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 gozhang2/loop-engineering-kit --skill spec-to-donegit clone --depth 1 https://github.com/gozhang2/loop-engineering-kitWrote 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/gozhang2/loop-engineering-kit/spec-to-done)<a href="https://agentmods.dev/skills/gozhang2/loop-engineering-kit/spec-to-done"><img src="https://agentmods.dev/badge/skills/gozhang2/loop-engineering-kit/spec-to-done/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/gozhang2/loop-engineering-kit/spec-to-done"><img src="https://agentmods.dev/badge/skills/gozhang2/loop-engineering-kit/spec-to-done.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 | $0.00098 | $0.04626 |
| Opus 5.5 | $0.00039 | $0.01850 |
| Sonnet 5.5 | $0.00020 | $0.00925 |
| Haiku 4.5 | $0.00010 | $0.00463 |
Grade A, and why
spec-to-done 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 1mo 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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec To Done
Drive a reviewed spec to delivered, integrated closure. The output is a closure record backed by a criterion-to-evidence ledger and a green integrated check — not a pile of individually green tasks.
This is a portable workflow, not a runtime. It works with one agent building items sequentially or a team of implementers in parallel, on any repository, task system, or none.
Treat it as a protocol, not a procedure: teams may carry the messages in JSON, markdown, issues, or PR comments. Six invariants make the loop trustworthy, whatever the carrier:
- Every worker gets bounded work.
- Every handback is reviewable.
- Every gate decision explains the basis for trust or rejection.
- Every acceptance criterion maps to evidence, a waiver, or a named blocker.
- Every owner-only decision is escalated, never improvised.
- Closure never overclaims.
Everything else — item sizing, ordering, tooling, how hard to inspect a given handback — is supervisor judgment, and good supervisors will invent moves this file does not list. The protocol's job is to make those moves inspectable, not to replace them.
Evidence First
"Done" in this loop is an evidence claim, not a status update. Every part of the loop exists to produce, check, or record evidence:
- Every claim names something inspectable — a commit, diff, test, check, run, artifact, screenshot, review, trace, or recorded waiver. If a reader cannot open it, it is not evidence.
- Evidence covers process as well as result. The result evidence says what was achieved; the work trace — how it was done — says whether to trust it.
- The criterion-to-evidence ledger is the loop's spine. Gates read evidence against criteria; they do not read narratives, confidence, or effort.
- No local evidence, no merge. No integrated evidence, no closure. Task-local green is not done — it is supporting evidence for one item.
- Missing evidence is never papered over: a criterion is open, blocked, or carries a waiver recorded by the decision owner. A waiver is a decision, not missing evidence.
What ships with it
1 file 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.
- 1mo ago First seen · 385 lines · 98 tokens per session scan A 175c4eb08e51
spec-to-done is a skill published in the GitHub repository gozhang2/loop-engineering-kit (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 98 tokens to every session and 4,626 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 2026-08-31.
Other skills, from other repositories
codex-issue-coordinator
Coordinates a large batch of GitHub issues through separate Codex worker threads, tested pull requests, review loops, and gated merges. Use when the user asks one Codex thread to manage several coding sessions or complete a parent issue, milestone, or issue batch.
plan
Turns a reviewed spec or decided brief into ordered tasks for separate agent runs. Use for implementation tasks, tracker tickets, or useful milestones. Do not use for one coding task or its short execution outline.
corp-new
A workflow for creating a new department folder inside a local agent headquarters, with its own rules, skills, tasks, and links back to the headquarters.
manager
A session-to-GitHub tracker that creates, updates, and reads issues across repositories, including their labels, parent epics, and project-board placement.
corp-doctor
A guided maintenance and setup tool for a Personal Corp system, meaning a business workflow built from AI agents, department repositories, and shared rules. It checks what exists before making changes.
gh-issues
Use when creating, searching, updating, or managing GitHub issues via CLI. Triggers: "issue", "create issue", "gh issue", "task tracking", "context", "handoff", "resume task", "session context", "save progress", "active tasks", "in-progress", "my tasks", "open issues". Covers: gh commands, bulk operations, JSON/jq…