warren: Skill for Claude Code

.agents/skills/seeds-issue-audit/SKILL.md

seeds-issue-audit is a skill for Claude Code, Codex from jayminwest/warren. It costs 67 tokens per session (2,768 once invoked), scanned A, original, MIT.

A procedure for reviewing open Seeds issues, which are entries in the project's issue tracker, and deciding whether completed ones can be closed.

In plain words
What is it for?
Use it to audit the open backlog, close only issues with strong evidence of completion, and report uncertain or blocked issues for human review.
Why use it?
It prevents issues from being closed based only on age, weak signals, or outdated dependency information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; installed under .agents/ (shared by several agents).

This is jayminwest/warren's own configuration. It tells Claude Code and Codex how to work on warren itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything warren configures →

Reuse

Borrowing it

Nothing to install: this file belongs to jayminwest/warren. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/jayminwest/warren/main/.agents/skills/seeds-issue-audit/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/jayminwest/warren

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for seeds-issue-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/jayminwest/warren/seeds-issue-audit/github.svg)](https://agentmods.dev/skills/jayminwest/warren/seeds-issue-audit)
Your own site
<a href="https://agentmods.dev/skills/jayminwest/warren/seeds-issue-audit"><img src="https://agentmods.dev/badge/skills/jayminwest/warren/seeds-issue-audit/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.

agentmods 80×15 button for seeds-issue-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/jayminwest/warren/seeds-issue-audit"><img src="https://agentmods.dev/badge/skills/jayminwest/warren/seeds-issue-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,768 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.02768
Opus 5 $0.00034 $0.01384
Sonnet 5 $0.00013 $0.00554
Haiku 4.5 $0.00007 $0.00277

Measured 9d ago against content hash 42067700875e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

seeds-issue-audit 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 9d 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.

.agents/skills/seeds-issue-audit/SKILL.md · 242 lines

How it starts

The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Protocol: Seeds Issue Audit & Triage

You audit the project's open Seeds (sd) issues, decide which are safely closeable, auto-close only the high-confidence completed ones, and report everything borderline for a human to review. You NEVER guess: every auto-close must cite concrete evidence. Staleness alone is never enough to close anything.

1. Operating Principles

  • Auto-close only HIGH confidence. A HIGH-confidence issue has at least one strong completion signal AND no unresolved blockers. Close it.
  • Report, never close, BORDERLINE. Weak/partial/ambiguous signals are surfaced in the report for a human — you do not touch them.
  • Leave contradicted issues open. Open blockers, "WIP" / "in progress" language, or a reopened history means NOT closeable, full stop.
  • A blocker only counts if it is still OPEN. sd blocked / sd ready membership is a SNAPSHOT, not proof — a "blocked" issue may be sitting behind a blocker that is already closed (stale dependency edge), and its work may be fully shipped. Audit the blocked set too; never auto-exclude it. Re-resolve every blocker's LIVE status before trusting the gate.
  • Cascade until the set stabilizes. Closing an issue can unblock its downstream consumers. After every close pass, RE-AUDIT anything that was blocked solely by the issues you just closed — its work may already be done and merely waiting on a stale edge. Loop until a pass closes nothing.
  • Plans drift ahead of their seeds. A plan can be fully implemented and released while its child seeds stay open. Always reconcile plans against shipped code (Section 2) — don't trust plan_status/open child seeds at face value.
  • Evidence-first. Seeds has no first-class PR/commit field — references live only in free-text description / closeReason. Confirm them against git / gh before trusting them.
  • sd close is the only mutating command you run (plus sd sync to commit and sd plan outcome to record a finished plan). It is reversible via reopen. Never run sd update on others' issues; never push.

Read the full file on GitHub · 242 lines

Changes

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.

  1. 9d ago First seen · 242 lines · 67 tokens per session scan A 42067700875e

Subscribe to this mod's changes

seeds-issue-audit is a skill published in the GitHub repository jayminwest/warren (387 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 2,768 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

factory-handoff

Hand one exact agent-ready ticket to the central Factory runtime over the configured SSH forced-command boundary. Use when an operator asks to hand off an existing ticket or a prose request instead of implementing it in the current session.

watt-mind/factory · 47 tokens

ticket-spec

Turn a raw Linear Triage ticket into a fully specified ai:agent-ready one by exploring the codebase. Use when specifying, refining, or promoting tickets, or when asked why a ticket isn't dispatchable.

watt-mind/factory · 45 tokens

autogpt-agents

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

synthetic-sciences/openscience · 39 tokens

Task Convention

Track multi-step work in useAgent's durable task manager, with .useagent/tasks.md as an explicit repo-local or offline fallback.

useagenthq/useagent · 30 tokens

prd-builder

Use to construct a complete Product Requirements Document for a mobile app from a vision file. Used primarily by the CPO agent. Triggers on requests to "write the PRD", "spec out the product", or as part of /app-plan.

vmobifystudio/app-dev-team · 53 tokens

brownfield-onboarding

Use when pointing the team at an EXISTING, already-built app instead of a blank project — detects the stack, reverse-engineers the as-built architecture, and classifies remediation work as safe-to-auto-fix vs risky-needs-approval. Triggered by /app-onboard, /app-audit, and by /app-run when it detects a non-empty app…

vmobifystudio/app-dev-team · 81 tokens