -2 lines 988dbbbdc366
- 11d ago Changed · +2 lines 2300830af4f4
- 1mo ago Changed · +28 lines 8b39e6cf8d77
- 1mo ago First seen · 155 lines · 20 tokens per session scan A 3fbd2be52adf
decide is a skill published in the GitHub repository me2resh/apexyard (533 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 1,791 once invoked, about $0.0001 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 2026-08-30.
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