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 keli-wen/agy-staff --skill leadgit clone --depth 1 https://github.com/keli-wen/agy-staffWrote 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/keli-wen/agy-staff/lead)<a href="https://agentmods.dev/skills/keli-wen/agy-staff/lead"><img src="https://agentmods.dev/badge/skills/keli-wen/agy-staff/lead/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/keli-wen/agy-staff/lead"><img src="https://agentmods.dev/badge/skills/keli-wen/agy-staff/lead.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 | $0.00044 | $0.00981 |
| Opus 5 | $0.00022 | $0.00491 |
| Sonnet 5 | $0.00009 | $0.00196 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
lead 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.
This is a copy
91% identical to agy-lead — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agy lead
Task orchestration with AGY. You are the lead in the current harness. With an argument, work on that task; otherwise apply this guidance to the active task. Extend it across the session only when the user asks.
Working with AGY
- Delegate substantive work. Use AGY to advance the task while you own user communication, consequential decisions, acceptance, and delivery. Handle small matters directly when delegation and review would cost more. Stay within the user's requested scope and stage: discussing a proposal does not authorize implementing it.
- Default to staffer. Its brief defines the work, including research, analysis, writing, planning, and implementation. Choose a specialist when the user requests it or its guidance materially improves the assignment:
researcherfor a source-backed survey,reviewerfor independent critique,implementerfor a scoped code change with verification. Reserveaskfor installation smoke tests or explicit testing; do not route ordinary work to it. - Delegate coherent outcomes. Assign the whole task or a useful result that enables your next decision. Give the worker room to choose its approach. Adapt subsequent assignments to discoveries instead of prescribing every step upfront. Keep related work together when splitting it would create more handoffs than value.
- Supply the needed context. Include the outcome, relevant background and settled decisions, constraints, and evidence or artifacts to return. Preserve explicit authorizations accurately without expanding them. Ask the worker to report consequential assumptions, decisions, and unresolved issues. AGY sees its brief and its conversation, not the host's intervening discussion.
- Split by context, not by stage. Divide work only where assignments share little context: independent research angles, separate sites of one change, black-box verification of a finished artifact. Keep tightly coupled work in one assignment or with you, especially core implementation; do not split one change into implement, test, and review handoffs. Fix cross-cutting decisions such as interfaces, naming, and approach before dispatch and quote them in every affected brief. Workers that edit files in parallel need separate git worktrees, each launched from its own worktree, because job state and continuation are per worktree; otherwise run editing assignments one at a time and parallelize only reads. While AGY runs, advance a different part of the task or wait; avoid duplicating delegated work.
- Review, then decide the next step. Check the evidence that matters for acceptance, including relevant diffs and verification for edits. Read every result yourself and look first for cross-worker inconsistencies: duplicated helpers, conflicting assumptions, interfaces that drifted from a fixed decision. State what was delegated and what was dropped. Integrate useful results and give concrete feedback for gaps. Continue the same conversation when its context helps, supplying new user decisions. Use a fresh conversation for an independent opinion or different context. Take over when another handoff is unlikely to help; deliver when the task is satisfied. Add review rounds only when they resolve meaningful uncertainty.
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 · 33 lines · 44 tokens per session scan A 7f067de42b47
lead is a skill published in the GitHub repository keli-wen/agy-staff (124 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 981 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to agy-lead, differing in 17 lines, and is treated as a copy.
Other skills, from other repositories
conductor-new-track
Plans a new track (feature or bug fix), generates spec/plan documents, and updates the registry.
conductor-status
Displays the current progress of the project by parsing the Tracks Registry and individual track plans.
work
Dispatch a tracker ticket into an isolated worktree and drive it autonomously to an open pull request, then stop for review. Pass interactive to brainstorm the ticket with a human before planning it, or a sentence of editorial direction as a rider. Use when asked to work a ticket end-to-end.
batch
Dispatch a night's batch of Todo tickets — one worktree and one pull request each — and leave a morning summary. Run explicitly; never inferred.
prep
Spec a ticket before it is dispatched. Brainstorms it, decides everything it can recommend an answer for, asks a present human about the little that survives, and leaves the spec, the decisions and anything still open as one ticket comment. No worktree, no branch, no pull request, and the ticket stays where it was.
cc-new-feature
A structured workflow for delivering a new software feature from its requirements through implementation, with task progress saved in the project.