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 agentmods add skills/kirodotdev/kirocrew/goal-loopnpx skills add kirodotdev/KiroCrew --skill goal-loopgit clone --depth 1 https://github.com/kirodotdev/KiroCrewWhat 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 | $0.00144 | $0.01808 |
| Opus 5 | $0.00072 | $0.00904 |
| Sonnet 5 | $0.00029 | $0.00362 |
| Haiku 4.5 | $0.00014 | $0.00181 |
Grade A, and why
goal-loop 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 3d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
goal-loop
Thin orchestration skill on top of self-nudge-loop. One extra file
(GOAL.md) and one extra script (scaffold.sh) that calls the underlying
self-nudge-loop scaffold and appends goal-specific conventions.
What you get
After running this skill's scaffold.sh, the anchor directory contains:
<anchor>/
├── GOAL.md ← your goal statement + issue-discovery rules (this skill)
├── LOOP.md ← DoD placeholder + REST arming recipe (from self-nudge-loop)
├── README.md ← directory map (from self-nudge-loop)
└── board/ ← kanban-md board, 6 columns (from self-nudge-loop)
The loop agent re-reads GOAL.md + LOOP.md every cycle. That's the
"mission briefing" — everything else is session state.
When to use
- User sets a concrete, verifiable goal ("get this test suite to 100% pass", "migrate all callers off module X", "drain DLQ Y").
- You want the agent to discover issues itself (grep TODO/FIXME, failed tests, open tickets) and convert them to board cards.
- You trust the agent to run for 10+ cycles autonomously without human per-step review.
When NOT to use
- One-off fix → just use the agent directly
- Already-defined backlog → use
self-nudge-loop/scaffold.shdirectly - Goal cannot be expressed as ≤5 shell-checkable DoD criteria → split the goal first
Prerequisites
kanban-md CLI — required for the board operations the loop agent runs
every cycle (kanban-md pick, create, move, handoff). It is a
single-binary Go tool from
github.com/antopolskiy/kanban-md.
Install (pick one):
# Homebrew (macOS/Linux) — recommended, auto-updates
brew install antopolskiy/tap/kanban-md
# Go (if you already have Go on PATH)
go install github.com/antopolskiy/kanban-md/cmd/kanban-md@latest
# Pre-built binary from GitHub Releases
# https://github.com/antopolskiy/kanban-md/releases
# download the linux/amd64 (or matching) tarball, extract to ~/.local/bin/
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.
- 3d ago First seen · 173 lines · 144 tokens per session scan A 9c4effa585f8
goal-loop is a skill published in the GitHub repository kirodotdev/KiroCrew (3,532 stars, last pushed today), licensed Apache-2.0. It adds 144 tokens to every session and 1,808 once invoked, about $0.0007 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.
Other skills, from other repositories
copilotkit-contribute
Use when contributing to the CopilotKit open-source project — forking, cloning, setting up the monorepo, creating branches, running tests, and submitting pull requests against CopilotKit/CopilotKit.
kano-backlog
Prioritize and refine a GitHub Issues backlog with the Kano model — categorize every open issue as Must-be, Performance, Attractive, Indifferent, or Reverse, apply Kano + priority labels back to GitHub automatically, and recommend the single best next issue to pick up. Use this whenever the user wants to triage…
vigilante-issue-implementation
Implement a GitHub issue end-to-end when Vigilante dispatches work for a watched repository. Use the provided worktree, respect repository instructions, comment on the issue as work progresses, and report failures back to GitHub.
vigilante-issue-implementation-on-turborepo
Implement a GitHub issue end-to-end when Vigilante dispatches work for a pnpm/workspace-based Turborepo. Use the provided worktree, respect repository instructions, comment on the issue as work progresses, and report failures back to GitHub.
vigilante-issue-implementation-on-bazel
Implement a GitHub issue end-to-end when Vigilante dispatches work for a Bazel monorepo.
vigilante-issue-implementation-on-gradle
Implement a GitHub issue end-to-end when Vigilante dispatches work for a Gradle monorepo.